research framework document

Sustainable Rural Tourism in Himalayan Foothills pp 59–78 Cite as

Research Framework

• Suneel Kumar 2  
• First Online: 20 September 2023

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This section presents the research design, provides a description and justification of the methodological approach and methods used, and details the research framework for the study. In addition, it presents the research objectives and highlights the research hypothesis; discusses about the research area, sampling techniques used, and the sample size drawn for the study; and presents the questionnaire used for collection of data and a detailed view of the statistical tools and techniques used in the study for the analysis purpose.

• Flexible strategies
• Sustainable development goals
• Judgmental sampling
• Snowball sampling
• Interpretive structural modeling
• MICMAC analysis
• Continuity-change matrix
• HML-VDB analysis

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Kumar, S. (2023). Research Framework. In: Sustainable Rural Tourism in Himalayan Foothills. Springer, Cham. https://doi.org/10.1007/978-3-031-40098-8_3

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Theoretical Framework Example for a Thesis or Dissertation

Published on October 14, 2015 by Sarah Vinz . Revised on July 18, 2023 by Tegan George.

Your theoretical framework defines the key concepts in your research, suggests relationships between them, and discusses relevant theories based on your literature review .

A strong theoretical framework gives your research direction. It allows you to convincingly interpret, explain, and generalize from your findings and show the relevance of your thesis or dissertation topic in your field.

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Sample problem statement and research questions, sample theoretical framework, your theoretical framework, other interesting articles.

Your theoretical framework is based on:

• Your problem statement
• Your research questions
• Your literature review

A new boutique downtown is struggling with the fact that many of their online customers do not return to make subsequent purchases. This is a big issue for the otherwise fast-growing store.Management wants to increase customer loyalty. They believe that improved customer satisfaction will play a major role in achieving their goal of increased return customers.

To investigate this problem, you have zeroed in on the following problem statement, objective, and research questions:

• Problem : Many online customers do not return to make subsequent purchases.
• Objective : To increase the quantity of return customers.
• Research question : How can the satisfaction of the boutique’s online customers be improved in order to increase the quantity of return customers?

The concepts of “customer loyalty” and “customer satisfaction” are clearly central to this study, along with their relationship to the likelihood that a customer will return. Your theoretical framework should define these concepts and discuss theories about the relationship between these variables.

Some sub-questions could include:

• What is the relationship between customer loyalty and customer satisfaction?
• How satisfied and loyal are the boutique’s online customers currently?
• What factors affect the satisfaction and loyalty of the boutique’s online customers?

As the concepts of “loyalty” and “customer satisfaction” play a major role in the investigation and will later be measured, they are essential concepts to define within your theoretical framework .

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Below is a simplified example showing how you can describe and compare theories in your thesis or dissertation . In this example, we focus on the concept of customer satisfaction introduced above.

Customer satisfaction

Thomassen (2003, p. 69) defines customer satisfaction as “the perception of the customer as a result of consciously or unconsciously comparing their experiences with their expectations.” Kotler & Keller (2008, p. 80) build on this definition, stating that customer satisfaction is determined by “the degree to which someone is happy or disappointed with the observed performance of a product in relation to his or her expectations.”

Performance that is below expectations leads to a dissatisfied customer, while performance that satisfies expectations produces satisfied customers (Kotler & Keller, 2003, p. 80).

The definition of Zeithaml and Bitner (2003, p. 86) is slightly different from that of Thomassen. They posit that “satisfaction is the consumer fulfillment response. It is a judgement that a product or service feature, or the product of service itself, provides a pleasurable level of consumption-related fulfillment.” Zeithaml and Bitner’s emphasis is thus on obtaining a certain satisfaction in relation to purchasing.

Thomassen’s definition is the most relevant to the aims of this study, given the emphasis it places on unconscious perception. Although Zeithaml and Bitner, like Thomassen, say that customer satisfaction is a reaction to the experience gained, there is no distinction between conscious and unconscious comparisons in their definition.

The boutique claims in its mission statement that it wants to sell not only a product, but also a feeling. As a result, unconscious comparison will play an important role in the satisfaction of its customers. Thomassen’s definition is therefore more relevant.

Thomassen’s Customer Satisfaction Model

According to Thomassen, both the so-called “value proposition” and other influences have an impact on final customer satisfaction. In his satisfaction model (Fig. 1), Thomassen shows that word-of-mouth, personal needs, past experiences, and marketing and public relations determine customers’ needs and expectations.

These factors are compared to their experiences, with the interplay between expectations and experiences determining a customer’s satisfaction level. Thomassen’s model is important for this study as it allows us to determine both the extent to which the boutique’s customers are satisfied, as well as where improvements can be made.

Figure 1 Customer satisfaction creation 

Of course, you could analyze the concepts more thoroughly and compare additional definitions to each other. You could also discuss the theories and ideas of key authors in greater detail and provide several models to illustrate different concepts.

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National Institute of Standards and Technology

Nist technical series publication.

NIST SP 1500-18r2

NIST Research Data Framework (RDaF)

Version 2.0

Robert J. Hanisch

Office of Data and Informatics

Material Measurement Laboratory

Debra L. Kaiser

Andrea Medina-Smith

Bonnie C. Carroll

Eva M. Campo

Campostella Research and Consulting

Alexandria, VA

This publication is available free of charge

https://doi.org/10.6028/NIST.SP.1500-18r2

February 2024

The NIST Research Data Framework (RDaF) is a multifaceted and customizable tool that aims to help shape the future of open data access and research data management (RDM). The RDaF will allow organizations and individual researchers to develop their own RDM strategy. Though NIST is leading the RDaF, most of the content in the current version 2.0, which supersedes preliminary V1.0 and interim V1.5, was obtained via engagement with national and international leaders in the research data community. NIST held a series of three plenary and 15 stakeholder workshops from October 2021 to September 2023. Workshop attendees represented many stakeholder sectors: US government agencies, national laboratories, academia, industry, non-profit organizations, publishers, professional societies, trade organizations, and funders (public and private), including international organizations. The audience for the RDaF is the entire research data community in all disciplines—the biological, chemical, medical, social, and physical sciences and the humanities. The RDaF is applicable from the organization to the project level and encompasses a wide array of job roles involving RDM, from executives and Chief Data Officers to publishers, funders, and researchers. The RDaF is a map of the research data space that uses a lifecycle approach with six stages to organize key information concerning RDM and research data dissemination. Through a community-driven and in-depth process, NIST identified and defined specific, high-priority topics and subtopics for each lifecycle stage. The topics and subtopics are programmatic and operational activities, concepts, and other important factors relevant to RDM which form the foundation of the framework. This foundation enables organizations and individual researchers to use the RDaF for self-assessment of their RDM status. Each subtopic has several informative references —resources such as guidelines, standards, and policies—to help a user understand or implement that subtopic. As such, the RDaF may be considered a “best practices” document. Fourteen overarching themes —topic areas identified as pervasive throughout the framework—illustrate the connections among the six lifecycle stages. Finally, the RDaF includes eight sample profiles for common job functions or roles. Each profile contains topics and subtopics an individual in the given role needs to consider in fulfilling their RDM responsibilities. Individual researchers and organizations involved in the research data lifecycle will be able to tailor these sample profiles or generate entirely new profiles for their specific job function. The methodologies used to generate the content of this publication, RDaF V2.0, are described in detail. An interactive web application has been developed and released that provides an interface for all the components of the RDaF mentioned above and replicates this document. The web application is easy and intuitive to navigate and provides new functionality enabled by the interactive environment.

Publications in the SP1500 subseries are intended to capture external perspectives related to NIST standards, measurement, and testing-related efforts. These external perspectives can come from industry, academia, government, and others. These reports are intended to document external perspectives and do not represent official NIST positions. The opinions, recommendations, findings, and conclusions in this publication do not necessarily reflect the views or policies of NIST or the United States Government.

Certain commercial entities, equipment, or materials may be identified in this document to describe an experimental procedure or concept adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the entities, materials, or equipment are necessarily the best available for the purpose.

NIST Technical Series Policies

Copyright, Fair Use, and Licensing Statements

NIST Technical Series Publication Identifier Syntax

Publication History

Approved by the NIST Editorial Review Board on 2023-12-21

Supersedes NIST Series 1500-18 version 1.5 (May 2023) https://doi.org/10.6028/NIST.SP.1500-18r1 ; NIST Series 1500-18 (February 2021) https://doi.org/10.6028/NIST.SP.1500-18

How to Cite this NIST Technical Series Publication

Hanisch, RJ; Kaiser, D; Yuan, A; Medina-Smith, A; Carroll, B; Campo, E (2023) NIST Research Data Framework (RDaF) Version 2.0. (National Institute of Standards and Technology, Gaithersburg, MD), NIST Special Publication (SP) 1500-18r2. https://doi.org/10.6028/NIST.SP.1500-18r2

NIST Author ORCID IDs

Robert Hanisch: 0000-0002-6853-4602

Debra Kaiser: 0000-0001-5114-7588

Alda Yuan: 0000-0001-9619-306X

Andrea Medina-Smith: 0000-0002-1217-701X

Bonnie Carroll: 0000-0001-8924-1000

Eva Campo: 0000-0002-9808-4112

Contact Information

[email protected]

Version 2.0 of the NIST Research Data Framework builds on the Preliminary version 1.0 released in February 2021 and on the interim version 1.5 released in May 2023, and incorporates input from many stakeholders. Version 2.0 has more than twice as many   topics  and  subtopics  as V1.0 and includes new sections. The major new sections are  overarching themes : terms prevalent in multiple lifecycle stages, and  profiles , which provide a list of the most relevant topics and subtopics for a given job function or role within the research data management ecosystem. A Request for Information (RFI) based on interim V1.5 was posted in the Federal Register in early June 2023. All comments received in response to this RFI were considered and the RDaF V1.5 was revised as appropriate. A draft of this modified version was presented at a stakeholder workshop held in September 2023.

Author Contributions

Robert Hanisch : Conceptualization, Methodology, Supervision, Writing- review and editing; Debra Kaiser : Formal Analysis, Methodology, Writing- review and editing; Alda Yuan : Formal Analysis, Methodology, Project Administration, Writing- original draft, Writing- review and editing, Visualization; Andrea Medina-Smith : Data Curation, Formal Analysis, Visualization, Software, Writing- review and editing; Bonnie Carroll : Conceptualization, Supervision, Writing- review and editing; Eva M. Campo : Data Curation, Visualization, Writing- review and editing.

Acknowledgments

The completeness, relevance, and success of the NIST RDaF is wholly dependent on the input and participation of the broad research data community. NIST is grateful to all the workshop participants and others who have provided input to this effort. First and foremost, NIST thanks the members of the RDaF Steering Committee, past and present, who have given sound advice and shared their invaluable expertise since the inception of the RDaF in December 2019: Laura Biven, Cate Brinson, Bonnie Carroll (Chair), Mercè Crosas, Anita de Waard, Chris Erdmann, Joshua Greenberg, Martin Halbert, Hilary Hanahoe, Heather Joseph, Mark Leggott, Barend Mons, Sarah Nusser, Beth Plale, and Carly Strasser.

The RDaF team is also grateful to Susan Makar from the NIST Research Library for assistance with the informative references and to Angela Lee for development of the V2.0 interactive web application. Thanks to Eric Lin and James St. Pierre for their critical advice.

Thanks to the former members of the RDaF team including Breeze Dorsey, Laura Espinal, and Tamae Wong. Thanks as well to Campostella Research and Consulting for providing administrative support for the project and technical support for the natural language processing work. Our appreciation also goes to the NIST Material Measurement Laboratory (MML) leadership for their support and to all participants of the various workshops held to solicit community feedback, particularly those individuals who volunteered to serve as discussion leaders.

And finally, thanks to all involved with the NIST Cybersecurity Framework, which provided an initial model for development of the RDaF.

Keywords Research data, research data ecosystem, research data framework, research data lifecycle, research data management, research data dissemination, use, and reuse, research data governance, research data sharing, research data stewardship, open data.

1 Introduction

NIST’s Research Data Framework (RDaF) is designed to help shape the future of research data management (RDM) and open data access. Research data are defined here as “the recorded factual material commonly accepted in the scientific community as necessary to validate research findings.”[ 1 ] The motivation for the RDaF as articulated in the first RDaF publication V1.0 [ 2 ]—that the research data ecosystem is complicated and requires a comprehensive approach to assist organizations and individuals in attaining their RDM goals—has not changed since the project was initiated in 2019. Developed through active involvement and input from national and international leaders in the research data community, the RDaF provides a customizable strategy for the management of research data. The audience for the RDaF is the entire research data community, including all organizations and individuals engaged in any activities concerned with RDM, from Chief Data Officers and researchers to publishers and funders. The RDaF builds upon previous data-focused frameworks but is distinct through its emphasis on research data, the community-driven nature of its formulation, and its broad applicability to all disciplines, including the social sciences and humanities.

The RDaF is a map of the research data space that uses a lifecycle approach with six high-level lifecycle stages to organize key information concerning RDM and research data dissemination. Through a community-driven and in-depth process, stakeholders identified topics and subtopics —programmatic and operational activities, concepts, and other important factors relevant to RDM. These topics and subtopics, identified via stakeholder input, are nested under the six stages of the research data lifecycle. A partial example of this structure is illustrated in Fig. 1 .

Fig. 1 — Partial organizational structure of the framework foundation

The components of the RDaF foundation shown in Fig. 1 —lifecycle stages and their associated topics and subtopics—are defined in this document. In addition, most subtopics have several informative references —resources such as guidelines, standards, and policies—that assist stakeholders in addressing that subtopic. Specific standards and protocols provided in the text or informative references may only be relevant for certain RDM situations. A link to the complete list of informative references is given in Appendix A .

The RDaF is not prescriptive; it does not instruct stakeholders to take any specific approach or action. Rather, the RDaF provides stakeholders with a structure for understanding the various components of RDM and for selecting components relevant to their RDM goals. The RDaF also includes sample profiles , which contain topics and subtopics an individual in a job role or function are encouraged consider in fulfilling their RDM responsibilities. Researchers and organizations involved in the research data lifecycle will be able to tailor these profiles using a supplementary document and online tools that will be available on the RDaF homepage . Entirely new profiles may be generated using a blank on-line template available in this supplementary document. Other uses of the RDaF include self-assessment and improvement of RDM infrastructure and practices for both organizations and individuals.

The RDaF was designed to be applicable to all stakeholders involved in research data. An organization seeking to review their data management policies may use the subtopics to create their own metrics for RDM assessment. Researchers who wish to ensure that their data are open access may use the framework to create a “checklist” of RDM considerations and tasks. A research project leader seeking guidance on how to assign data management roles may use the eight sample profiles as a starting point to create customized lists of responsibilities for individual researchers in their lab.

Since the first publication of the RDaF in 2021 (V1.0 [ 2 ]), NIST has expanded and enriched the framework through extensive engagement with stakeholders in the research data community. This publication, RDaF V2.0, includes updates to V1.0 and new features. Definitions and informative references for each subtopic have been added to improve the usability and applicability of the RDaF. In addition to profiles discussed in the previous paragraph, this document includes overarching themes that appear across multiple lifecycle stages and a list of many of the key organizations in the RDM space (see Appendix B ). The methodology used to generate the content of V2.0 is described in detail in the following section.

Note that the terms “data,” “datasets,” “data assets,” “digital objects,” and “digital data objects” are used throughout the framework depending on the context. Data is the most general and frequently used term. Dataset means a specific collection of data having related content. A data asset is “any entity that is comprised of data which may be a system or application output file, database, document, and web page.”[ 3 ] Digital objects and digital data objects typically have a structure such that they can be understood without the need for separate documentation. In addition, the terms “organization” and “institution” used throughout the framework are synonymous and the terms "RDaF team" and "team" refer to the authors of this publication. Finally, a list that spells out the full names of acronyms and initialisms used throughout this document is provided in Appendix C .

2 Methodology

This section describes the approaches used to develop RDaF V2.0, including brief descriptions of activities since the inception of the project in 2019. Throughout the lifetime of the RDaF project, the Steering Committee members noted previously in the Acknowledgements section were consulted, took leadership roles as discussion leaders at workshops, and provided valuable input and feedback on all aspects of the project.

2.1 Framework Development Through Stakeholder Input

The RDaF is driven by the research data stakeholder community, which can use the framework for multiple purposes such as identifying best practices for research data management (RDM) and dissemination and changing the research data culture in an organization. To ensure that the RDaF is a consensus document, NIST held stakeholder engagement workshops as the primary mechanism to gather input on the framework. The workshops have taken place in three phases, each resulting in further examination and refinement of the framework.

2.1.1 Phase 1: Plenary Scoping Workshop and Publication of the Preliminary RDaF V1.0

In the plenary scoping workshop held in December 2019, a group of about 50 distinguished research data experts selected a research data lifecycle approach as the organizing principle of the RDaF. The RDaF team subsequently selected six lifecycle stages—Envision, Plan, Generate/Acquire, Process/Analyze, Share/Use/Reuse, and Preserve/Discard—from a larger pool of stages suggested by workshop break-out groups. Feedback from this workshop contributed to the publication of the RDaF V1.0, which provides a structured and customizable approach to developing a strategy for the management of research data. The framework core (subsequently renamed foundation in V2.0) consisting of these six lifecycle stages and their associated topics and subtopics is the main result of that publication.

2.1.2 Phase 2: Opening Plenary Workshops

The second phase of the RDaF development began with two virtual plenary workshops held in late 2021. Each workshop had approximately 70 attendees and focused on two cohorts. The university cohort (UC) workshop, co-hosted by the Association of American Universities, the Association of Public Land-grant Universities, and the Association of Research Libraries, was a horizontal cut across various stakeholder roles in universities (e.g., vice presidents of research, deans, professors, and librarians), publishing organizations, data-based trade organizations, and professional societies. In contrast, the materials cohort (MC) workshop, held in cooperation with the Materials Research Data Alliance , was a vertical cut across stakeholder organizations engaged in materials science, including academia, government agencies, industry, publishers, and professional societies.

Prior to the workshops, the attendees selected, or were assigned to, one of six breakout sessions, each focused on a stage in the RDaF research data lifecycle. A NIST coordinator sent the attendees a link to the RDaF publication V1.0, a list of the participants, and definitions of the topics for that session’s lifecycle stage. The agenda for the two workshops included an overview talk by Robert Hanisch on the RDaF, a one-hour breakout session, and a plenary session with summaries presented by an attendee of each breakout and with closing remarks. During the breakout sessions, a discussion leader, recruited by the RDaF team, solicited input from the 10 to 12 participants on the following questions:

What are the most important (two or three) topics and the least important one?

Are there any missing topics?

Should any topics be modified or moved to another lifecycle stage?

The identical questions were posed regarding the subtopics for each topic. Attendee input was captured as notes taken by the session rapporteur and the NIST coordinator and an audio recording. After the two opening plenary workshops, the RDaF team revised the topics and subtopics for the lifecycle stages based on input from the workshops. All six of the lifecycle stages were then reviewed side-by-side for consistency and completeness.

The collective review revealed 14 overarching themes which appeared in multiple lifecycle stages. These themes include metadata and provenance, data quality, the FAIR (Findable, Accessible, Interoperable, and Reusable) data principles, software tools, and cost implications. Section 4 of this document will address all overarching themes in detail.

2.1.3 Phase 3: Stakeholder Workshops

The next step in obtaining community input involved a series of two-hour stakeholder workshops focused on specific roles, equivalent to job functions or position titles. To secure a broad range of feedback, the RDaF team compiled a list of more than 200 invitees, including attendees of previous workshops and additional experts. These invitees were assigned to one of the following 15 roles:

Academic mid-level executive/head of research

Budget/cost expert

Data/IT leader

Data/research governance leader

Institute/center/program director

Open data expert

Professional society/trade organization leader

Provider of data tools/services/infrastructure

Senior executive

Unlike the first two RDaF workshops, these role-focused workshops were composed of smaller groups. The goal of these workshops was to develop profiles, i.e., lists of topics and subtopics important for individuals in a specific role with respect to RDM. Though the target size of these two-hour workshops was 10 to12 participants, the actual number ranged from four to 14. For each workshop, the RDaF team identified and invited an expert to serve as the discussion leader. Two members of the team were assigned to each workshop: a presenter and a rapporteur.

During the workshops, after a brief presentation covering the purpose and structure of the RDaF, participants selected the lifecycle stages most relevant to their assigned role. For each lifecycle stage, participants reviewed the topics and subtopics, and discussed any that were missing, misplaced or unclear. Depending on the length of the discussion, each workshop covered two to four of the lifecycle stages. In addition to requesting input on the topics and subtopics, the NIST coordinators asked participants to consider which topics and subtopics had the greatest influence on their role and those over which they had the greatest influence.

2.2 Framework Revisions per Stakeholder Workshop Input

Most of the input from participants at the Stakeholder Workshops concerned the topics and subtopics, and this input was used to revise them.

2.2.1 Stakeholder Workshop Note Aggregation

After the Stakeholder Workshops, the RDaF team designed a common methodology for collecting and analyzing the feedback, using a template to record the input from each workshop. This template contained the following:

A column for topics and subtopics in a lifecycle stage that were missing, misplaced, or unclear

A column for topics and subtopics relevant to, or missing from, the profile for a role

A section on feedback that addressed the definition of the role

A section on “takeaways” regarding the framework as a whole

A section on proposed new overarching themes

To analyze the feedback from each stakeholder workshop, selected RDaF team members first reviewed the rapporteur’s notes to familiarize themselves with the discussion. Then these team members viewed the recording of the workshop, read through any written comments provided in the workshop chat, and noted every comment in the appropriate section of the template. After the first draft of the template notes was completed, the team members viewed the recording a second time, added any missing comments, and converted each comment and suggestion concerning a topic or subtopic into a potential change for review. Finally, the entire RDaF team considered each potential change and generated an updated interim V1.5 of the framework foundation.

2.2.2 Input for Profile Development

After updating the framework foundation based on the stakeholder feedback, the next step involved the generation of a sample profile for each role addressed by a workshop. As the feedback from the stakeholder workshops concerning profiles was limited and varied in form and specificity, more data were needed to develop these profiles.

The updated topics and subtopics were used to develop blank checklists of topics and subtopics for the lifecycle stages discussed at each of the 15 stakeholder workshops. The appropriate spreadsheet was sent to the participants of a given workshop with instructions to mark those topics and subtopics that were most relevant to the role addressed at that workshop. About 60 participants submitted out a spreadsheet with their responses for the workshop they attended.

The responses were analyzed for similarities and several roles were modified. For example, professors and researchers were grouped together to form one role as professors are typically involved in their groups’ research. After consideration of the participants’ responses, the RDaF team selected eight common job roles for the generation of sample profiles. These roles are AI expert, curator, budget/cost expert, data and IT expert, provider of data tools, publisher, research organization leader, and researcher.

For each sample profile, the RDaF team first calculated the percentage of responses that labeled a subtopic as relevant. When 50% or more of the respondents considered a subtopic to be relevant, it was presumptively deemed relevant for the sample profile. Next, the team considered all comments received with the profile responses as well as all the notes from the Stakeholder Workshop to further flesh out the sample profile. Lastly, the RDaF team consulted with experts in these roles to finalize the profiles.

2.2.3 Request for Information on Interim Version 1.5

Interim V1.5 of the RDaF was published in May 2023 [ 4 ]. This publication included the entire list of topics and subtopics for the six lifecycle stages, definitions, informative references for most of the subtopics, 14 overarching themes, and eight sample profiles.

The RDaF team developed a Request for Information (RFI) that was posted in the Federal Register on June 6, 2023, to communicate updates to the RDaF and receive additional feedback on V1.5. The public had 30 days after release of the RFI to comment on any aspect of the RDaF. The RDaF team reviewed and distilled the comments into almost 70 possible action items which were considered individually within the context of the intent of the framework. All comments received were considered in generating V2.0 of the framework.

2.3 Development of an Interactive Web Application

A web application has been developed and released that presents an interface to the RDaF components—lifecycle stages, topics, subtopics, definitions, informative references, overarching themes, and sample profiles—and thus replicates this RDaF V2.0 document in an interactive environment. In addition to providing an easy means of navigating through the various components and the relationships among them, the web application has new functionality such as the capability to link subtopics to their corresponding informative references and to direct a user to the original source of any reference.

The web application runs on a variety of platforms including Windows, MacOS, and Linux. Development of the software—database design, Entity Framework Core, web application framework, search strategies, and user interface—is the subject of a separate publication in preparation.

3 Framework Foundation – Lifecycle Stages, Topics, and Subtopics

The foundation of the RDaF consists of lifecycle stages, topics, and subtopics selected by the RDaF team using a vast amount of stakeholder input as described in Section 2 . The RDaF research data lifecycle graphic depicted in Fig. 2 is cyclical rather than linear and has six stages defined below. Each stage is interconnected to all other stages, i.e., a stage can lead into any other stage. An organization or individual may initially approach the lifecycle from any stage and subsequently address any other stage. It is likely that an organization or individual will be involved in all lifecycle stages simultaneously, though with different levels of intensity or capacity.

Envision – This lifecycle stage encompasses a review of the overall strategies and drivers of an organization’s research data program. In this lifecycle stage, choices and decisions are made that together chart a high-level course of action to achieve desired organizational goals, including how the research data program is incorporated into an organization’s data governance strategy.

Plan – This lifecycle stage encompasses the activities associated with preparing for data acquisition, selection of data formats and storage solutions, and anticipation of data sharing and dissemination strategies and policies, including how a research data program is incorporated into an organization’s data management plan.

Generate/Acquire – This lifecycle stage covers the generation of raw research data, both experimentally and computationally, within an organization or by an individual, and the collection or acquisition of research data produced outside of an organization.

Process/Analyze – This lifecycle stage concerns the actions performed on generated or externally acquired research data to yield processed research data, typically using software, from which observations and conclusions can be made.

Share/Use/Reuse – This lifecycle stage outlines how raw and processed research data are disseminated, used, and reused within an organization or by an individual and any constraints or encouragements to use/reuse such data. This stage also includes the dissemination, use, and reuse of raw and processed research data outside an organization.

Preserve/Discard – This lifecycle stage delineates the end-of-use and end-of-life provisions for research data by an organization or individual and includes records management, archiving, and safe disposal.

Fig. 2 — Research data framework lifecycle stages

Tables 1 - 6 presented below each cover one research data lifecycle stage and its associated topics and subtopics. The goal of the framework is to be comprehensive while remaining flexible. An organization or individual may find that not every topic and subtopic in a lifecycle stage is relevant to their work. The selection of subtopics to generate a profile for a job or function will be described in Section 5 .

Many lexicons are used in the research data management space. Though the RDaF does not intend to introduce an entirely new vocabulary, it is important to be precise with the use of key terms. For each topic and subtopic, the RDaF provides definitions to assist users in understanding what tasks and responsibilities are associated with that topic or subtopic. To derive these definitions, the RDaF team performed a search of common data lexicons such as CODATA’s Research Data Management Terminology and Techopedia [ 5 , 6 ]. Additionally, the team searched more broadly for common and research data management-specific definitions, including ones for the informative references that provide guidance in the implementation of the RDaF. Some definitions are general or commonly understood and as such have no references. The definitions were checked for consistency with stakeholder feedback. Individual researchers and organizations should keep in mind that these definitions are not prescriptive and consider their own context when determining whether the definitions provided are appropriate.

Table 1. Envision lifecycle stage

Table 2. Plan lifecycle stage

Table 3. Generate/Acquire lifecycle stage

Table 4. Process/Analyze lifecycle stage

Table 5. Share/Use/Reuse lifecycle stage

Table 6. Preserve/Discard lifecycle stage

4 Overarching Themes

The RDaF was refined from the preliminary V1.0 using input from the two opening plenary workshops and the 15 stakeholder workshops. During this refinement process, 14 themes that spanned the various lifecycle stages were identified. Rather than repeat these themes in each stage, they are listed here with a brief explanation of their meaning in the context of research data and research data management (RDM). Following the explanatory narrative, the specific lifecycle stages/topics/subtopics in which each theme appears are shown in tabular form.

In most cases, the overarching themes are supported by explicit references in the framework. In other cases, the themes are implicit. For example, the cost implications and sustainability theme touches on every topic or subtopic, although it is not called out in any lifecycle stage: there is a financial implication to every decision and action that will be considered by those working with research data in any capacity. Note that while these 14 themes emerge from the general definitions of the topics and subtopics, considering the scope of RDM from the perspective of a specific individual or organization, other themes may emerge. Such custom themes can serve as an additional organizing function for job roles, tasks, and other activities represented by the topics and subtopics in the framework.

Separate tables generated for each overarching theme document the topics and subtopics most closely associated to that theme (see Tables 7 - 20 below). There are also two graphics that provide summary information. Figure 3 is a Sankey diagram that provides a visualization of the relationship between each lifecycle stage and each overarching theme. Figure 4 is a matrix table that gives a high-level overview of the relationships between the overarching themes and the topics for each lifecycle stage. (Some of the overarching theme names in Figs. 3 and 4 have been truncated or abbreviated for visualization purposes.)

Fig. 3 — Sankey diagram of the relationships between lifecycle stages and overarching themes

Fig. 4 — Matrix diagram of topics and overarching themes

4.1 Community Engagement

Community engagement , typically broader for RDM practices and more focused for research data projects, is an intentional set of approaches for both listening to and communicating with stakeholders. Successful research, data management, and data curation come from strong engagement with the community of practice or discipline and the organization in which the research is conducted. Community engagement is present in all the RDaF lifecycle stages, although there is an emphasis on it within the Envision and Plan stages. Engagement with stakeholders early in the research process may result in stronger outcomes and uptake of new research. In the other four lifecycle stages, stakeholder engagement is essential for accomplishing the goals established at the beginning of a research project.

Table 7 lists the topics and subtopics that are most relevant to the overarching theme of community engagement.

Table 7. Community engagement (overarching theme)

4.2 Cost Implications and Sustainability

Cost implications and sustainability is a theme that touches every lifecycle stage and most stakeholders in the research ecosystem. From Chief Data Officers and provosts to researchers and grant administrators, cost is a constant focus of all individuals’ work in public and private organizations. Administrators and C-suite officers would typically focus their efforts on the stages of Envision and Plan, while researchers, particularly those with curation duties and service provision, have more impact on the cost implications in the Generate/Acquire, Process/Analyze, Share/Use/Reuse, and Preserve/Discard stages.

Sustainability in research and RDM means sustainable funding, staffing, and preservation models as applied to research data. It is imperative that sustainable plans affecting these three areas are assessed as the areas are developed and maintained to prevent institutions and users from losing access to valuable datasets.

Table 8 lists the topics and subtopics that are most relevant to the overarching theme of cost implications and sustainability.

Table 8. Cost implications and sustainability (overarching theme)

4.3 Culture

Culture is the basis for the entirety of a given organization’s success in managing research data and in nearly every other aspect of running a collective enterprise; culture is what gives an institution or organization its character and consistency over time. Cultures are firmly embedded and stem from both informal practices and formal written policies which can make them difficult to change. Culture shapes norms within an organization and creates glide paths towards ingrained values and behaviors as well as resistance to others. Specifically, culture dictates how research data are valued or supported in an institution.

Table 9 lists the topics and subtopics that are most relevant to the overarching theme of culture.

Table 9. Culture (overarching theme)

4.4 Curation and Stewardship

The processes and procedures to make research data shareable and reusable are typically referred to as curation and stewardship . Both curation and stewardship, and the job roles that are responsible for them, aim to collect, manage, preserve, and promote research data over their lifecycles. Curation is often performed by librarians and others outside of a laboratory or research group, while data stewards tend to work with a specific research group, lab, or department (i.e., a specific discipline) to ensure that they are embedded in research projects from the onset of the Plan lifecycle stage. Because curators tend to work outside of labs, they are typically engaged in research projects much later during the Share/Use/Reuse stage, which may introduce complications. The curation and stewardship theme implicitly touches each lifecycle stage.

Table 10 lists the topics and subtopics that are most relevant to the overarching theme of curation and stewardship.

Table 10. Curation and stewardship (overarching theme)

4.5 Data Quality

Data quality directly impacts a dataset’s fitness for purpose, usability, and reusability. All parties involved in every stage of a dataset’s lifecycle should be cognizant of data quality. The CODATA Research Data Management Terminology [ 5 ] definition of data quality includes the following attributes: accuracy, completeness, update status, relevance, consistency across data sources, reliability, appropriate presentation, and accessibility. Assessment of data quality is not a single process, but rather a series of actions that, over the lifetime of a dataset, collectively assure the greatest degree of quality.

Table 11 lists the topics and subtopics that are most relevant to the overarching theme of data quality.

Table 11. Data quality (overarching theme)

4.6 Data Standards

Data standards, both discipline-specific (e.g., Darwin Core [ 255 ] or NeXus [ 256 ]) and general (e.g., PREMIS [ 257 ] or schema.org [ 258 ]) are implemented by researchers to make their datasets both more FAIR and of higher quality. Researchers may use formal (e.g., ISO [ 259 ] or ANSI [ 260 ] standards) or de facto (e.g., DataCite [ 209 ]) standards for their research community. Use of data standards ensures consistency within a discipline and can reduce cost by decreasing the likelihood that data will have to be created again. Data standards are called out in every lifecycle stage except Envision.

Table 12 lists the topics and subtopics that are most relevant to the overarching theme of data standards.

Table 12. Data standards (overarching theme)

4.7 Diversity, Equity, Inclusion, and Accessibility

Diversity, equity, inclusion, and accessibility (DEIA) is a broad theme covering important social and cultural aspects of a research enterprise. Efforts in DEIA center on growing the sense of belonging for everyone in every laboratory, research group, department, or institution. Research data practices are not immune to biases and historical disadvantages must often be addressed through intentional action. DEIA is important not just for members of underrepresented and marginalized groups, but for the integrity of the research process as a whole. More inclusive research tends to be more rigorous as it introduces different perspectives that enable more complete and broader interpretations of research data. Given the typical challenges associated with cultural changes within an institution, DEIA efforts must be embedded throughout the research data management lifecycle to maximize their effectiveness.

Table 13 lists the topics and subtopics that are most relevant to the overarching theme of diversity, equity, inclusion, and accessibility.

Table 13. Diversity, equity, inclusion, and accessibility (overarching theme)

4.8 Ethics, Trust, and the CARE Principles

Ethics, trust, and the CARE principles encompass the ethical generation, analysis, use, reuse, sharing, disposal, and preservation of data and are pillars of responsible research that are called out throughout the framework. The phrase “as open as possible, as closed as necessary” [ 261 ] comes to mind when working through the ethical implications of sharing data. While ethical choices are often made at the Share/Use/Reuse lifecycle stage, questions and concerns regarding the generation or collection of data are likely to be examined by an institutional or ethics review board and must be considered in the Plan stage. In the Preserve/Discard stage, it is essential to comply with preservation and disposition standards. While the subtopics in the framework are a starting point for understanding how ethics touches every aspect of the research data lifecycle, it is also important that a project be securely grounded in the practices of a given discipline; for example, the standards for historical research will differ from those for economic or healthcare research.

Trust is a factor across the Framework and is the basis for relationships between data producers and users, the funding agencies that support projects, and the institutions that host research. Specific populations will also have various ethical considerations, for example, the CARE Principles for Indigenous Data Governance are quickly becoming the standard for working with indigenous data worldwide [ 262 ].

Table 14 lists the topics and subtopics that are most relevant to the overarching theme of ethics, trust, and the CARE principles.

Table 14. Ethics, trust, and the CARE principles (overarching theme)

4.9 Legal Considerations

As much as technical capabilities structure the ways in which data can be gathered, created, published, and preserved, legal considerations constrain and channel the research data lifecycle. Laws form the background rules governing how data can be managed and shared. Legal considerations can be complex, as they are context-specific, hierarchical, and change over time. They typically vary by sector (e.g., healthcare, finance, education, and public government) and by geographic location (e.g., municipal, regional, national, and international), and are often subject to interpretation. Institutions that share data often use contracts and agreements that rely upon the legal system to order and enforce the terms therein. Laws sometimes restrict access, especially for categories of sensitive data such as personally identifiable information, certain types of healthcare information, and business identifiable information. However, laws can also enable data sharing by providing clear guidelines or directives to provide open data when it is in the public interest. Though legal considerations appear in most of the six lifecycle stages, meticulous planning and preparation make any constraints and compliance with policy requirements less onerous.

Table 15 lists the topics and subtopics that are most relevant to the overarching theme of legal considerations.

Table 15. Legal considerations (overarching theme)

4.10 Metadata and Provenance

Metadata and provenance comprise the information about a dataset that defines, describes, and links the dataset to other datasets and provides contextualization of the dataset [ 91 ]. Metadata are essential to the effective use, reuse, and preservation of research data over time. In the Envision and Plan stages, metadata support legal and regulatory compliance, and are a consideration in planning data outputs and resources.

The table below shows each topic/subtopic that mentions or covers metadata. While the final lifecycle stage (Preserve/Discard) does not explicitly relate to metadata, the existence of descriptive and other metadata is imperative to this stage. The robustness of metadata for a file or dataset determines the level of curation needed for preservation and use: richer metadata allows for better findability, interoperability, and reuse in support of the FAIR data principles, while less robust metadata make all these activities more difficult and time intensive. Poor-quality metadata can render an otherwise important dataset unusable when the creator of the dataset is no longer available.

Included in the metadata theme is provenance, the historical information concerning the data [ 41 ]. Understanding the provenance of a given dataset, including metadata on the experimental conditions used to generate the data, is essential for many disciplines. Without proper provenance documentation, it is difficult to assess the quality and reliability of the data and to publish them with correct metadata. Provenance can be used as a criterion for preservation.

Table 16 lists the topics and subtopics that are most relevant to the overarching theme of metadata and provenance.

Table 16. Metadata and provenance (overarching theme)

4.11 Reproducibility and the FAIR Data Principles

Touching many of the lifecycle stages are reproducibility and the FAIR data principles , which are findability, accessibility, interoperability, and reusability. Reproducible research yields data that can be replicated by the author or other researchers using only information provided in the original work [ 84 ]. Standards for reproducibility differ by research discipline, but typically the metadata and other contextual information needed for reproducibility are similar to those described by the FAIR data principles [ 33 ]. These community-based principles have come to define, for many disciplines, the state to which a published dataset should aspire. By keeping the principles of findability, accessibility, interoperability, and reusability in mind while planning a project or when data are collected, the data will be ready for broader reuse when they are publicly released. Extensions of the FAIR data principles also exist, such as FAIRER, which adds Ethical and Revisable to the base principles [ 263 ].

Table 17 lists the topics and subtopics that are most relevant to the overarching theme of reproducibility and the FAIR data principles.

Table 17. Reproducibility and the FAIR data principles (overarching theme)

4.12 Security and Privacy

Digital data are designed to be easily shared, copied, and transformed, but their mobility can make privacy and security difficult to ensure. Security and privacy issues are fundamentally about trust, both in the institutions and systems that facilitate collection, storage, and transfer of data, as well as the individuals within those institutions. Proper protocols, rationally based on the need to protect vulnerable populations or sensitive information, or stemming from common understandings of security needs, promote trust, which can enable greater data mobility. In the European Union, organizations that collect, store, or hold personal data must comply with the General Data Protection Regulation. [ 264 ] The U.S. does not have such a universal regulation, though various federal laws govern different sectors and types of data, and some states have their own additional regulations. Security and privacy issues arise in the Envision and Plan lifecycle stages, with the results folded into the day-to-day procedures for handling and accessing data and appear again in the Share/Use/Reuse lifecycle stage.

Table 18 lists the topics and subtopics that are most relevant to the overarching theme of security and privacy.

Table 18. Security and privacy (overarching theme)

4.13 Software Tools

Regarding research data, software tools are programs or utilities for developing applications and analyzing/processing or searching for data. Additionally, software tools are used to generate data from computational and experimental methods, throughout the publication process. An exhaustive list of tools would be ever-changing; more important than a list of tools used in every discipline is the understanding that the tools used during all lifecycle stages can influence other stages.

Table 19 lists the topics and subtopics that are most relevant to the overarching theme of software tools.

Table 19. Software tools (overarching theme)

4.14 Training, Education, and Workforce Development

Training, education, and workforce development are critical for ensuring that any given organization or individual involved in the research data management process has the necessary skills for RDM. Investment into workforce development is especially important in an area where best practices are still developing. On-the-job training not only helps to promote the standardization that is important in RDM but can also promote equity by ensuring that everyone has access to the most innovative practices.

Table 20 lists the topics and subtopics that are most relevant to the overarching theme of training, education, and workforce development.

Table 20. Training, education, and workforce development (overarching theme)

5 Profiles

Profiles specify those topics and subtopics in the RDaF lifecycle stages that are most relevant for a particular job role or research data management (RDM) function in an organization. The framework contains a comprehensive list of the tasks and issues that may arise with respect to research data activities and RDM. Most organizations or individuals will not find every subtopic to be relevant. As described below, NIST is developing a tool that allows individuals and organizations to customize a profile (i.e., select relevant subtopics from the full list of subtopics) for their specific needs or responsibilities.

The RDaF team generated sample profiles for eight common RDM job roles or functions. These profiles described below are intended to serve as samples and guides. Users may either modify a sample profile as a starting point for their own profile or build an entirely new profile by selecting relevant subtopics. The subtopics relevant to the eight sample profiles are presented in Table 21 . A straightforward tool to generate a customized profile—by modifying one of the sample profiles or by creating an entirely new profile—is described in Appendix D . The tool is an editable Excel file that contains all the information in Table 21 and a blank template of all the subtopics. Profiles may also be used to conduct self-assessments of RDM and identify tasks and issues that may need attention. Results of such self-assessments can subsequently be communicated within an organization or between organizations.

AI expert – This profile addresses the growing and evolving field of artificial intelligence. Experts in AI and machine learning often deal with large and incomplete datasets and may not be the originators of the data, making it difficult, e.g., to assess data and metadata quality.

Budget/cost expert – This profile is relevant to those individuals whose job responsibilities encompass budgetary and financial issues, such as securing funding, distributing funds and tracking spending within an organization. Budgetary issues underlie nearly every subtopic; this profile focuses on those subtopics that drive RDM costs.

Curator – This profile is pertinent to individuals who curate data in general, such as data librarians, and to individuals who curate data only for a specific research project. Curators collect, organize, clean, annotate, and transform data, which are critical tasks for data preservation, use, and reuse.

Data/IT leader – This profile is relevant to those individuals who establish priorities for RDM at an organizational or disciplinary level and who engage in strategic planning and establishing RDM infrastructure requirements.

Provider of data tools – This profile is germane to those individuals who create and provide tools that enable data to be collected, analyzed, stored, and shared such as hardware providers and programmers.

Publisher – This profile is pertinent to those individuals who publish articles in scientific journals and datasets in various dissemination modes These individuals and their organizations are concerned with data access, storage, preservation, and evaluation of data quality in publishing decisions.

Research organization leader – This profile is relevant to those individuals who establish policies, procedures, and processes for managing research data across an organization.

Researcher – This profile is germane to those individuals who conduct scholarly studies in all disciplines, including the social sciences and humanities, to produce new data used to, e.g., increase knowledge, validate hypotheses, and facilitate decision-making.

Table 21. Sample profiles

6 Conclusions and Ongoing Work

Version 2.0 of the NIST RDaF has been developed through extensive stakeholder engagement via a total of 17 workshops. Carefully crafted methodologies were used in the development process, which took place over nearly two years. The RDaF is based on a lifecycle model with six stages, each having a comprehensive list of defined topics and subtopics, as well as informative references for most of the subtopics. Version 2.0 contains full descriptions of 14 overarching themes and eight sample profiles detailing the relevant subtopics for eight common job roles/functions in research data management (RDM) and in conduct of research data projects. V2.0 also contains a list of many research data management organizations, with a link to the homepage for each organization. In addition to these features and resources, a tool has been produced that enables the creation of customized profiles. Finally, a web application has been developed and released that presents an interface to all content in this RDaF V2.0 document in an interactive environment and provides new functionality such as linkages of subtopics to corresponding informative references. The link to this web application is available on the RDaF homepage . The paragraphs below describe ongoing work in various areas.

The RDaF V2.0 can be tailored and customized to fit the needs of a variety of data management professionals and organizations. The content of the RDaF is already being implemented and used in various ways. Organizations have used the topics and subtopics in V1.0 to create “scorecards” of subtopics that indicate the current state of their RDM and are using V2.0 as a guide to create implementation plans for improving RDM and for creating profiles. The RDaF could potentially be used as a basis for a data management education curriculum. NIST welcomes and encourages additional creative uses of the RDaF by the community.

The research data ecosystem is evolving rapidly and NIST intends to release updates of the RDaF on a regular basis (subject to availability of resources). Additionally, NIST will assist the research data community, including organizations and individuals engaged in or interested in using the framework, to assess and improve their RDM. NIST will also seek partnerships with organizations having similar aspirations, such as the Australian Research Data Commons, who recently released their “Research Data Management Framework for Institutions”[ 262 ] and the Research Data Alliance’s new working group, the “RDA-OfR Mapping the Landscape of Digital Research Tools [ 266 ].” Finally, NIST is following the development of frameworks in other areas, such as the Sendai Framework for Disaster Risk Reduction [ 267 ]. NIST encourages organizations and individuals seeking assistance in using the RDaF or considering the development of value-added tools based on the RDaF to contact the team at [email protected] .

Given the complexity of the framework, the RDaF team is working on various tools to improve accessibility and applicability of the framework. The RDaF V2.0 interactive web application described in section 2.3 has an intuitive design such that users can easily navigate all components in the V2.0 document and view relationships among these components. New features of this web application such as graphical navigation, a user feedback form, and a guided profile-maker are under development.

Interactive, web-based knowledge graphs are being developed to visually demonstrate the interconnected nature of the many subjects and tasks in RDM [ 268 ]. The knowledge graphs will allow exploration of the relationships between, e.g., topics, subtopics, and job functions (profiles) within the research data ecosystem. Such interactive knowledge graphs enable individuals and organizations to approach RDM from a variety of perspectives and starting points. A user will be able to select any component of the framework, determine the other components to which the starting component is linked, and navigate through the diagram in an intuitive manner. For example, a researcher interested in metadata may start at one subtopic, then move to the overarching themes related to that subtopic. Next, that individual may review the sample researcher profile to determine other subtopics associated with metadata. Parsing through these subtopics, the researcher may encounter, for example, the data privacy subtopic, for which more knowledge is desired. To obtain this knowledge, the researcher then navigates to the informative references for that subtopic.

Due to the complex nature of RDM, the RDaF was designed to be comprehensive and broadly applicable. As a multifaceted tool, it can be used to address various aspects of RDM for organizations and individuals, e.g., assessment of the state of RDM using the RDaF lifecycle stages/topics/subtopics, development of strategies to improve RDM infrastructure, policies, and practices, and identification of RDM tasks and responsibilities for specific job roles or functions. Organizations and individuals seeking to use the RDaF for these and other purposes may need assistance. To this end, NIST intends to develop and publish a best practice guide for various use scenarios in collaboration with different stakeholder groups. Such a guide will focus on use of the RDaF for general topics, such as: assessment of existing RDM policies and practices; determination of goals for RDM; creation of step-by-step plans for reaching RDM goals; generation of curricula for continuing education and other training materials; and creation of job descriptions with individualized workplans.

The various workshops held to further develop the RDaF resulted in many transcripts and notes. The methodology section 2 described a manual, human-driven method of incorporating that feedback to generate V2.0. As a supplement and an experimental exercise, the RDaF team is also exploring natural language processing as a method to extract insight and draw conclusions via machine learning. These findings will be compared with the results of the manual process and may be incorporated in future versions of the RDaF.

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[15]  NOAA Administrative Order 212-15 ( National Oceanic and Atmospheric Administration ), 212–15 , p 4 . Available at https://www.noaa.gov/sites/default/files/legacy/document/2020/Mar/212-15.pdf

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Appendix A : Informative References

Research data occupy a complex and vast space with formidable management challenges. While the RDaF seeks to offer a comprehensive view of research data management, organizations and individuals may identify additional topics, subtopics, and profiles germane to their specific circumstances. In addition to definitions for each topic and subtopic, the RDaF contains more than 800 informative references. Some informative references provide background information that enable a more in-depth understanding of a subtopic. Other informative references, such as guidelines, standards, and policies, aid a user in addressing a specific subtopic. The interactive web application described in section 2.3 will enable linkages of informative references to corresponding subtopics.

The entire bibliography of informative references is available at: https://doi.org/10.6028/NIST.SP.1500-18r1sup1

Appendix B : Descriptions of Key Organizations

This Appendix provides a list of many key organizations, each of which is accompanied by a short definition or description to provide some context of their role in research data management.

Academy of Science of South Africa - Officially recognized national science academy that aims to provide evidence-based scientific advice on issues of public interest to government and other stakeholders.

Accelerating Public Access to Research Data (APARD) - A collaboration between the Association of American Universities (AAU) and the Association of Public and Land-grant Universities (APLU) to improve public access to data resulting from federally funded research. 

Alfred P. Sloan Foundation - This foundation makes grants primarily to support original research and education related to science, technology, engineering, mathematics, and economics.

American Geophysical Union (AGU) - An association of more than half a million advocates and professionals in Earth and space sciences.

American Library Association (ALA) - The oldest and largest library association in the world which aims to provide leadership for the development, promotion, and improvement of library and information services and the profession of librarianship to enhance learning and ensure access to information.

Association of American Medical Colleges - A not-for-profit association dedicated to transforming health through medical education, health care, medical research, and community collaborations. 

Association of American Universities (AAU) - AAU’s 65 research universities transform lives through education, research, and innovation.

Association of Public and Land-grant Universities (APLU) - A membership organization of university leaders collectively working to advance the mission of public research universities. The association’s membership consists of more than 250 public research universities, land-grant institutions, state university systems, and affiliated organizations spanning all 50 states, the District of Columbia, four U.S. territories, Canada, and Mexico.

Association of Research Libraries (ARL) - A nonprofit membership organization of research libraries and archives in major public and private universities, federal government agencies, and large public institutions in Canada and the US.

Australian Research Data Commons (ARDC) - A leading research data infrastructure facility in Australia that accelerates Australian research and innovation by driving excellence in the creation, analysis and retention of high-quality data assets.

Belmont Forum - A partnership of funding organizations, international science councils, and regional consortia committed to the advancement of transdisciplinary science.

Bill & Melinda Gates Foundation - A foundation that funds multi-million dollar initiatives to support global programs aimed at improving the quality of life by advances in science, technology, and data.

Biodiversity Global Information Facility - An international network and data infrastructure funded by the world's governments and aimed at providing anyone, anywhere, open access to data about all types of life on Earth.

BRAIN Initiative - A collaborative, public-private research initiative funded by NIH with the goal of supporting the development and application of innovative technologies that can create a dynamic understanding of brain function. 

California Digital Library - DMPTool - A free, open-source, online application that helps researchers create data management plans (DMPs).

CANAIRE - Formerly the Canadian Network for the Advancement of Research, Industry and Education, CANAIRE is the not-for-profit organization which operates the national backbone network of Canada's national research and education network (NREN).

Center for Open Science - A nonprofit organization that works to ensure that the process, content, and outcomes of research are openly accessible by default.

China Science and Technology Cloud - A national platform to provide scientists with efficient and integrated cloud solutions in the retrieval, access, use, transaction, delivery and other aspects of sharing scientific information and relevant services.

CKAN - An open-source data management system for powering data hubs and data portals. CKAN makes it easy to publish, share, and use data. It powers catalog.data.gov , open.canada.ca/data , and data.humdata.org , among many other sites.

Coalition for Publishing Data in the Earth and Space Sciences - A collaboration among research repositories, scholarly publishers, and other stakeholders focused on jointly developing, implementing, and promoting leading practices around the preservation and citation of data, software, and physical samples that lead toward credit and reuse in the Earth, space, and environmental sciences.

CENDI – CENDI is the Federal Scientific and Technical Managers Group. CENDI’s mission is to increase the impact of federally funded science and technology by improving the management and dissemination of U.S. federal scientific and technical information and data.

Committee on Data of the International Science Council (CODATA) - As the Committee on Data of the International Science Council (ISC), CODATA helps realize ISC’s vision of advancing science as a global public good. CODATA does this by promoting international collaboration to advance Open Science and to improve the availability and usability of data for all areas of research.

Commonwealth Scientific and Industrial Research Organisation (Australia) - An Australian Government agency that works with industry, government and the research community to turn science into solutions to address Australia's greatest challenges.

CoreTrustSeal - A nonprofit organization that promotes trustworthiness in repositories through certification.

Data Archiving and Networked Services (DANS, the Netherlands) - The Dutch national center of expertise and repository for research data.

DataCite - A leading global nonprofit organization that provides persistent identifiers (DOIs) for research data and other research outputs.

DataONE (Data Observation Network for Earth) - A community-driven program providing access to data across multiple member repositories, supporting enhanced search and discovery of Earth and environmental data.

Department of Energy (DOE) - The mission of the Department of Energy is to ensure America’s security and prosperity by addressing its energy, environmental, and nuclear challenges through transformative science and technology solutions.

Digital Research Alliance of Canada (DRAC) - DRAC serves Canadian researchers by integrating, championing, and funding the infrastructure and activities required for advanced research computing, research data management, and research software.

DKAN - A community-driven, free and open-source open data platform that gives organizations and individuals the ability to publish and consume structured information.

Dryad - A nonprofit membership organization that is committed to making data available for research and educational reuse now and into the future.

e-IRG – e-Infrastructure Reflection Group - A strategic body to facilitate integration in the areas of European e-infrastructures and connected services, within and between member states, at the European level and globally.

Earth Science Information Partners (ESIP) - Created by NASA, ESIP supports the networking and data dissemination needs of its members and the global Earth science data community by linking the functional sectors of observation, research, application, education and use of Earth science.

Economic Commission for Latin America and the Caribbean (ECLAC) - Headquartered in Santiago, Chile, ECLAC is one of the five regional commissions of the United Nations. It was founded with the purpose of contributing to the economic development of Latin America, coordinating actions directed towards this end, and reinforcing economic ties among countries and with other nations of the world.

European Data Infrastructure (EUDAT) - One of the largest infrastructures of integrated data services and resources supporting research in Europe.

European Open Science Cloud (EOSC) - An environment for hosting and processing research data to support EU science.

European Strategy Forum on Research Infrastructures (ESFRI) - A group that supports a coherent and strategy-led approach to policy making on research infrastructures in Europe, and facilitates multilateral initiatives leading to the better use and development of research infrastructures at the EU and international level.

FAIRsharing.org - A community-driven resource with users and collaborators across all disciplines who work together to enable the FAIR Principles by promoting the value and the use of standards, databases and policies.

Fedora Commons - A digital asset management content repository architecture upon which institutional repositories, digital archives, and digital library systems might be built.

Figshare - A repository where users can make all their research outputs available in a citable, shareable and discoverable manner. 

Flatiron Institute - An internal research division of the Simons Foundation, the institute is a community of scientists who are working to use modern computational tools to advance science, both through the analysis of large, rich datasets and through the simulations of physical processes.

Future of Research Communications and e-Scholarship (FORCE11) - A community of scholars, librarians, archivists, publishers and research funders that aims to help facilitate the change toward improved knowledge creation and sharing. 

Global Dataverse Community Consortium (GDCC) – An international organization for existing and new Dataverse community efforts that provides a collaborative venue for institutions to leverage economies of scale in support of Dataverse repositories around the world.

Global Open Findable, Accessible, Interoperable and Reusable (GO FAIR) - A community working towards implementations of the FAIR Guiding Principles. This collective effort has resulted in a three-point framework that formulates the essential steps towards the end goal, a global Internet of FAIR Data and Services.

Harvard Dataverse - A free data repository open to all researchers from any discipline, both inside and outside the Harvard community, where one can share, archive, cite, access, and explore research data.

Higher Education Leadership Initiative for Open Scholarship (HELIOS) - A cohort of colleges and universities committed to collective action to advance open scholarship within and across their campuses.

Integrated Global Greenhouse Gas Information System - An observation-based information system for determining trends and distributions of greenhouse gasses (GHGs) in the atmosphere and the ways in which they are consistent or not with efforts to reduce GHG emissions.

International Association of Scientific, Technical and Medical Publishers (STM) - The leading global trade association for academic and professional publishers.

International Bureau of Weights and Measures (BIPM) - An international organization established by the Metre Convention, through which Member States act together on matters related to measurement science and measurement standards.

International Council for Scientific and Technical Information (ICSTI) - A specialized intergovernmental organization established for ensuring the international exchange of scientific and technical information.

International Development Research Center (Canada) - A Canadian government project that funds research and innovation within and alongside developing regions to drive global change.

International Federation of Library Associations (IFLA) - An international organization that works to represent the interests of the librarian profession and improve services worldwide.

International Science Council (ISC) - Works at the global level to catalyze and convene scientific expertise, advice and influence on issues of major concern to both science and society.

Inter-university Consortium for Political and Social Research (ICPSR) – An organization that supports research by maintaining an archive of disciplinary research and offering training in the use of data.

Islandora - A foundation that maintains an extensible, modular, open-source digital repository ecosystem focused on collaborative authorship, management, display, and preservation of digital content at scale.

Kavli Foundation - A foundation that aims to advance science for the benefit of humanity by: stimulating basic research in the fields of astrophysics, nanoscience, neuroscience, and theoretical physics; strengthening the relationship between science and society; and honoring scientific discoveries.

Laura and John Arnold Foundation - A philanthropic organization dedicated to improving the lives of all Americans through evidence-based policy solutions that maximize opportunity and minimize injustice.

Materials Genome Initiative - A federal multi-agency initiative for discovering, manufacturing, and deploying advanced materials twice as fast and at a fraction of the cost compared to traditional methods. The initiative creates policy, resources, and infrastructure to support U.S. institutions in the adoption of methods for accelerating materials development.

National Academies of Sciences, Engineering, and Medicine (NASEM) - A nonprofit organization that provides independent, objective advice to inform policy with evidence, spark progress, and drive innovation. 

National Aeronautics and Space Administration (NASA) – An independent agency of the U.S. federal government responsible for the civil space program, aeronautics research, and space research.

National Information Standards Organization (NISO) - A non-profit standards organization that develops, maintains, and publishes technical standards related to publishing, bibliographic, and library applications.

National Institute of Standards and Technology (NIST) - A United States federal agency whose mission is to promote innovation and industrial competitiveness by advancing measurement science, standards, and technology in ways that enhance economic security and improve quality of life.

National Institutes of Health (NIH) - Part of the U.S. Department of Health and Human Services, NIH is the largest biomedical research agency in the world.

National Library of Medicine (NLM) - The world’s largest biomedical library, NLM maintains and makes available a vast print collection and produces electronic information resources on a wide range of topics.

National Science and Technology Council (NSTC) - A cabinet-level council of advisers to the President on science and technology that includes the Subcommittee on Open Science, formerly the Interagency Working Group on Open Science.

NOIRLab - NSF's NOIRLab, formerly named the National Optical-Infrared Astronomy Research Laboratory, is the United States national center for ground-based, nighttime optical astronomy.

ORCID (Open Researcher and Contributor ID) - A global, not-for-profit organization providing a unique, persistent identifier for individuals to use as they engage in research, scholarship, and innovation activities.

Organization for Economic Co-operation and Development (OECD) - An international organization that works with governments, policy makers, and citizens, on establishing evidence-based international standards and finding solutions to a range of social, economic, and environmental challenges.

Pub Med Central - A free digital repository run by the National Institutes of Health (NIH) that archives open-access full-text scholarly articles that have been published in biomedical and life sciences journals.

re3data (Registry of Research Data Repositories) - A global registry of research data repositories from all academic disciplines.

Research Data Alliance (RDA) - Launched as a community-driven initiative in 2013 by the European Commission, the United States Government's National Science Foundation and National Institute of Standards and Technology, and the Australian Government’s Department of Innovation, RDA has the goal of building the social and technical infrastructure to enable open sharing and reuse of data.

São Paulo Research Foundation (Brazil) - A public foundation located in São Paulo, Brazil, with the aim of providing grants, funds, and programs to support research, education, and innovation of private and public institutions and companies in the state of São Paulo.

Scholarly Publishing and Academic Resources Coalition (SPARC) - A non-profit advocacy organization that supports systems for research and education that are open by default and equitable by design.

Society for Scholarly Publishing (SSP) - A nonprofit organization formed to promote and advance communication among all sectors of the scholarly publication community through networking, information dissemination, and facilitation of new developments in the field.

Wellcome Trust - A global charitable organization that supports discovery research into life, health and wellbeing, with a focus on three worldwide health challenges: mental health, infectious disease and climate and health.

World Data System (WDS) - An affiliated body of the International Science Council (ISC) that aims to enhance the capabilities, impact and sustainability of member data repositories and data services.

Zenodo - An open repository developed under the European OpenAIRE program and operated by European Organization for Nuclear Research (CERN) that enables researchers to preserve and share their research output from any science, regardless of the size and format.

Appendix C : Acronyms and Initialisms

Appendix d : sample profiles (supplementary document).

Sample profiles for eight common research data management job roles are available as a supplementary document at https://doi.org/10.6028/NIST.SP.1500-18r1sup2 and on the RDaF homepage . This document contains the information in Section 5 and provides a blank template in a format amenable to the generation of customized profiles.

Appendix E : Change Log

In Fall 2023, the following updates were made to the published RDaF preliminary version 1.0 to produce this full version 2.0:

Expanded the topics and subtopics in the lifecycle stages which make up the “framework core,” renamed the “framework foundation”

Added 14 overarching themes, that are pervasive throughout the lifecycle stages

Added eight sample profiles, each of which identifies those topics and subtopics that are most relevant to a common job role or function in research data management

Added definitions for the topics and subtopics

Added informative references, such as guidelines, standards, and policies, for most of the subtopics

Developed and released an interactive web application RDaF V2.0 that replicates the content of the V2.0 document

Added a methodology section that describes the means by which the framework was updated

Added ongoing work

Home » Introduction to Research Frameworks

Introduction to Research Frameworks

What are research frameworks, research frameworks provide us with:, frameworks content, using research frameworks, contributing to the research frameworks.

• Using OASIS reporting to contribute ...

In 1996 the English Heritage (now Historic England) publication ‘ Frameworks for our Past ‘ highlighted the need for research frameworks for the historic environment as a tool for establishing long-term objectives. The DCMS document ‘ Historic Environment: a Force for our Future’ (2001) stated that English Heritage had been ‘ commissioned to frame a co-ordinated approach to research across the historic environment sector’ .

In Scotland, the Scottish Archaeological Research Framework (ScARF) was launched in 2012. Funded primarily by what is now Historic Environment Scotland and managed by the Society of Antiquaries of Scotland, this National Research Framework was one of the first to be available online as an updateable web-resource. It is now a key part of Scotland’s Archaeology Strategy.

Research Frameworks for many areas and specialisms have now been developed across the UK, with more in production. Some of the earlier Frameworks are already being reviewed and updated. In Scotland, as well as new thematic frameworks, the national framework is being updated through a series of regional frameworks.

The development of this Research Frameworks Network also addresses a number of the recommendations of the Pye Tait Review of Research Frameworks report (2014), including the need to ‘ Pursue the development of a dynamic and interactive web-based system for hosting a new generation of Research Frameworks’ .

As new Research Frameworks are developed, and older documents are reviewed, the plan is for them to be published here on the Network as a central location. We are also working on making older Research Frameworks (originally published as monographs) available through the Network.

Research Frameworks help us to identify what is important or significant archaeologically. They are normally organised by either;

• Geographical areas such as Regional, County, or World Heritage Site (e.g. the South West Regional Research Framework)
• Periods (eg the Mesolithic)
• Themes (eg Roman pottery)

They provide research questions and objectives to help co-ordinate and focus our research effort.

They are created by bringing together people across the sector to create a shared framework, key stakeholders include:

• Local authorities
• Contractors
• Voluntary groups

Each framework will be approached in a different way, but are usually guided by a Steering Group and begin with meetings of local stakeholders from across the historic environment spectrum. These events may take the form of a mixture of workshops and meetings and people come together to discuss and identify research priorities. Sections of the Frameworks are often written by specialists, but undergo peer review and consultation before the final resource assessment and research questions are agreed.

1. An up to date overview of current understanding – ie “what we currently know” .

They are usually created by synthesising information from lots of different sources, eg Historic Environment Records (HERs), reports from planning-led investigations, academic and society journals. This resource assessment provides an overview of a specific period, place or theme – eg The Bronze Age in the West Midlands.

2. A Research Agenda – identifying gaps in our knowledge and providing questions to fill these gaps .

An agreed set of research areas and questions that can be used to help co-ordinate research is developed. The questions help focus what the sector and communities want to know more about. Research agendas can help to coordinate academic and community research as well as provide a research focus for development-led projects.

3. Strategies to carry out this research .

These strategies provide the framework within which the research can be carried out by promoting and recommending potential ways forward and partnerships, which will help to answer the questions in the research agenda.

Regional and Thematic Frameworks will differ in content. They can cover archaeology, the built environment, landscapes, environmental information, and maritime heritage. However, generally they all follow a similar structure and contain the following:

• Definition of the region or theme – defining the area covered by the framework
• Summary or resource assessment of the time periods or themes
• Research Agenda and Questions – list of key research questions for each period or a synthesis of research themes spanning multiple periods
• Research Strategy – possible strategies for advancing understanding of the Agenda topics
• Overarching questions – region or specialism wide questions
• Environmental information (if relevant) – details of the palaeoenvironmental remains
• Case Studies to highlight particular research or sites
• Resources/bibliography – these vary in detail and scope across the network, but often contain lists of publications used in the production of the framework, online resources and other relevant information.

A table of existing research Frameworks can be found  here . We are working to make more research frameworks available on this network.

Research Frameworks play an important role in providing an overview of current understanding, coordinating research and informing decision making – particularly planning related. They have many different uses:

1. Local authority staff:

• As a reference to provide context for assessing the significance of heritage assets and proposed sites.
• To provide a research focus for planning-led investigations.

2. Contractors:

• As a reference resource to help write desk-based assessments and environmental impact assessments.
• Referred to when writing Written Schemes of Investigation (WSIs) in response to project briefs.

3. Academics:

• To scope out research projects and provide direction for postgraduate research.
• To support applications for funding
• To assess the ‘impact’ of their research, eg in relation to Research Excellence Framework (REF) impact assessments.

4. Local Societies:

• To improve their knowledge and scope out research projects.
• To support applications for funding community led projects
• To establish research priorities linking into the regional and national picture.

Frameworks rely on continual research to keep up to date. Everyone is encouraged to add to the value of the Frameworks by contributing to these online documents via the commenting facility as new work is carried out relevant to the research questions.

To find out how to get involved please visit the How to use the Research Framework Site page to find out how to register and contribute to the historical and archaeological knowledge on these sites.

Using OASIS reporting to contribute to the Research Frameworks

When reporting your project via OASIS (the online system for reporting archaeological investigations and linking research outputs and archives), depending on the area in which your work took place, it is now possible to ensure that your work directly links to the relevant Research Framework.

Research Questions identified within your project can be linked via the OASIS system. A series of walk-through talks were presented in early 2023, the video clip (below) demonstrates the process with screenshots.

Please note, not all Frameworks are currently listed within OASIS, more will be added as they become available.

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4. Developing a Framework or Model of Change

This toolkit helps in developing a picture of the pathway from activities to intended outcomes.

• To convey the purpose and direction of your initiative or effort (i.e., the outcomes sought and how you will get there)
• To show how multiple factors interact to influence the problem or goal
• To identify actions and interventions more likely to lead to the desired result   How will your organization or effort use its framework or model of change?   Related resources : Developing a Logic Model or Theory of Change  
• Easy to communicate
• Uplifting/inspiring to those involved in the effort
• A reflection of the perspectives of the community it represents   What's your group's vision for the effort?  
• What the group is going to do (e.g., "...by connecting and supporting children and caring adults.")
• What is going to do it (e.g., "Promote caring relationships...")   What's your group's mission for the effort?   Related resources : Proclaiming Your Dream: Developing Vision and Mission Statements  
• Summarize all of the specific measurable results of your initiative or program that you anticipate. These should include behavioral changes and related community-level outcomes.
• Forward logic (But why?) - ask yourself why this problem exists. What brought it about? What maintains it?
• Reverse logic (But how?) - ask how this problem might be solved or goal accomplished?
• Identify what personal factors (e.g., knowledge, belief, skills) contribute to the problem or goal
• Identify the environmental factors (e.g., supports and services; access, barriers, and opportunities; consequences of efforts; policies and broader conditions) that contribute to the problem or goal.   Related resources : Creating Objectives Gathering and Using Community-Level Indicators Community-Level Indicators: Some Examples Analyzing Root Problems of Problems: The "But Why?" Technique Defining and Analyzing the Problem   
• The overall initiative - may include all strategies and relationships used to affect change and bring about improvement for the overall problem or goal (e.g., reduce violence; promote caring relationships)
• A particular initiative or program - may include only the components and elements of a specific aspect of the overall effort (e.g., education programs; policy change)
• A specific work plan for an action or model for cooperation among stakeholders or participating agencies   Which level will your model of change describe?   Related resources : Identifying Action Steps in Bringing About Community and System Change  
• Purpose or mission - what the group is going to do and why
• Context and conditions under which the problem or goal exists and which may affect the outcome (e.g., history of the effort, broad cultural and environmental factors, political situation, economic conditions)
• Inputs - resources and supports available, as well as constraints or barriers to meeting the initiative's objectives
• Activities or interventions - what the initiative or program does to bring about change and improvement (e.g., enhancing support, modifying access)
• Outputs - direct results or products of the group's activities (e.g., number of people trained or activities conducted)
• Effects - more broadly measured outcomes or results (may include immediate, intermediate, and longer-term effects)   Related resources : Generating and Choosing Solutions Understanding Risk and Protective Factors: Their Use in Selecting Potential Targets and Promising Strategies for Interventions Proclaiming Your Dream: Developing Vision and Mission Statements Understanding and Describing the Community Defining and Analyzing the Problem Identifying Community Assets and Resources Identifying Action Steps in Bringing About Community and System Change Gathering and Using Community-Level Indicators Community-Level Indicators: Some Examples  
• An expected time sequence (what occurs before what) to arrange the components and elements of the framework or model.
• Arrows or other methods to communicate directions of influence and sequences of events. Some arrows may point in both directions to show and interaction or mutual influence.   Related resources : Developing a Logic Model or Theory of Change  
• Select a case situation (real or hypothetical) in which you can obtain feedback about your logic model
• Check for the usefulness of the elements of the model (e.g., was it understandable?)
• Check for the completeness of the model (e.g., what was missing?)
• Revise and add to make it more complete.   After testing the usefulness of the model with a case situation, what revisions did you make?   Related resources : Developing a Logic Model or Theory of Change  
• Orienting those doing and supporting the work - use to explain how the elements of the initiative or program work together, where contributors fit in, and what they need to be able to make it work.
• Planning - use to clarify your initiative or program's strategies, identify targets and outcomes, prepare a grant proposal, identify necessary partnerships, and estimate timelines and needed resources for the effort.
• Implementation - use to determine what elements you have and don't have in your initiative or program, develop a management plan, and make mid-course adjustments.
• Communication and advocacy - use to justify to others why the initiative/program will work and to explain how investments will be used.
• Evaluation - use to document accomplishments, identify differences between the ideal program and the currently operating one, determine which indicators will be used to measure success and frame questions about attribution (of cause and effect) and contribution of the program/initiative to the mission.   How might you put your model of change to work within your organization or community now? In the future?   Related resources : Providing Staff Orientation Programs Providing Volunteer Orientation Programs Providing Support for Staff and Volunteers  
• Link the path of activities to intended effects or outcomes
• Plan expansion of activities to reach your goals
• Understand the boundaries of your program or initiative
• Adjust course to allow for unanticipated changes
• Develop a new framework for an extended effort or new initiative  

Research Framework

A framework is an essential idea that humans have been using to build something effectively. This structure is widespread in various fields. In web development, for example, web developers use a framework called Model-View-Controller(MVC) to develop a web application.  MVC framework  is one of the most common software design patterns that web developers use to build user-interfaces. This type of structure allows them to create a more organized and understandable set of codes, making it an essential tool in developing an object-oriented program using programming languages, such as Javascript. Aside from web development, you can use frameworks in executing research methodologies, such as quantitative and qualitative research .

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What is the Research Framework?

A research framework is a precise representation of the structure of a research project plan . Through this structure, you can determine the critical areas of the study. It also allows you to come up with relevant research questions and research objectives. To develop a research framework, you have to team up with the individuals within your organization or community. These people may include local authorities, contractors, voluntary groups, and other affecting individuals.

What are the Contributions that Research Framework Can Offer?

Developing a framework for your study is crucial to obtain the following benefits.

1. Timely Knowledge

Whether you are conducting marketing research or nursing research, you will need to gather the relevant information that surrounds your study for a better understanding of your research. You can collect this type of information by scanning related reports and writings from a public library, publications, and other sources.

2. Knowledge Gaps

After receiving the relevant information, you will be able to determine the holes of the data between the existing information and your current study. To close the gap, use this knowledge difference to come up with questions, which you will be focusing on for the rest of your project.

3. Research Strategy

If you can develop an action research framework, market research framework, or any other research framework, it will be easier for you to plan on how to carry out your project.

10+ Research Framework Examples

To give you a better understanding of research frameworks, we collated a list of samples that you can easily download in PDF formats.

1. Disaster Management Research Framework Example

Size: 227 KB

2. Research Framework Plan Example

Size: 270 KB

3. Research Framework Policy Example

4. Research Framework Methodology Example

Size: 308 KB

5. Feminist Research Framework Example

6. Basic Research Framework Example

7. research methodology and analysis framework example.

Size: 197 KB

8. Research Evaluation Framework Example

Size: 215 KB

9. Framework for Assessing Research Example

Size: 76 KB

10. Research Training Framework Example

Size: 159 KB

11. Research Strategic Framework Example

How to Apply Research Framework?

In applying the framework to research projects such as experimental investigations for the first time, following a guide can be essential to prevent your research from going astray. Read the following instructions to ensure that you are doing your research correctly.

1. Take Note of the Observation

When researching with a set framework, the first thing that you must do is to observe the research surroundings. There are many ways to do your observation. You can take note of the indicators that will reveal the hidden matters during your study. In the process, you may notice unusual activities that may need further examination. You can also uncover a connection between one or two matters, which the existing information didn’t cover.

2. Develop Research Questions

By following the previous step, you should be able to take note of remarkable observations. Through these remarks, you will formulate the research questions. In doing so, make sure that the items that you have come up with will interest you and your audience. Aside from that, it would help if you were the first individual who will answer the questions. However, you also have to ensure that these questions are answerable given the time and the resources that you have.

3. Determine the Study Objectives

Once you have gathered the research questions, you can easily create the objectives of your project. Develop answerable, predictive, and clear assertions.

4. Assign the Most Appropriate Design

By choosing a research method, you can determine how to gather the necessary data, which is crucial to come up with a conclusion of your research. Case study, open-label, parallel design, cross-sectional, and case-control are a few of the vast array of the research designs that you can choose from to apply in your project.

5. Describe the Data Collection Process

Explain all the procedures for gathering the necessary information for your study. This essay should cover the process involved in collecting and storing the data. Specify the individuals or organizations that can retrieve the data and the steps that you are going to take in ensuring the subject and the data confidentiality.

6. Analyze the Data

Once you have all the necessary information, analyze it using statistical methods to come up with the best solution, and conclusion for your research project. Lastly, present the results to the target audience.

Before conducting a research project, it is essential to learn the use of research frameworks. Just like software development frameworks, this type of tool will ensure that you are executing the research process of your project systematically. We created this article to ensure that you are not going to conduct your research project aimlessly.

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How to Document UX Research Effectively (+ Free Template)

• February 8, 2023

Learning how to document UX research is a fundamental skill for every user researcher. It’s all well and good doing the research, but if your documentation is difficult to understand or access, your efforts will quickly spiral into chaos.

Where and how you store your user research largely depends on what kind of user research you have undertaken. While there are dozens of different types, from usability testing to behavioral heat mapping, we’re going to focus on the all-important user interviews .

There are plenty of documentation tools you can use to keep track of your research, but it’s not just about the software, unfortunately. Documentation tools aren’t magical genies that can solve all of your problems with a simple click of “install”.

No, a documentation tool or UX repository is just the start. There are several things you should keep in mind when you want to effectively document UX research. Ten things, to be precise. 

@tldv.io Ian can make jokes about it. He was let go too. Goodluck to anyone dealing with this. It is frustrating, illogical, and difficult but you will get through it #layoff #tech ♬ original sound – tldv.io – AI Meeting Recorder

10 Ways to Effectively Document UX Research

1. always introduce the key components.

Regardless of where you’re storing your research, you always need to make it abundantly clear to the reader what the purpose of your research is. Make sure the purpose, methods, findings, and outcomes are obviously visible and easily digestible. A non-researcher should be able to glimpse at your UX research repository and immediately understand those 4 elements.

Also contained and easily accessible in your research doc should be information about what was tested or researched, and who the user group was.

You can use a whole bunch of different UX research methods to complete your goals, but the final result should be crystal clear immediately.

2. Don’t Rely on Handwritten Notes

If you’re handwriting notes in the 2020s, you may as well be using a quill and ink. Of course, there’s nothing better than putting pen to paper when writing something creative, but for jotting down important bites of information on the fly, technology is your friend.

If you want to make the most of your user interviews , you should use tl;dv, a free tool that lets you make notes easily during an online meeting . You can set timestamps so that you and your team can revisit moments with precision and ease. It’ll create a hyperlink so you can jump straight to the moment the user said something noteworthy. And the best part? You can copy and paste it to your research repository in a couple of seconds, and your entire team can access it just as easily.

This makes your job a helluva lot easier. Think about when you’re presenting your research findings to stakeholders and product managers. You want to convince these people that your research is thorough and your suggestions are beneficial. What better way than by showing the stakeholders the problem in the voice of the customer themselves?

Nobody wants to read through dozens of handwritten notes. And even if you type them up neatly, you’re still missing the nuances and emotions that come through with real visual and audial comments. Not to mention, memory is a fickle b*tch.

3. Be Wary of Automatic Note-Taking

You know when we said you should avoid hand-writing notes? Well you should be careful around AI-generated notes too. Sure, AI can be helpful. I mean, there are dozens of AI meeting assistants that are super powerful and can help in many different ways, but when it comes to note-taking, you don’t want to rely on an algorithm.

With the rise of ChatGPT and Google’s rival chatbot , Bard, it’s no wonder that everyone wants AI to do everything for them. But there are certain things that you can do better than AI can, especially when it comes to understanding the nuances of human language. Most bots still fail captchas, but it takes a special breed of human to do so.

With tl;dv, you will soon be able to generate AI summaries of your meetings so that you can get an overview of what was said. However, the option to swiftly and manually add notes will always be there. This gives you the best of both worlds, empowering you to get state-of-the-art AI summaries, while also highlighting and timestamping all the parts that you deem noteworthy too. It’s the quickest and most efficient way to maximize your note-taking.

If you’re caught up in the AI hype, you might want to look at some free GPT meeting softwares . Just don’t rely on them to do everything as well as you can. AI isn’t that clever yet. 

Or is it…?

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4. Document User Insights as Accurately as Possible

The best way to document user insights is in their own voice. By using a meeting recorder , you can rewatch your user interviews as many times as you wish. This can help you plunge the depths of your user interviews, whilst also providing an excellent way to accurately and effectively document them.

It’s difficult to remember all the finer details of what your users say, especially if you’re trying to handwrite notes as you listen. tl;dv is a great example of a tool that lets you engage in the conversation more, knowing that you’ll have the recording to rewatch and analyze in more detail.

5. Don’t Forget the Question

Don’t just document the user’s answers. Also make sure you document the question. How was it phrased? Were you framing the question in a way to elicit a specific response? We do this all the time, intentionally or not. If you have a bias that you’re unaware of, it can completely disrupt the user research process.

A good way to ensure that bias is kept to a minimum is to run the Mom Test .

@tldv.io If my mom would like it, then it passes. Right? // @been.ian skipped one of our meetings to finish this #product #tech #momtest ♬ original sound - tldv.io - AI Meeting Recorder

The Mom Test is a simple test you can run to pluck good advice from anyone, including your mother! It helps you reframe questions to get to the heart of what the user wants , which, at the end of the day, is what user research is all about.

It should be a priority if you want to master customer-centric product development .

6. Make Use of a UX Repository

Briefly mentioned earlier, a UX research repository is a platform where you will collect, store, and maintain all your user research. From the very beginnings to the analysis and outcomes.

There are a wide range of UX research repository tools that you can use. Which tool you choose will depend on whether you want the repository to be easily accessible by your entire team, including the important decision makers, or if your research is so specific and niche that you will only have a small team of dedicated researchers using it.

We advise you to think about the sharing of your research findings, just as much as anything else, if not more so. Without being able to adequately portray your findings to those that make the final decisions, your research is effectively useless, no matter how beautiful it looks in your specialized repository.

Tools like Notion and Miro are often widely used by businesses. These low-hanging fruit can easily be converted into a research repository if you’re feeling creative. This saves money on expensive tools, makes it a lot easier for your entire team to access it, and provides a base for deeper analysis and research transparency amongst your team.

7. Ensure Insights are Accessible and Shareable

Reiterated for importance: if stakeholders and crucial decision makers can’t access or understand your research, it is useless.

Now, as this post is all about how to document UX research effectively, we have to make sure that it is easily accessible by the company stakeholders, and more shareable than a viral TikTok.

@tldv.io We love constructive criticsm #productmanager #product #tech #productmanagement #corporatehumor #startup ♬ original sound - tldv.io - AI Meeting Recorder

To do this, you might need to use a remote UX research tool like tl;dv to easily create clips, highlights and short snippets that you can copy and paste to your colleagues so they can get the raw and authentic version of the user’s wants and needs.

Available for both Google Meet and Zoom , tl;dv offers unlimited free recordings with live transcripts that can be edited to create shareable reels .

8. Track Patterns and Progressions

One of the most important things to do during the analysis phase is to keep track of patterns that crop up over and over and over again. When your users are all telling you the same thing, it’s time to start listening.

The best thing to do is develop a technique to keep track of things that users are repeating. One way is to use tl;dv’s powerful search function . By searching for a keyword, you can see in which meeting transcripts it has been used and what was said about it. In just a few moments, you can double check to make sure that you’ve covered all the times a specific topic was talked about.

There are plenty of ways you can measure the user experience , but keeping track of patterns and progressions is a surefire way to boost your efficiency.

9. Pay Attention to What Users Do, Not What They Say

User interviews are great, but they’re not the be all and end all. In fact, behavioral heat mapping tools like Hotjar provide fascinating insights into what your users are actually doing when they interact with your site or app. It shows what they’re drawn to, where they click, and, basically, what they do. With this information, you can spot weaknesses in your design and get access to the user’s actions rather than their opinions.

It’s worth noting that people are often unaware of what they like and dislike, or what appeals to them and what doesn’t. Sometimes it’s subtle. With heat mapping tools, you can get the answers from them via their actions rather than their words.

In addition to behavioral heat mapping, you can also use usability testing platforms like Maze . This allows you to create and test a prototype with ease. Different businesses will have different requirements: you can check out some other usability testing tools here.

When combined with the research gathered from user interviews, these other research methods provide a fantastic insight into what your customers actually want.

10. Tackle Your Biases

Mentioned earlier, all user researchers have biases . They’re inescapable. However, that doesn’t mean you can’t become aware of your biases and work to reduce them as much as possible.

It’s important to acknowledge any and all research biases in the documentation as early as possible. You can use this time to list any other shortcomings in the research too.

With your biases and other pitfalls laid bare before you, you can approach the research and analysis from a fresh mindset. It’s great to keep an eye on them throughout so that you can check you’re not slipping back into old habits. In a way, it’s like doing reality checks throughout the day so that you can eventually catch yourself in a dream and gain awareness. You want to catch yourself if you’re ever approaching things from a biased mindset.

Templates Galore!

If you were here because you were promised a free UX research document template, we haven’t forgotten about you!

There are tons of templates that you can use to help you document UX research. Here are a few free ones to get you started:

• Bit.ai’s Free Template
• Polaris’ UX Nuggets
• Zapier’s New Feature Research Base
• Lean Design Research for Emotional Data

If you’re looking for more free UX research documentation templates, you can get a big fat list of them here . 105 to be exact.

Document Your Research Effectively

We hope that our ten points and free template options helped you answer the question of how to document UX research in an effective way. Remember to start early; nobody wants to try and organize a manic mess after the research has already started coming in.

Put effort into the planning and structure of your research documentation and your future self will thank you. Also, don’t forget to utilize the power of video in bringing user voices closer to your organization. A free user interview recorder like tl;dv helps you share and embed bite-size video insights so that your UX documentation is as accurate as possible. 

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• Open access
• Published: 04 April 2024

Understanding health system resilience in responding to COVID-19 pandemic: experiences and lessons from an evolving context of federalization in Nepal

• Shophika Regmi 1 ,
• Maria Paola Bertone 2 ,
• Prabita Shrestha 3 ,
• Suprich Sapkota 1 ,
• Abriti Arjyal 1 ,
• Tim Martineau 4 ,
• Joanna Raven 4 ,
• Sophie Witter 2 &
• Sushil Baral 1  

BMC Health Services Research volume  24 , Article number:  428 ( 2024 ) Cite this article

Metrics details

Introduction

The COVID-19 pandemic has tested the resilience capacities of health systems worldwide and highlighted the need to understand the concept, pathways, and elements of resilience in different country contexts. In this study, we assessed the health system response to COVID-19 in Nepal and examined the processes of policy formulation, communication, and implementation at the three tiers of government, including the dynamic interactions between tiers. Nepal was experiencing the early stages of federalization reform when COVID-19 pandemic hit the country, and clarity in roles and capacity to implement functions were the prevailing challenges, especially among the subnational governments.

We adopted a cross-sectional exploratory design, using mixed methods. We conducted a desk-based review of all policy documents introduced in response to COVID-19 from January to December 2020, and collected qualitative data through 22 key informant interviews at three tiers of government, during January-March 2021. Two municipalities were purposively selected for data collection in Lumbini province. Our analysis is based on a resilience framework that has been developed by our research project, ReBUILD for Resilience, which helps to understand pathways to health system resilience through absorption, adaptation and transformation.

In the newly established federal structure, the existing emergency response structure and plans were utilized, which were yet to be tested in the decentralized system. The federal government effectively led the policy formulation process, but with minimal engagement of sub-national governments. Local governments could not demonstrate resilience capacities due to the novelty of the federal system and their consequent lack of experience, confusion on roles, insufficient management capacity and governance structures at local level, which was further aggravated by the limited availability of human, technical and financial resources.

Conclusions

The study findings emphasize the importance of strong and flexible governance structures and strengthened capacity of subnational governments to effectively manage pandemics. The study elaborates on the key areas and pathways that contribute to the resilience capacities of health systems from the experience of Nepal. We draw out lessons that can be applied to other fragile and shock-prone settings.

Peer Review reports

Resilience has emerged as a key concept for health systems in the last decade. Catastrophic events such as economic crises, infectious disease outbreaks, civil unrest, and other shocks have highlighted the need to understand the concept of resilience in relation to health systems and reflect on how to effectively build resilient health system to cope with shocks and crises [ 1 ]. The relevance of resilience in relation to health systems was further highlighted globally during the 2020–2021 pandemic of coronavirus disease (COVID-19). The concept and definition of resilience is evolving and gaining greater interest and attention. Blanchet et al. defined resilience as the capacity of a health system to prepare and respond to shocks and to adapt and transform to cope with those, while ensuring delivery of quality and essential health services [ 2 , 3 ]. Recent literature has highlighted that resilience does not always imply a strong health system with the view that health systems can be strong in stable conditions but may prove vulnerable to shocks or, a health system can be resilient during emergencies but not performing well in routine conditions [ 4 ]. COVID-19 has tested the resilience capacities of health systems worldwide to respond to the pandemic while maintaining routine health functions. While it is agreed that the ability of the health system to deal with such shocks and remain resilient depends on the governance and political economy of the local context [ 5 ], more research is needed to explore the elements and pathways (which we call “resilience capacities”) that can support heath system resilience during shocks and crises, and generalise lessons learned from case studies. This study explores the health system response to COVID-19 in the new federal context of Nepal and examines the processes of policy formulation, policy communication and implementation at the three tiers of government, including the dynamic interactions between these tiers. It also reflects on how these processes might have affected the response and the longer-term resilience capacities of the health system as well as the role played by resilience capacities of the health system in allowing effective or suboptimal absorption, adaptation, and transformation in the face of a shock.

To guide our understanding of health system resilience and identify core capacities that underlie resilience which may have been activated and/or supported during the COVID-19 response, we adopted the resilience framework and hypotheses developed by ReBUILD for Resilience in 2020 [ 6 ] (Fig.  1 ), based on earlier literature on the topic, including that undertaken by team members (e.g. Jamal et al. in the analysis of health system resilience in Syria) [ 7 ]. Under this framework, the broader capacities that the health system must have in place in order to deploy resilience approaches are depicted as enabling the core (absorption, adaptation and transformation) approaches. Resilience capacities refer both to specific elements, such as the presence of a culture of learning within the health system, as well as the pathways, strategies and interlinkages between capacities that reinforce each other (for example, the framework hypothesises that effectiveness of learning processes is related to inclusivity and open governance and decision-making) [ 6 ].

Resilience framework

Study setting

In Nepal, a new constitution was promulgated in September 2015, replacing the unitary government and declaring the country as a federal democratic republic comprising of three autonomous governance levels: the federal, the province (7 provinces) and the local level (with 753 municipalities). The introduction of this federalised structure was still at an early stage when COVID-19 pandemic hit the country. Municipalities in the new structure are responsible for the delivery of basic health services in addition to other functions related to formulation of local plans and implementation of health programmes. The functions and responsibilities across the three tiers of governments were defined, however clarity in terms of implementation of these functions and the existence of capacity gaps especially at municipality level were already known before the pandemic [ 8 , 9 ]. The chronic stress due to the decentralization processes with the added acute crisis due to the COVID-19 pandemic posed a major challenge for the local governments that had to prepare and respond to the pandemic, while at the same time keeping basic healthcare delivery intact, which they were only starting to manage and oversee directly.

Nepal was heavily affected by the COVID-19 pandemic during the first wave in 2020. Figure  2 presents the distribution of COVID-19 cases from January– December 2020 by province in Nepal, including Bagmati province where the capital city Kathmandu lies, which reported the highest number of cases [ 10 ]. However, it should be noted that data also reflect changing government guidelines on testing (for example, from June 2020 no tests were required for asymptomatic cases in quarantine). The government’s response to COVID-19 started in January 2020, and a first lockdown was imposed between March and July 2020, though it was already partially lifted in late May. A much higher wave of cases occurred from August onwards, due to the influx of Nepali migrant workers returning from India and the time of the festivals of Dashain, Tihar and Chhath in October, during which the government had relaxed restriction on transportation.

Distribution of COVID-19 cases by province and total deaths from January to December 2020

This study adopted a cross-sectional design using a mix of policy review and primary data from key informant interviews (KIIs). With the aim of understanding the COVID-19 policy response mechanisms adopted by the federal, provincial and local governments to implement basic health services along with preparedness and response to COVID-19, we selected the study sites from all three tiers of the government - Kathmandu (federal level), Lumbini Province (provincial level) and two municipalities of Kapilvastu district (municipal/local level) which was one of the districts with highest COVID-19 cases, bordering with India.

We first conducted a desk-based review of health sector policies, guidelines, and directives on COVID-19 preparedness and response formulated at national and subnational levels from January to December 2020. Document search was carried out mostly online with frequent and regular visits to governmental websites that provide all the COVID-19 policies, guidelines, directives and other relevant documents (Table  1 ). Out of a total of 90 policies and other guiding documents and directions published by the government over the year 2020 regarding COVID-19 preparedness and response, 76 policies were identified as most relevant and data extracted from them.

Secondly, we carried out KIIs in January-March 2021, at federal and sub-national levels to complement and triangulate the information from the policy review, in order to better understand the process of policy formulation, communication and implementation at all levels. In total, 22 KIIs were conducted with participants from federal, provincial and local levels, purposively selected considering their roles in COVID-19 response (Table  2 ). The interviews took place in Nepali language and lasted for 60 to 90 min. Topic guide was developed in English and translated into Nepali prior to data collection and was further revised and adapted iteratively based on the field experiences (topic guide in Supplementary File 1 ). KIIs were audio-recorded after receiving consent from the key informants, and then transcribed and translated into English for analysis.

All data from the document review and KIIs were extracted to provide a descriptive overview and timeline of the policy formulation processes, as well as the policy communication and implementation. At a more analytical level, data analysis took a thematic framework analysis approach and was based on a list of themes and subthemes derived from components of the resilience framework [ 6 ], and emerging themes from the data, in line with study objectives. Data was coded using a qualitative software NVivo and was processed iteratively with regular discussion among research team members. Thorough triangulation of information from policy review and KIIs was also carried out, and data was then summarized and organized under defined themes and sub-themes.

Findings from the policy review are presented in terms of the trajectory of COVID-19 related policy documents over a one-year period. Moreover, data from policy review and KIIs are analysed and presented using a structure of the broader thematic order aligned with the components of resilience framework and supported by quotes extracted from the original transcripts.

Emergency planning and policy development

Covid-19 governance structure and key actors in the policy formulation process.

After the confirmation of first COVID-19 case on 23rd January 2020 in Nepal, the Government of Nepal started formulating various policies and directions in response to COVID-19 pandemic starting from March 2020. Figure  3 below provides an overview of the timing of main events and policies that took place or were published in the period between January and December 2020.

The policy formulation process followed an already existing governance structure with different committees and working groups at national and sub-national levels, and involved engagement of different tiers of government as well as across government agencies and sectors (shown in Fig.  4 ). After the first COVID-19 case was diagnosed in Nepal in January 2020, the Government of Nepal formed a High-Level Coordination Committee, led by the Prime Minister and the Minister of Defence. Soon after COVID-19 was declared a pandemic on March 11, 2020 by the WHO, [ 11 ] three different committees– the Direction Committee, the Facilitation Committee, and the COVID-19 Crisis Management Centre (CCMC) were formed for rapid and integrated response for the prevention and management of COVID-19. The Council of Ministers formed the CCMC primarily responsible for managing the responses in an integrated manner, through its representative units at province, district and local levels [ 12 ].

Timeframe of COVID-19 policies and guidelines. Note : Abbreviations used in the Fig.  3 - CICT (Case Investigation and Contact Tracing), IPC (Infection Prevention and Control), HRH (Human Resource for Health), HF (Health Facility), EMDT (Emergency Medical Deployment Team)

COVID-19 management and response structure

Likewise, the Incident Command System run under the MoHP, led by MoHP’s Secretary, was primarily responsible for developing and refining policies and guidelines for COVID-19 management, works in three different areas– coordination and monitoring, operation and information/data. Later in May, for conducting contract tracing effectively, the MoHP issued a directive for formation and mobilization of Case Investigation and Contract Tracing Teams (CICTT) in each local government [ 12 ]. Likewise, the MoFAGA issued a directive for the formation of the local level coordination committee and ward level coordination committee for mobilizing health workers and FCHVs, ensuring health message communication in accordance with MoHP guidelines, providing suggestions and establishing immediate referral systems, monitoring health desks at border entry points, ensuring self-quarantine and physical distancing, etc. [ 13 , 14 ]. However, in our synthesis, we found that community participation in, and the functionality of these coordination committees was a challenge which raises concerns about whether the planning and policy formulation process was inclusive and participatory.

Participation of subnational government in policy formulation (vertical collaboration)

With the federalization of the country, the province and local governments have power to make their own local policies and plans. At the same time, pandemic or any emergency management falls under the prime responsibility of the federal government [ 15 ]. Therefore, considering the emergency situation and the limited time available to respond to the pandemic, the federal government effectively led the overall policy development process with little or no consultation with province and local governments, which engaged mostly in implementation of policies and directions for COVID-19 management (for example, quarantine management). Although there were some exceptions (for example, the HEOC meetings, which included province level representatives), most respondents at provincial government level felt they were insufficiently involved in the policy formulation processes.

Province [government] was less involved in the policy formulation process at federal level. Some draft documents were shared [with province] to collect feedback but nobody has time to review those documents and hence, finalized [policies and guidelines] were sent at once, whereas some documents were developed and circulated without our concern. (EDP_ Province).

There was no inclusion of local level representatives such as mayors, deputy mayors, executive officers, health coordinators and chiefs of health offices in the formulation of COVID-19 related policies and documents at the province level, who were involved in routine health policies formulation process in the province in the non-COVID context.

Multi-sectoral collaboration and networks

Multi-sectoral collaboration was widely observed in federal and provincial levels during the policy formulation process. Participation from different ministries like Ministry of Foreign Affairs and General Administration, Ministry of Home Affairs, Ministry of Industry, Commerce and Supplies, Ministry of Communication and Information Technology, as well as medical associations, security forces (Nepal Army, Armed Police Force) was reported in policy formulation and response activities. Although there was a delay in decision from the government to involve the private sector in the COVID-19 response, from June 2020, the federal government engaged with the private health sector for testing and treatment through a reimbursement mechanism [ 16 ]. In addition, consultation with partners, such as the World Health Organization (WHO), international non-government organizations (NGOs) and technical experts were regularly held during policy formulation processes at federal level.

Likewise, province government also coordinated and collaborated with other departments and ministries and also with international NGOs and private sectors, WHO, United Nations Children’s Fund (UNICEF), United Nations Population Fund, Red Cross Society, representatives from medical colleges and Association of Private Health Institution of Nepal, Nepal Commission Drug Association and other local organizations for technical assistance while developing policies. Nevertheless, community level representation was missing in both federal and provincial policy formulation processes.

While formulating the policies, local problems and needs have to be addressed. The policies are developed at the national level, but they do not align with our local context. Our local level is not developed enough to implement the policies due to many difficulties such as lack of human resources, finance. (Mayor_Municipality2)

Strategic use of evidence

The federal government successfully used global evidence in policies and guidelines developed at federal level, despite the lack of a dedicated professional team and mechanisms for local evidence generation. For example, it considered WHO interim recommendations in different areas for COVID-19 management, and regularly adapted them to some extent while developing national policies and guidelines. Similarly, the province level considered federal policies and WHO technical guidelines. However, during the policy formulation at the federal and provincial levels, identification of local resource needs for example in terms of health staff, logistics, health infrastructure, etc. was found to be done on an ad-hoc basis using assumptions, rather than based on local information and monitoring of local environment and population needs and outcomes.

We developed a concept about how to treat if there are 5000 critical cases in Lumbini province. Consequently, we formulated a plan including how many HR and equipment will be required, etc. Thereafter, we made a contingency plan assuming how to treat if there are 5000 cases. We made an action plan accordingly to manage [COVID-19] for six months as we were unknown about how long will [COVID 19] last for. (Province official).

Applicability and relevance of national policies to local context

Local level respondents clearly felt the inapplicability and often the irrelevance of national level policies at local level as COVID-19 response and policies were not developed considering local context and lacked coordination with local levels. For instance, differences between urban and rural areas were evident in terms of infrastructure and human and financial capacity, but the same policy was applied to both settings.

I did not find the national policy to be appropriate to local context. Moreover, I felt that national COVID-19 policy was promoting the autocratic style of enforcing the activities. (Ward Chair_Municipality1)

This was reiterated by development partners in the province who stated that federal policies were vague and too general. For instance, national guidelines for CICT mentioned mobilization of public health professionals, nurse/paramedics and lab technicians/lab assistants for CICT which is not possible at province and local levels because such human resources are not easily available. Local administrations therefore had to adapt guidelines and make them specific to their context. This was the case, for example, of guidelines for isolation centres and operating procedures regarding CICT.

Gender and equity in policies and response measures

Our policy review revealed that gender and equity considerations were not generally reflected in COVID-19 policies and guidelines. A federal level informant confirmed that often gender and equity parameters in policies and guidelines were overlooked as the focus was on finding ways to respond to the emergency situation, rather than considering gender and equity. Similarly, gaps were observed in consideration of gender and equity in provincial level policies and guidelines, especially at the beginning. However, a series of gender related issues started emerging during implementation, for example in relation to quarantine management (common bathing area for males and females, cases of rape etc. occurring in different parts of the country that appeared quite frequently in media sources). This forced a revision of policies at the province level, as a reactive management to inform practices accordingly to the context e.g., separate living and essential health services for children, elderly, pregnant and lactating mothers, people with disability and chronic illnesses in quarantine centres [ 17 ], separate room, toilet and bathroom for males and females along with sanitary pads for females, and provision of female security personnel at female isolation centres [ 18 ].

There was no thought about gender [equality and equity] since it was handled based on case. But there were some issues during quarantine management like increased number of people were kept together, both male and females were kept in the same block, bathing area was also same for both male and females in the quarantine centre. However, gender issue was not addressed in policies. [During quarantine management], we witnessed that problem, so we addressed it verbally though it was not mentioned in the policy. Later, the issue had been addressed by arranging separate rooms for male and female. (Province official)

Policy communication and information dissemination approaches

The federal government used several channels for policy communication and dissemination. These included for example: daily national press briefings, situation reports, and notices on official websites, social media platforms (Facebook, twitter, Viber), newspapers, local radios, and televisions. Although different mediums were used, the overall communication process was found to be a one-way, top-down approach. Targeted communication to respective audiences was absent as communication to different levels of government, health workers and public was done in the same manner. Interaction for communicating policies between the three tiers of government was largely missing. As a result, provincial and local governments remained less aware of some policies and updates, and thus had to rely on their own access to information.

There needs to be targeted audience and focused communication. We just did general communication. After making policies, we should have called ministers of all seven provinces, directors and briefed them about the policy. We should have explained the reason for not doing PCR testing after 14 days and explained them about the evidence on which guidelines are based. We did not communicate about it. (MoHP_Federal). There was a communication gap. Federal level formulated the guidelines but never informed us about that. We have to search in Facebook, we knew [about the guidelines] through other mediums. We only operated and managed by exploring [the guidelines] through other mediums and self-search. (Province official)

In contrast, the provincial government was to some extent more proactively engaging in communicating and updating local governments about new policies, via direct channels such as phone call, email or physical meetings, although that was sluggish in the initial phase. Furthermore, ad-hoc meetings were also conducted between province and local levels for coordination. Later, the provincial government developed a software application that gathered relevant COVID-19 information, national policies and official documents to inform and update local governments and health workers. At the municipal level, municipalities were found to communicate information regarding COVID-19 policies and guidelines to ward representatives and health workers in a simple and comprehensive way, either in person or via phone. They also discussed ways to implement policies and guidelines.

The federal government did not communicate policies formally. The province government sent model of different format through email. It has also mobilized a responsible person [for communication]. Policies and guidelines keep on changing but the responsible person does the coordination. They call formally and ask us to enter the situation here in that format and we send the data through email. We also take the direction from there. That is how the information is circulated. (Health Coordinator_Municipality1).

Health workers on the other hand were not officially informed about policies from the municipality or other levels. They were informed verbally by municipality officials but not in any written form or through sharing of documents which they felt to be ineffective and inhibited their understanding. They also relied on their own access to information.

Regarding the urgent matter like providing vitamin-A during COVID, we got that information through Facebook only… That information should have been forwarded to us, but it was not done. My friends shared it on Facebook and I saw it there. After that, I printed that and shared with the health workers. (Male Health Worker_ Municipality2)

Policy implementation

Decision space, capacity, and accountability in policy implementation at subnational level.

Decision space includes authority and choices to make decisions at the local level, accompanied by strengthened capacities and accountability mechanism for better decision making [ 19 ]. Federalism has meant that increased power is assigned to subnational governments, and local governments have de jure decision spaces for the operational aspect of disease management such as planning, budgeting, resource allocation for COVID-19 management. In practice, provincial and local governments were found to be exercising this power mostly at the operational level and in terms of policy implementation (rather than in terms of policy formulation), by allocating budget for COVID-19 management, establishing isolation and quarantine centres, procuring equipment and materials (personal protective equipment, masks, sanitizers, soap) and hiring health workers, among other activities. Local governments did not always follow federal guidelines. For example, the guideline for testing was amended by federal government which required no testing after completion of 14 days of isolation. This guideline was not followed by the local governments, and they continued testing for all COVID-19 infected people completing a quarantine period. Moreover, the guidance of the federal government to not allow the migrant population to enter the country through border entry points because of increased risks of transmission of COVID-19 infection was again not followed by local governments. Instead, both local governments included in our analysis permitted entry for migrants who were stranded on the India-Nepal border and placed them in quarantine centres.

However, issues were raised because of the lack of budget available to local governments due to delay in allocation from federal level or the absence of emergency budgets to cover for such a pandemic situation. This highlighted the fact that a large amount of budget remains with federal government despite the decentralization in the country. In addition, respondents noted that duplication of budget happened in some places while budget was insufficient in others. This created confusion and difficulties in policy implementation.

There was a controversy. Sometimes, federal government directly provided budget for quarantine management to municipal level, whereas sometimes, budget was sent to province and province sent budget to municipal level for quarantine management. Federal, provincial and local government separated budget for quarantine and isolation. It was not clear who should allocate what amount of budget and their exact roles, particularly in the context of COVID 19 response. (EDP_ Province).

As a result, the overall implementation process was not smooth and, in some instances, resulted in suboptimal implementation. One clear example concerns the management of quarantine and isolation centres where the local governments faced a hard time to establish and manage them in the community. Most quarantine centres were established at schools, community halls, hotels and other spaces, which was not sufficient to quarantine thousands of people entering Nepal from India and other countries. Due to the tremendous load of people in quarantine centres, municipalities were unable to properly manage the quarantine centres and people faced many difficulties in terms of getting quality food, space, privacy and safety, which also affected the safety of the health workforce from the COVID-19 infection.

Policy compliance and mechanism for monitoring

Despite the availability of decision space concerning operational mechanisms, a number of respondents at municipal level noted the lack of clarity on the roles and responsibilities of local governments with regard to federal policies, which hindered rapid and effective implementation. This was also confirmed by respondents from federal government. One example concerned the mobilisation of the budget and human resources needed for CICT, which affected the contact tracing and case investigation activities.

The CICT structure that was [supposed to be] formed all-round the nation was not activated adequately. There was uncertainty regarding who will offer the budget necessary for training, how the training will be conducted. Municipalities were not clear how to manage budget and from where to manage health personnel to form CICT team. (EDP_Federal).

Policy compliance was challenging due to the sudden changes over which local governments seemed to have no control. For example, respondents at local level recounted how they had tried to build up structures to implement a policy on mobilization of volunteers, only to see it later revised.

We received a national directive on how to form a volunteer team during the COVID-19 pandemic. Later, after we took a decision and formed a team, we again received another letter from the government due to which we cancelled the mobilization of volunteer teams. (Health Coordinator_Municipality 1).

A number of mechanisms were put in place by the different levels to monitor compliance to the COVID-19 policies. The federal government recruited and deployed provincial coordinators in order to assess the need of health infrastructures and human resources required for responding to the pandemic and the MoHP at central level made visits to the provincial dedicated hospital and laboratories for monitoring. At provincial level, the Ministry of Health (then functioning under Ministry of Social Development) and PHD along with WHO conducted monitoring and supervision of COVID-19 hospitals, quarantine centres and border entry points, mostly on an ad-hoc basis rather than regularly. Similarly, with support from WHO and UNICEF, the province created “isolation centre joint monitoring teams” to monitor delivery of services and maintenance of standards at quarantine and isolation centres at local levels with the use of a monitoring checklist.

However, neither federal nor provincial levels were able to monitor policy implementation and compliance at community level. The urban municipality included in this study received only one monitoring visit during the entire COVID-19 pandemic. The rural municipality included in this study (but not the urban one) formed ward committees as directed by federal government to monitor policy compliance in terms of self-quarantine, institutional quarantine, and adoption of public health standards (such as, social distancing, wearing mask and sanitizing/washing hands).

This study explored the health sector policy response to COVID-19 in the federalised context of Nepal, highlighting the critical role of the health system in policy formulation, communication and implementation across multiple levels. The study assessed how the response mobilised potential or existing health system resilience capacities and how this has affected its effectiveness, and highlighted areas which require urgent action to build a resilient health system. The findings also demonstrated how different components of the resilience framework [ 6 ] interacted that are crucial in building health system resilience. Table  3 provides a summary overview of the main findings aligning with the components of the framework.

Our findings highlighted that the federal government, who is mainly responsible for the emergency management in the federalised context, effectively handled the overall policy development process with technical leadership from MoHP and CCMC, and by engaging multi-sectoral actors. This fits within the roles in the decentralised context where federal government sets policy and leads management in emergency situation, and local governments translate them into actions with necessary adaptations. However, the participatory and inclusive process of policy formulation with the involvement of other tiers of governments (province and municipalities) and the communities was often ignored. Policies developed at federal level lacked feasibility and applicability in local contexts, which was also highlighted in another study conducted in Nepal [ 20 ]. The emergency plans and structures that were established before the federal system in the country were used in the pandemic response, but proved difficult to adapt and implement in varied local settings. Furthermore, the existing community structures at local levels, that are linking communities to the health system were not properly utilised during pandemic response, and thus emphasis should be given to community engagement by sufficiently training and mobilising community health workers (FCHVs including health workers at peripheral level) for the emergency response [ 21 ].

Effective coordination and communication was another area for which the federal government was largely criticized. Although various channels and media were used aggressively in communicating COVID-19 policies and information from federal to subnational governments, including to the public, they all used a top-down approach that raised concerns about clarity and understanding of the messages at different layers. The policy communication process, which was not systematic, timely and targeted, resulted in misunderstanding of the decisions and confusion in their implementation at the ground level, where there was no mechanism to monitor and ensure compliance to those policy decisions. Due to lack of clarity in roles and decisions, further delays in action and poor implementation were the resulting consequences. Therefore, crucial to health system resilience is to ensure that the coordination and communication channels and approaches should be appropriate and reach targeted audiences on time with clear messages [ 22 ]. Gender and equity was an area that received less attention in the policy documents, nevertheless, reactive management during implementation led to adaptations when issues started to be reported.

Another key area identified in our synthesis was availability of decision space at the local level and the capacity to use it. Local governments, despite having decision space to develop local policies and guidelines in the federalised context, were mainly relying on policies and decisions communicated by provincial and federal governments and their contextual tailoring was very rare. This was due to lack of capacity and experience, and the absence of mechanisms to develop and monitor accountability. Insufficient capacity of local government in decentralised contexts to function appeared to be a common problem across six countries in fragile and conflict-affected settings (namely Pakistan, Philippines, Indonesia, Myanmar, Nepal, Sri Lanka, and Papua New Guinea), as highlighted in a recent study [ 23 ]. This capacity gap and the contexts impact the performance, equity and ultimately, resilience of the health system [ 24 ]. The response mechanisms implemented at local levels therefore were ad hoc without effective use of evidence and resources [ 5 , 25 ]. As a consequence, the issue of low trust in local governments among the public remained, which was also highlighted in another study conducted in Cameroon, Nepal and South Africa, where governments struggled to build credibility and acceptance of public during COVID-19 [ 5 ]. Moreover, decentralization was seen in administrative structure and functions, while financial control was still centralized (the federal government holds 82% of the programme budget [ 26 ]). In line with the context in Nepal, the national level in Myanmar retains control over financing, legislation and the formulation of national policies and plans [ 27 ]. The central government in Indonesia holds 90% of the resources where districts have control over only one-third of the total public expenditure on health [ 23 ]. A combination of centralization, in which the federal government takes the lead in coordinating and providing policy guidance for improved performance, along with decentralization, where local governments have increased flexibility and decision space to increase equity and resilience [ 23 ], is sometimes argued as an effective model of decentralization. This was highlighted in a study in India, where lessons from the responses of individual states’ during COVID-19 suggested that empowering state governments to handle pandemics, while the central government focuses on designing effective strategies, increasing funding and strengthening monitoring mechanisms, can be highly effective [ 28 ].

By applying the health system resilience framework [ 6 ] to the study findings, our analysis highlights the role played by the resilience capacities of the health system and how they were mobilised in supporting the response to the COVID-19 pandemic. We found that some elements that might have contributed to the resilience of the health system and its capacity to absorb, adapt and transform in the face of the pandemic were already present and were effectively exploited. These were found in particular at federal level and included the rapid and comprehensive activation of already existing emergency structure and plans, which was yet to be tested in the federalised context. In the newly established federal system, such capacity to formulate response policies were meant to be transferred to local levels, alongside the skills and resources necessary to make efficient use of the policy formulation decision space. However, due to the novelty of the federal system and the consequent lack of experience, confusion about roles and responsibilities, insufficient local health system governance and low availability of human, technical and financial resources, those same resilience capacities were not effectively mobilised at local levels. As a consequence, a rapid response, reverting to a pre-federalisation, top-down model prevailed over a participatory approach of inclusive and open governance in decision making, that would have strengthened potentially existing resilience capacities at local levels, or to build them to ensure the longer term resilience of the local health systems. This approach promoted absorption strategies in order to cope with the pandemic but did not generally support adaptive responses of the health system.

Importantly, this last point does not mean that adaptations did not occur at the local level. While policies formulated at central level were reflecting less on local contexts and needs and did not build on locally relevant intelligence and data (rather built on global evidence), local governments were able to partially take advantage of the decision space allowed by the federalization process, at least in terms of policy communication approaches and policy implementation. We found a few examples of local tailoring of policies and guidelines, although often this was reactive rather than proactive and hampered by lack of financial, human and material resources, ambiguity in roles and responsibilities, and lack of capacity for information gathering and implementation monitoring. For example, the local governments mobilized the CICT team, adapting to the local context due to the unavailability of technical human resources indicated in the guideline. Likewise, adaptation was also seen in the operation of quarantine and isolation centres for management of COVID-19 cases.

Strengths and limitations of the study

This study aimed to explore health system resilience in Nepal in responding to COVID-19 pandemic, taking examples from two municipalities as a case study. The study offers some important insights on the need for an inclusive policy formulation process and effective communication strategies which use the right channels and approaches to reach targeted audiences in a decentralized context. These are crucial components of pandemic responses but less emphasized in other studies. Moreover, the study also shares some experiences of the country in the transition to federalization around coordination and partnership, translating capacities to local governments and generating local leadership, accountability and trust, which are instrumental to strengthen and build resilient health systems across multiple levels. However, there are some limitations to our work. The findings of this study may not be representative of wider contexts, and thus demand further research of a larger scale. However, the coping mechanisms adopted and the resilient capacities shown by the country and the local governments, and the key lessons learnt, generate important learnings for the country itself, and for other similar settings to consider during future shocks and emergencies.

This study has assessed key resilience capacities of the health system required to manage shocks, such as COVID-19 pandemic. It is clear that a strong and flexible command structure is essential in effectively dealing with an emergency situation. Although the federal government has a key role in emergency response, there is a need for decentralized frameworks to be used in emergency situations, where strengthening capacity of local governments is one of the key areas of focus, in addition to investment in infrastructure and equipment. Inclusive, responsive, evidence- and needs-based, and gender equitable policies and adoption of a clear and effective approaches to communicate the policies are crucial to building resilience to protect population health in the situation of emergency and changing health needs. Continued learning and adaptation from the COVID-19 pandemic, and from other events of acute and chronic shocks to the health system in countries undergoing structural transitions will help build resilience in the long run.

Data availability

The data generated and analysed from KIIs in this study are not publicly available because they contain interviews from informants who consented for use of the data in this study and thus would not allow for public storage. Data are available from corresponding author on request.

Abbreviations

COVID-19 Crisis Management Center

Case Investigation and Contact Tracing

Coronavirus Disease

Department of Health Services

Epidemiology and Disease Control Division

External Development Partner

Female Community Health Volunteer

Health Emergency Operation Center

Key Informant Interviews

Ministry of Federal Affairs and General Administration

Ministry of Health and Population

Non-Governmental Organization

Provincial Health Directorate

United Nations Children’s Fund

World Health Organization

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Acknowledgements

The authors would like to acknowledge all stakeholders who participated in this study and shared their valuable experiences.

This work was funded by the Foreign, Commonwealth and Development Office (FCDO), UK aid, under the ReBUILD for Resilience Research Programme Consortium (PO 8610). The funding body did not play any role in the design or analysis for the study.

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Regmi, S., Bertone, M.P., Shrestha, P. et al. Understanding health system resilience in responding to COVID-19 pandemic: experiences and lessons from an evolving context of federalization in Nepal. BMC Health Serv Res 24 , 428 (2024). https://doi.org/10.1186/s12913-024-10755-0

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Perspectives on the Framework

Robin Ewing, Alison Lehner-Quam, Amy James, Margaret Gregor, James Rosenzweig, and Jennifer Ditkoff

Teacher Education and Information Literacy

Introducing the Instruction for Educators Companion Document

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© 2024 Robin Ewing, Alison Lehner-Quam, Amy James, Margaret Gregor, James Rosenzweig, and Jennifer Ditkoff

T he ACRL Education and Behavioral Sciences Section (EBSS) Instruction for Educators Committee (IFE Committee) is charged “to make distinctive contributions as education library specialists to the field of bibliographic instruction.” 1 Beginning in fall 2020, members of the IFE Committee worked to create an ACRL Framework for Information Literacy for Higher Education (Framework) companion document for the field of teacher education. The Companion Document to the ACRL Framework for Information Literacy for Higher Education: Instruction for Educators (Companion Document), 2 approved by the ACRL Board of Directors in June 2023, is designed to provide support for teacher preparation programs to develop educator research skills and pedagogical praxis in the realm of information literacy. The EBSS IFE Committee examined key literature and professional standards and created a draft document within ACRL’s LibGuides, 3 which was revised after receiving many rounds of feedback from librarians and educators in the field. This article shares the process involved in creating the Companion Document, a theoretical overview within a disciplinary context, practical ways to teach the content, and an exploration of next steps for the implementation of the Companion Document.

Background and Disciplinary Context

Librarians who teach information literacy to students studying to become educators are supporting students’ development in three areas: teacher preparation and education, teacher professional practice, and teacher pedagogy practice. Librarians design and prepare instruction to (1) support teacher education students’ coursework in their teacher education program, (2) prepare teachers for research skills needed in their careers, and (3) prepare teachers to support the information needs and practices of their students. 4 The Framework for Information Literacy, along with inquiry and reflection practices, can deepen students’ understanding of research practice and knowledge within the disciplines. 5 Librarians who work with education students and within social science fields offer research experiences that extend into professional practice, such as supporting research for evidence-based classroom practice 6,7 and fostering and guiding K–12 students’ information literacy skills and dispositions. 8 The connections between teacher education and information literacy highlight the need for a companion document.

Figure 1. Screenshot from the Companion Document to the ACRL Framework for Information Literacy for Higher Education: Instruction for Educators LibGuide.

The IFE Committee created the Information Literacy Standards for Teacher Education 9 between 2006 and 2011 and linked that document to the 2000 ACRL Information Literacy Competency Standards for Higher Education. 10 In 2020, the IFE Committee considered revising the document to align with the ACRL Framework for Information Literacy. Communication with EBSS leadership and the ACRL Information Literacy Frameworks and Standards Committee, along with IFE Committee member discussion, reinforced a need to produce a new document focused on the Framework.

Companion Document Creation

After deciding a new document focused on the Framework was needed, the IFE Committee identified the steps needed to complete the Companion Document. They decided to work in small teams, which ensured no major task was assigned to a single person. The committee’s work started with a review of ACRL guidance on creating companion documents. 11,12 They also consulted the chairs of the EBSS Social Work Committee and Communication Studies Committee on their processes for developing companion documents for social work and journalism. A committee team used this information to create a project plan for the Companion Document creation.

The first section of the project plan was an environmental scan. The committee wanted to know how librarians integrate the Framework as they work with teacher education students and education faculty. They hosted the discussion “Teaching the Teachers: A Collaborative Discussion on the Framework and Standards for Teacher Education Students” 13 on November 13, 2020. After the discussion, a literature review on the intersection of teacher education and the Framework was conducted. As the committee reviewed the search results, they determined whether each resource aligned with specific frames. The committee also considered the reviewed literature through the lenses of social justice, metacognition, and digital/media literacy, key concepts in teacher education.

An essential feature of the project plan was multiple drafts based on feedback from education librarians. The committee used the feedback from the discussion and the literature review analysis to create the first draft of the Companion Document in LibGuides. The committee divided into three teams, with each team assigned two frames to draft. As part of this work, the teams reviewed the Interstate Teacher Assessment and Support Consortium (InTASC) Model Core Teaching Standards 14 and the International Society for Technology in Education (ISTE) Standards for Educators 15 to identify where those standards aligned with their assigned frames. The first draft of three frames was completed by June 2021. New committee members joined the teams in fall 2021. A polished draft of all frames was finished in time to share with participants before the discussion event “The ACRL Framework and Teacher Education: Shaping the Companion Document for Instruction for Education,” 16 held on December 10, 2021. Participants provided essential feedback on each frame.

Based on that feedback, the IFE Committee substantially revised the Companion Document. In particular, discussion participants asked for more emphasis on how to integrate the frames and education standards into instruction. This suggestion prompted an overhaul of the sample objectives and activities sections of each frame. The next version of the document was shared more widely within EBSS. Additionally, the EBSS Equity, Diversity, and Inclusion Task Force was asked to review the document with a social justice lens. These two rounds of feedback led to the next version. After review by the EBSS leadership, the Information Literacy Frameworks and Standards Committee, and the ACRL Standards Committee, the ACRL Board of Directors approved the Companion Document in June 2023.

Companion Document Example

The Companion Document is divided into sections corresponding to the six frames in the Framework for Information Literacy. Within each frame there is a section titled “In an Education Context.” This section articulates which information literacy knowledge practices and dispositions are relevant to each of the three teacher roles (as teacher education student, as professional, and as classroom teacher). The relationships between the three teacher roles and the frames are demonstrated in this example from Scholarship as Conversation:

In their course assignments, teacher education students need to be able to:

• demonstrate their ability to trace the history of a given scholarly conversation using citations; and
• summarize changes in educational scholarly perspectives over time on a particular topic. 17

Scholarship as Conversation also applies to a teacher’s professional practice, where they need to be able to:

• inform themselves about new ideas and understandings in teaching and education through their reading, their use of digital tools (e.g., journal and search alerts), and their participation in learning networks; and
• use their newfound knowledge to improve their own professional teaching practice. 18

Librarians working with teacher education students can prepare them for their work in PK–12 classrooms so that as teachers, they are ready to:

• invite students to respond to diverse perspectives by constructing their own arguments while crediting the authors and creators of the works to which they are responding; and
• encourage students to develop their own voice and to share their own knowledge, creative works, and inquiry findings with others. 19

The Companion Document, as a whole, helps librarians working with teacher education students to provide support for lifelong learning for educators.

Now that the Companion Document has been approved by the ACRL Board of Directors and published, the IFE Committee can assist librarians with the application of the Framework and the challenge of relating the Companion Document to state education standards. The IFE Committee also understands any document of this length and complexity will remain a work in progress. Given the success of the IFE discussion forums in 2020 and 2021, as well as the 2022 event “Fulfilling the Framework: Strategies for Activating Information Literacy Skills for Pre-service Educators,” 20 the IFE Committee anticipates continuing to facilitate online conversations with librarians and educators that will employ the document as a resource while also gathering feedback on the ways it can continue to improve. These discussions will inform future work to ensure the document serves the broadest possible array of potential users. Research into the Companion Document will also add to the limited literature available on teacher education, and the Framework will be used to inform future revisions of the document.

Based on conversations from the forums, the IFE Committee observed that librarians in this field expressed a greater need for instructional activities and assessments that implement the Framework successfully. A concerted effort to develop a larger collection of example lessons, whether by developing them in-house through the work of IFE Committee members or by soliciting and curating lessons from EBSS membership (or other ACRL sections), would benefit users of the Companion Document.

In reflecting on its work in recent years, the IFE Committee is delighted to see its goal reach fruition in sharing the Companion Document with the wider ACRL community. This could not have been accomplished without the generous contributions of the librarians and educators who participated in the discussion forums and feedback surveys. Their insights were critically important to the revision of the Companion Document. In engaging in this work, the IFE Committee learned much from the ACRL groups that had already developed companion documents for the Framework and is therefore ready to support others in the creation of companion documents. The Companion Document is a major contribution to the field of information literacy instruction in teacher education because it integrates the Framework into the work of educators at every level.

• “EBSS Instruction for Educators Committee,” ACRL/EBSS, accessed December 20, 2023, https://www.ala.org/acrl/ebss/acr-ebsbie .
• ACRL/EBSS Instruction for Educators Committee, “Companion Document to the ACRL Framework for Information Literacy for Higher Education: Instruction for Educators,” June 2023, https://www.ala.org/acrl/sites/ala.org.acrl/files/content/standards/Framework_Companion_Instruction_Educators.pdf .
• “Companion Document to the ACRL Framework for Information Literacy for Higher Education: Instruction for Educators,” ACRL/EBSS/IFE, accessed December 20, 2023, https://acrl.libguides.com/ed .
• Alison Lehner-Quam and Wesley Pitts, “Exploring Innovative Ways to Incorporate the Association of College and Research Libraries Framework in Graduate Science Teacher Education ePortfolio Projects,” New Review of Academic Librarianship 25, no. 2–4 (2019): 357–80, https://doi.org/10.1080/13614533.2019.1621186 .
• Sara D. Miller, “Diving Deep: Reflective Questions for Identifying Tacit Disciplinary Information Literacy Knowledge Practices, Dispositions, and Values through the ACRL Framework for Information Literacy,” Journal of Academic Librarianship 44, no. 3 (2018): 412–18, https://doi.org/10.1016/j.acalib.2018.02.014 .
• Andrej Šorgo and Jasmina Heric, “Motivational and Demotivational Factors Affecting a Teacher’s Decision on Whether to Do Research,” Center for Educational Policy Studies Journal 10, no. 3 (2020): 77–97, https://doi.org/10.26529/cepsj.869 .
• Tricia Bingham, Josie Wirjapranata, and Shirley-Ann Chinnery, “Merging Information Literacy and Evidence-Based Practice for Social Work Students,” New Library World 117, nos. 3–4 (2016): 201–13, https://doi.org/10.1108/NLW-09-2015-0067 .
• Di Wu, Chi Zhou, Yating Li, and Min Chen, “Factors Associated with Teachers’ Competence to Develop Students’ Information Literacy: A Multilevel Approach,” Computers & Education 176 (2022), https://doi.org/10.1016/j.compedu.2021.104360 .
• “Information Literacy Standards for Teacher Education,” ACRL/EBSS, May 11, 2011, https://www.ala.org/acrl/sites/ala.org.acrl/files/content/standards/ilstandards_te.pdf .
• “Information Literacy Competency Standards for Higher Education,” ACRL, January 18, 2000, https://alair.ala.org/bitstream/handle/11213/7668/ACRL%20Information%20Literacy%20Competency%20Standards%20for%20Higher%20Education.pdf?sequence=1&isAllowed=y .
• “Connecting Justice to Frameworks: Information Literacy in Social Work,” YouTube video, 1:00:31, posted by ACRL, May 26, 2020, https://youtu.be/Re0pU6HJxEg .
• “Checklist for Developing and Reviewing Framework Companion Documents,” ACRL, revised February 2020, https://www.ala.org/acrl/resources/policies/checklist_ss_il .
• “Teaching the Teachers: A Collaborative Discussion on the Framework and Standards for Teacher Education Students,” ACRL/EBSS Instruction for Educators Committee, November 13, 2020, https://sites.google.com/view/ebss-ife-virtualdiscussion/home .
• “InTASC: Model Core Teaching Standards and Learning Progressions for Teachers 1.0,” Council of Chief State School Officers, accessed April 21, 2023, https://ccsso.org/sites/default/files/2017-12/2013_INTASC_Learning_Progressions_for_Teachers.pdf .
• “ISTE Standards: Educators,” International Society for Technology in Education, accessed April 21, 2023, https://www.iste.org/standards/iste-standards-for-teachers .
• “The ACRL Framework and Teacher Education: Shaping the Companion Document for Instruction for Education,” ACRL/EBSS Instruction for Educators Committee, accessed April 21, 2023, https://sites.google.com/view/ebssifedec2021workshop/home .
• “Companion Document to the ACRL Framework for Information Literacy for Higher Education: Instruction for Educators,” ACRL/EBSS/IFE, June 2023, https://acrl.libguides.com/ed .
• “Companion Document.”
• “Fulfilling the Framework: Strategies for Activating Information Literacy Skills for Pre-service Educators,” ACRL/EBSS Instruction for Educators Committee, December 9, 2022, https://sites.google.com/ewu.edu/ebssifefall22discussionsession/home .

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