research based notebook

Introducing NotebookLM

Jul 12, 2023

[[read-time]] min read

An AI-first notebook, grounded in your own documents, designed to help you gain insights faster.

At Google I/O this year we introduced a number of AI-first experiments in development, including Project Tailwind — a new kind of notebook designed to help people learn faster.

Today we’re beginning to roll out Project Tailwind with its new name: NotebookLM , an experimental offering from Google Labs. It’s our endeavor to reimagine what notetaking software might look like if you designed it from scratch knowing that you would have a powerful language model at its core: hence the LM. It will be immediately available to a small group of users in the U.S. as we continue to refine the product and make it more helpful.

It’s hard to go from information to insight

We know people are struggling with the rapid growth of information — it's everywhere and it’s overwhelming. As we've been talking with students, professors and knowledge workers, one of the biggest challenges is synthesizing facts and ideas from multiple sources. You often have the sources you want, but it's time consuming to make the connections.

We started to explore what we could build that would help people make connections faster in the midst of all this data, especially using sources they care most about.

NotebookLM automatically generates a document guide to help you get a better understanding of the material

NotebookLM: an AI notebook for everyone

NotebookLM is an experimental product designed to use the power and promise of language models paired with your existing content to gain critical insights, faster. Think of it as a virtual research assistant that can summarize facts, explain complex ideas, and brainstorm new connections — all based on the sources you select.

A key difference between NotebookLM and traditional AI chatbots is that NotebookLM lets you “ground” the language model in your notes and sources. Source-grounding effectively creates a personalized AI that’s versed in the information relevant to you. Starting today, you can ground NotebookLM in specific Google Docs that you choose, and we’ll be adding additional formats soon.

Once you’ve selected your Google Docs, you can do three things:

• Get a summary: When you first add a Google Doc into NotebookLM, it will automatically generate a summary, along with key topics and questions to ask so you get a better understanding of the material.
• A medical student could upload a scientific article about neuroscience and tell NotebookLM to “create a glossary of key terms related to dopamine”
• An author working on a biography could upload research notes and ask a question like: “Summarize all the times Houdini and Conan Doyle interacted.”
• A content creator could upload their ideas for new videos and ask: “Generate a script for a short video on this topic.”
• Or an entrepreneur raising money could upload their pitch and ask: “What questions would potential investors ask?”

While NotebookLM’s source-grounding does seem to reduce the risk of model “hallucinations,” it’s always important to fact-check the AI’s responses against your original source material. When you're drawing on multiple sources, we make that fact-checking easy by accompanying each response with citations, showing you the most relevant original quotes from your sources.

Learning and building, together

NotebookLM is an experimental product, built by a small team in Google Labs .

Our team has two goals in mind:

• Build a product with our users : We’ll be talking to people and communities often to learn about what’s working well and where the gaps are, with the intent of making NotebookLM a truly useful product.
• Roll out this technology responsibly : Getting feedback directly from you is a critical part of developing AI responsibly . We will also use a strict set of safety criteria in alignment with our AI Principles and implement appropriate safeguards before expanding to more users and launching new functionality.

We’ve built NotebookLM such that the model only has access to the source material that you’ve chosen to upload, and your files and dialogue with the AI are not visible to other users. We do not use any of the data collected to train new AI models.

We hope that in these early days you give NotebookLM a shot. Sign up to the waitlist to try it out!

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Google Colaboratory

Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education.

News and Guidance

Features, updates, and best practices

Browse Notebooks

Check out our catalog of sample notebooks illustrating the power and flexiblity of Colab.

Track changes

Read about product updates, feature additions, bug fixes and other release details.

Dive deeper

Check out these resources to learn more about Colab and its ever-expanding ecosystem.

Building responsible AI for everyone

We’re working to develop artificial intelligence responsibly in order to benefit people and society.

JupyterLab: A Next-Generation Notebook Interface

JupyterLab is the latest web-based interactive development environment for notebooks, code, and data. Its flexible interface allows users to configure and arrange workflows in data science, scientific computing, computational journalism, and machine learning. A modular design invites extensions to expand and enrich functionality.

Jupyter Notebook: The Classic Notebook Interface

The Jupyter Notebook is the original web application for creating and sharing computational documents. It offers a simple, streamlined, document-centric experience.

Language of choice

Jupyter supports over 40 programming languages, including Python, R, Julia, and Scala.

Share notebooks

Notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer .

Interactive output

Your code can produce rich, interactive output: HTML, images, videos, LaTeX, and custom MIME types.

Big data integration

Leverage big data tools, such as Apache Spark, from Python, R, and Scala. Explore that same data with pandas, scikit-learn, ggplot2, and TensorFlow.

A multi-user version of the notebook designed for companies, classrooms and research labs

Pluggable authentication

Manage users and authentication with PAM, OAuth or integrate with your own directory service system.

Centralized deployment

Deploy the Jupyter Notebook to thousands of users in your organization on centralized infrastructure on- or off-site.

Container friendly

Use Docker and Kubernetes to scale your deployment, isolate user processes, and simplify software installation.

Code meets data

Deploy the Notebook next to your data to provide unified software management and data access within your organization.

Voilà: Share your results

Voilà helps communicate insights by transforming notebooks into secure, stand-alone web applications that you can customize and share.

Currently in use at

Open standards for interactive computing.

Project Jupyter promotes open standards that third-party developers can leverage to build customized applications. Think HTML and CSS for interactive computing on the web.

Notebook Document Format

Jupyter Notebooks are an open document format based on JSON. They contain a complete record of the user's sessions and include code, narrative text, equations, and rich output.

Interactive Computing Protocol

The Notebook communicates with computational Kernels using the Interactive Computing Protocol, an open network protocol based on JSON data over ZMQ, and WebSockets.

Kernels are processes that run interactive code in a particular programming language and return output to the user. Kernels also respond to tab completion and introspection requests.

Data Management

• Naming and Organizing Data
• Storing, Backing up, and Versioning Data
• Documenting Methods and Describing Data

Creating Digital Research Notebooks

Digital notebook advantages, open science framework (free), create an osf project research notebook, labarchives (brown-paid subscription), create a labarchives lab notebook, further reading, learning objectives.

This page is designed to help you:

• Compare the advantages of using a digital research notebook
• Create a digital notebook for you and your collaborators to document the steps of your project and manage your project’s data

Below you'll find two tutorials for setting up a digital notebook using a free and open platform or using an Electronic Lab Notebook (ELN) paid for by Brown University.

• Create an Open Science Framework (OSF) online digital research notebook
• Create a LabArchives Electronic Lab Notebook  (ELN)

• Access online and via mobile
• Search for text and keywords
• Share with collaborators
• Track revisions
• Export and save digital copies

The Open Science Framework (OSF) is a free online project management platform developed by the Center for Open Science that is often used as a cloud-based research notebook. OSF is open software, so it is your own account and you will still have access if you leave Brown. Although "science' is in the name it is subject agnostic and can just as easily be used by humanities researchers.

• Set up an OSF Project to serve as a notebook for each of your research projects and share access with any collaborators.
• Add collaborators and grant viewing and/or editing privileges.
• After a project is completed (or even while the project is ongoing) make your OSF Project open to the public and get a link (URL) for sharing with others to view your project online and for citation.

An OSF Project is made up of Components . Each component you create and add to your project can represent a discrete part or stage of your project. For example, you could create a component for your experimental protocol, the data you have collected, your analysis, and one for writing up the results. Each component has its own Wiki that you and your collaborators can use to record your notes, experimental steps, and observations.

You can connect any existing free cloud storage and popular collaborative platforms to a component, such as GitHub for analysis code or Google Drive or DropBox for shared folders of project files. 

Create OSF Account

Go online and visit the URL: https://osf.io 

Click on Sign In in the upper right corner.

• Click on Select Your Institution and scroll down and select Brown University from the drop down menu
• Click Sign In and enter your Brown University username and password.

If you do not have a Brown University username and password, then click Sign Up and follow steps to create a free OSF account.

Create OSF Project

After signing in, you arrive on your  Dashboard  page. Your dashboard will show the OSF projects that you have created and/or OSF projects that you have been added to as a collaborator. To create a new OSF project follow these steps.

• At the top of the Dashboard page select  Create new project  (another way is from the search bar at the top of the page select  My Projects  and then  Create new project ).
• A pop-up window will appear where you will be able to enter the name of your new research project and then click  Create .

After you create your OSF Project you will be taken to its landing page. At the top you will see the URL for your project, the title of your project, your name and any collaborators you add, and the privacy setting. The default privacy setting for your new OSF project and any components you add is private, which means it is only viewable by you and/or any collaborators that you have added. You can choose to change this and make the project or any of its components public at any time.

• Click on  Description  and you can add a sentence describing your project to help you navigate projects in your dashboard page, e.g., “Digital Research Notebook for Summer Research Project.” 
• Below in the box titled  Wiki  click on the box-and-arrow icon and this will take you to the Wiki’s  Edit  panel. Enter your research questions and more detailed abstract about the project and click Save. You can edit your project wiki at any time.
• Affiliate your project with Brown University by clicking on  Settings  on the upper toolbar
• Select  Project Affiliation/Branding  among menu options
• Search and select Brown University in the search bar and click  Save .

View the online tutorial  Creating and Managing Projects  on the OSF site or watch the video below for more information on creating an OSF Project.

Create OSF Project Components

On the landing page of your OSF Project, in the box titled  Components , click on  Add component  and in the pop-up window give your component a name. You can repeat this as many times to add the separate parts comprising your project as they are required, such as a component for each of your experiments or for each of the stages of your project, such as an interview or survey. As you add components they will be listed on the Project’s landing page and you can reorder these, if needed. An important aspect of a component is integrating it with any tools that you and your collaborators use, such as GitHub repository or Google Drive, Box, or DropBox. To integrate these tools into your OSF Project components follow these steps.

• On the toolbar at the top of your project's landing page click   Add-ons
• Locate your preferred cloud storage provider from those available on the  Select Add-ons  menu.
• Next to the provider click on  Enable  and click  Confirm  in the pop-up window.
• The ones you choose to integrate into your Project space will appear in the box  Configure Add-ons . Click  Connect Account  next to each provider and then enter your username and password for each account you wish to grant OSF the permission to access.

View the online tutorials  Create Components   and  Connecting Add-Ons   on the OSF site or watch the video below for more information on creating components for your OSF Project and integrating cloud-based storage and collaborative tools .

Add Contributors

You can team contributors and grant them certain permissions via these steps.

On your Project landing page select  Contributors  from the top toolbar.

• Click  Add+  and enter the names and email addresses of your collaborators. If they already have an existing OSF account you can search for their name in the search bar and click to add them to your project. If they do not have an existing account click  Add as an unregistered contributor . Unregistered users will receive an email from OSF informing them of their addition to your project and inviting them to create an OSF account.
• Next to their name click on the  Permissions  drop down and select  Read  if you only want them to be able to view your project or  Read + Write  if you want them to be able to edit and add to your project.

View the online tutorial  Contributors and Permissions  on the OSF site or watch the video below for more information on adding collaborators to your OSF Project.

LabArchives@Brown  (LabArchives Brown University Edition) is Brown University’s institutional paid subscription to LabArchives . It is available to all members of the Brown University community, including clinical faculty affiliates. LabArchives is an electronic laboratory notebook (ELN) platform that offers more advanced features than many open digital research notebook platforms, including unlimited storage and more secure storage and versioning options such as being FDA 21 CFR Part 11 compliant. Create a LabArchives Electronic Lab Notebook by following the tutorial below.

Students can create as many LabArchives notebooks as they wish. Once logged in students can view the notebooks they own as well as ones shared with them.

For Independent Research Projects

If you are a student and are working on an independent project, then by default you will have the  Owner Role  of your notebooks that you create. You can choose to add collaborators and grant them certain viewing and editing privileges. As owner you can share an entry, page, folder or even your entire notebook with a collaborator. You can have your notebooks transferred to a private LabArchives account when you leave Brown so that you can retain access.

Working with a Faculty Member/Primary Investigator (PI)

If you are working under a faculty member on their project or in their lab that uses LabArchives, then they may set up a notebook for you and invite you to the notebook as a User. You can make a copy of your LabArchives notebook before leaving Brown.

When you log-in to  LabArchives@Brown  you will see a landing page dashboard titled  Notebooks . Along the left side bar you can sort and view all the notebooks that you have created as well as those you do not own but you have been provided with view access or added as a contributor to a notebook owned by someone else such as a faculty member serving as a Principal Investigator (PI).

Create an Account

• Go online and visit the URL: https://library.brown.edu/info/labarchives/
• Click on Sign up or log in to LabArchives
• Enter your Brown University username and password

If you do not have a Brown University username and password, then visit labarchives.com and create a free account by clicking Sign Up and following the steps to create a username and password. The free version of LabArchives does not have the same storage features as the LabArchives Brown University Edition, including restrictions on the size of a file that can be uploaded and total storage size.

Create a Notebook

When you log-in to LabArchives@Brown you will see a landing page dashboard on the top of left-side toolbar called  Notebooks . Click on  Notebooks  and the  + icon  to create a new notebook. 

In the next pop-up window  Create a New Notebook  you can enter a name for the new notebook, e.g., “Summer Research Project 20XX.” Next will be asked to choose a Folder Layout. 

• If you select None , then you can create and name the folders as you need to fit your project (recommended)
• After selecting the folder layout click  Create Notebook . Your notebook will now appear in the left-side toolbar under  Notebooks .

View the tutorial  Getting Started   on LabArchives site or watch the video below for more information.

Add New Folders and Subfolders

After creating a new notebook you can start creating any folders and subfolders within folders where you want to store the pages of entries and/or project files. 

• To create a new folder go to the left-side bar and click into the notebook in which you wish to add the folder and click  + New  and then  Add new folder .
• To create a new subfolder within an existing folder click on the existing folder to open the folder and  click + New  and then  Add new folder  .

Add New Pages

In order to make an entry in your notebook, i.e., start writing notes and observations in your notebook or add a file or an attachment, you first have to create a Page. To keep your notebook organized it is recommended to organize pages with folders. For example, you could create a folder and name it the name of the project and then create subfolders named with the date, YYYYMMDD to hold the pages created on that date.

• To create a new page in your notebook click on the folder or subfolder you want the page to appear and click  + New  and  Add new page . A pop-up window will appear asking you to provide a name for the page.

Create New Entries

To make an entry on a page find the page you would like to add the entry.

• In the toolbar at the top of the page click  + New   and a drop down menu will appear with several options. Entries can be made in several different ways
• If you want to be able to type directly on the page you can select  Rich Text   on the upper toolbar. A  Rich Text Entry Editor  will appear and you can begin typing and create any hyperlinks or attachments as needed.
• If you prefer using  Microsoft Office  tools such as  Word  or  Excel  you can click on the built in  Office Document  in the upper toolbar. You can also use your own Microsoft Office tools and save to LabArchives by downloading the  LabArchives Microsoft Office Plugin  by clicking on the ellipsis ⋮ icon in the upper right hand corner of the notebook and clicking on  Downloads .
• If you want to attach a file click on  Attachment  located on the upper toolbar (e.g., attach a file such as an image to an entry and to use the annotation tools to write notes on the image).
• Add  Google Docs  or other tools (freezer boxes, calculators, periodic table) by clicking on the  Widget  in the upper toolbar   and select from the drop down menu. 

Remember to save an entry to the page by clicking  Save to Page .

View the online tutorial  Creating and Managing Entries  on LabArchives site or watch the video below for more information.

Sharing with Collaborators

Share a folder and pages.

• To share a folder or page left click (mac)/right click (pc) on the folder or page in the left-side navigation bar and select  Share . In the pop-up enter the names and email addresses of the persons with whom you would like to share access or you can choose to generate a sharing link. 

Share an Entry

• Scroll to the entry you wish to share on the page. Hover your cursor over the top and a toolbar will appear with the  Share  icon. In the pop-up enter the names and email addresses of the persons with whom you would like to share access or you can generate a sharing link. 

Share a notebook

• Click on the ellipsis  ⋮  icon in the upper-right hand corner of the notebook. Click on  Notebook Settings . Under  User Management  you can invite a collaborator to your notebook by entering their names and email addresses. Next to their names click on  Role  to select their permissions (e.g., Read + Write). They will receive an invitation to create an account or or you can choose to generate a sharing link.

View the online tutorial  Sharing LabArchives Notebooks  on the LabArchives site or view the video below for more information.

• Harvard Medical School Electronic Lab Notebook Feature Comparison Matrix

This guide was designed to help you:

• Compare the advantages of using a digital research notebook
• Create a digital notebook for you and your collaborators to document the steps of your project and manage your project’s data
• << Previous: Documenting Methods and Describing Data
• Last Updated: Jul 12, 2023 8:33 AM
• URL: https://libguides.brown.edu/DataManagement

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• TECHNOLOGY FEATURE
• 03 May 2021

Reactive, reproducible, collaborative: computational notebooks evolve

• Jeffrey M. Perkel

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This year marks ten years since the launch of the IPython Notebook. The open-source tool, now known as the Jupyter Notebook, has become an exceedingly popular piece of data-science kit, with millions of notebooks deposited to the GitHub code-sharing site.

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Nature 593 , 156-157 (2021)

doi: https://doi.org/10.1038/d41586-021-01174-w

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Electronic Research Notebooks in the Educational Setting: A Scoping Review

• Published: 13 July 2023
• Volume 32 , pages 697–709, ( 2023 )

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• Eric Prosser   ORCID: orcid.org/0000-0002-9214-6298 1 &
• John Kromer   ORCID: orcid.org/0000-0002-0901-9889 2  

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Electronic research notebooks (ERNs) are used under a variety of names: electronic laboratory notebooks, digital laboratory notebooks, electronic field notebooks, and electronic engineering logbooks, to name a few. ERNs are common in industry and increasingly common in academia. This scoping review explores the literature describing the various uses and application of ERNs in an educational and teaching context. Using a common search string and eight indices and databases—Scopus, Web of Science, Engineering Village, ERIC, PubMed, LISTA, Scifinder-n, and ASEE—the study identified 38 articles that describe educational and teaching uses of ERNs. The types of ERNs used, the fields in which they were used, and the educational level of their use are explored. Furthermore, the scoping review discusses common advantages and disadvantages of ERNs with respect to paper notebooks as identified by the literature and highlights issues of equity and access that ERNs implicate. Finally, directions for future studies and actions are offered.

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Despite the increasingly digital nature of society there are some areas of research that remain firmly rooted in the past; in this case the laboratory notebook, the last remaining paper component of an experiment. Countless electronic laboratory notebooks (ELNs) have been created in an attempt to digitise record keeping processes in the lab, but none of them have become a ‘key player’ in the ELN market, due to the many adoption barriers that have been identified in previous research and further explored in the user studies presented here. The main issues identified are the cost of the current available ELNs, their ease of use (or lack of it) and their accessibility issues across different devices and operating systems. Evidence suggests that whilst scientists willingly make use of generic notebooking software, spreadsheets and other general office and scientific tools to aid their work, current ELNs are lacking in the required functionality to meet the needs of the researchers. In this paper we present our extensive research and user study results to propose an ELN built upon a pre-existing cloud notebook platform that makes use of accessible popular scientific software and semantic web technologies to help overcome the identified barriers to adoption.

In scientific research, communication is essential; between researchers, funding bodies, industry, and members of the public. Ideas need to be shared, evidence disseminated, plans discussed, findings recorded, and errors corrected. Researchers may work alone, but their research is of little value to the scientific community if it isn’t disseminated. The scientific record can act as a legally binding record that protects intellectual property (IP) [ 39 ]. Historically the paper laboratory notebook and the scientific paper have been at the centre of this scientific communication [ 12 ]; however this is being slowly replaced by the arrival of digital technologies and the Internet and the Web in particular [ 7 ].

Digital Technologies are shaping the way experiments are performed, results captured, and findings disseminated. Computers enable a myriad of functions that benefit researchers/scientists, they can be searched, shared, easily backed up, and readily accessed [ 18 ]. They facilitate interactive computation, electronic communication, multimedia, and digital information management [ 50 ]. Within the lab, instruments are mostly computer controlled; computers are the main tools for capturing, analysing, and annotating data. Electronic laboratory notebooks (ELNs) are also transforming the way that the scientific record is captured with a revolutionary transformation from paper notebooks to the digital capture of experiments [ 6 ].

ELNs offer significant benefits to researchers by facilitating long-term storage, reproducibility, and enhanced availability of experiment records across multiple devices, ensuring standard operating procedure compliance and providing interfaces to instrumentation, supporting IP protection, collaboration, and open science [ 4 , 21 , 24 , 43 , 49 ]. ELNs eliminate the need for manual transcription and can be used by distributed groups [ 32 ], facilitate managing notes, and simplify the inclusion and curation of digital resources (e.g. instrument data, analysis results) [ 2 ]. While some systems are restricted to repositories of raw data and results, others have the potential to support researchers through the whole experiment lifecycle [ 17 , 23 ].

More recently, semantic lab notebooks (SLNs) have utilised semantic web technologies to expose research data as formalised metadata [ 10 ], and to link between the different data sets collected throughout the experimental process [ 42 ]. Incorporating semantic web technologies within ELNs, using RDF and ontologies to enrich the data with meaning and context, provides new functionality such as making inferences about experiment types, and creates valuable links between experiment outcomes and their final reports [ 2 , 5 , 10 , 23 , 32 ]. Making ELN data machine readable increases interoperability, facilitates integration with third party tools and enables automatic generation of materials for deposition in an archive or publication [ 10 ], increasing the usefulness of the tools for researchers.

Although ELNs are being increasingly used for industrial research, uptake in academia is limited [ 19 , 35 ]. This paper explores the current offerings of ELNs and Electronic Notebook software. Our research conducted studies to investigate the attitudes of academics towards ELNs, and their desired functionality. It presents an overview of the barriers to adoption within academic environments, researcher behaviour, and key features for ELNs. Following these findings, we discuss priorities for future ELN development and propose our Semantic Platform based ELN solution. Table  1 introduces the user studies that will be discussed in this paper.

The market today

The current ELN Market is oversaturated with choice; however, despite the wide range of products available there is no obvious ‘leader’. Additionally, the scientific community is still resistant to using ELNs, despite the popularity of Electronic Notebooks. Electronic Notebooks that have been subverted to ELN usage, current ELN offerings, and the attitudes to ELNs and their current usage have been examined and detailed in this section.

Electronic notebooks

Today’s market has multiple offerings for Electronic Notebooks: (Microsoft Word, Office 365, Google Docs), Evernote [ 16 ] and OneNote [ 30 ], which have been evaluated for use as ELNs [ 33 , 46 , 47 ]. Oleksik et al.’s [ 33 ] study reported that the collaborative features of OneNote facilitated faster and easier sharing, and enabled simultaneous communication between researchers, irrespective of location. Users trialling Evernote as an ELN [ 47 ] said they appreciated the electronic affordances such as ‘accessible from any online computer’ and ‘ability to search’, but found that it was lacking in domain knowledge; stating that it was ‘simple and practical for some laboratories, but for others it does not offer features specialised for fields such as biology chemistry or quality assurance/quality control’. A balance may need to be struck between making an ELN usable across multiple disciplines, whilst still providing enough domain specific knowledge.

Whilst there are many attractive affordances of storing your notes electronically, it is of concern to researchers whether their data is kept truly private or not, once it has been put into these services. Different service providers differ in their privacy policies. For example, Google Docs states that not only do the users maintain intellectual property of any content they create, content will not be shared with any third parties, and the user can take their data with them if they choose to leave Google Docs [ 20 ]. However, other services such as Microsoft Office 365, may give contracted third parties access to their customer data (which includes both personal data such as names and email addresses, but also data uploaded into their systems such as images and documents) to perform certain services [ 29 ]. An example of a privacy policy controversy is Evernote, where the default was for their employees to be able to read users content to ascertain the accuracy of their machine learning algorithms [ 44 ]. It is important for researchers to be aware of privacy policies, and to ensure that research data is secure and can’t be read by third parties when using any software.

Electronic lab notebooks

Southampton University’s ELN Market study identified 103 ELNs [ 1 , 27 , 36 , 42 ], 72 active and 30 no longer active; either due to discontinuation or purchasing by larger companies. The Active ELNs were further investigated to see which domains they supported, and their platform and licensing availability (Figs.  1 , 2 ).

A chart illustrating the different domains represented by the active ELNs in the market

A chart illustrating the licensing and platform information across the active ELNs in the market

The different licensing categories and associated considerations are as follows:

Paid for—This is a proprietary piece of software that can be purchased, which may use proprietary data formats.

Paid (with free version)—This is a proprietary piece of software that can be purchased, but which also has a version of this software which can be used for free; either as a trial for a fixed period of time, or a version that has reduced functionality.

Open source—This is a product where the code behind the actual software has been made openly available so that anyone can redistribute it and edit it as long as they conform to the licensing conditions. Open Source products are often free, but not always, and could use either standard or proprietary data formats.

Free—This is a product which is free to use.

These findings illustrate an array of ELNs ranging from supporting specific disciplines (such as eNovalys [ 15 ] which is aimed at chemists), to providing all-purpose solutions (such as Kinematik’s eNovator ELN [ 25 ] which aims to provide a multi purpose ELN that can be used in many different areas). However, a common factor is that most of these ELNs require payment. Additionally slightly over 60% of them are web based/platform independent, with the rest only available on certain operating systems or without a disclosure of their platform compatibility.

There appears to be a proclivity towards ELNs that make use of pre-existing software. NuGenesis allows users to drag and drop Excel and Word files into their ELN, eLabJournal provides Excel inside it’s ELN, and LIMOSPHY uses Microsoft Word templates. This illustrates an increasing awareness that scientists do use notebooking software, even if they don’t specifically use ELNs. Additionally it suggests that there is a place for ELNs during the final write up process, as well as during the physical experimental process. These ideas will be explored further in “ Proposal ” section. In addition to the market investigations, current ELN usage was also researched. BioSistemika investigated ELN Usage, and the DaM survey looked at attitudes towards ELNs.

ELN usage and barriers to adoption

Despite the saturated ELN Market, results from the BioSistemika and DaM surveys indicated that whilst a large percentage of academic users are considering or interested in using ELNs (as shown in Fig.  3 ; Table  2 ), they are lacking in uptake in academia [ 19 , 35 ]. Many scientists extensively use computers, yet continue to use paper notebooks throughout their experiments; highlighting that computer illiteracy or an aversion to technology cannot fully explain resistance to ELNs [ 26 , 28 , 41 ].

The results of the BioSistemika Webinars: Are you using electronic laboratory notebooks (ELNs) in your Daily Lab Routine?

The University of Southampton’s Lab Practice Study asked users about their ELN usage and experiences. Some participants had used ELNs such as LocalWiki, LabTrove, Blog3, BioBook, Enovalys and an industrial one on a short term basis. The industrial ELN was unfavourably described, whilst the other ELNS were only deemed useful for certain purposes. One participant found Enovalys very useful for inorganic work, but lacking the required functionality for their transport runs. Equally, participants who tried LabTrove and Blog3 found some of the elements useful in certain situations, but all defaulted back to Word documents. One participant suggested that this was the case because it did not contribute in a systematic way to their work.

There are therefore challenges and barriers to adoption of ELNs. Figure  4 and Table  3 illustrate the key barriers that our studies identified, and these are described in more depth in the following sections.

The barriers of using an ELN from both a research lab and a diagnostic lab

As shown in Table  3 , a large percentage of survey respondents indicated that cost was a significant barrier to ELN adoption [ 4 , 19 , 35 ]. This includes financial outlay, staff hours, troubleshooting, and the fact that long-term use is likely to require on-going maintenance and support. There are also concerns about the required database administration and support, with suggestions that having professional IT staff to help with setup and maintenance would be pivotal.

One respondent experienced sharp price-increases in database maintenance and upgrade costs after an initial discount. Other concerns are service providers not competing to keep costs down, and the potential cost of storage space; indicating disincentives if the University charges groups for storage space. Figure  4 illustrates a willingness to pay up to $50 a month for an ELN, but not $100; suggesting that ELNs reach a point where they are considered ‘too expensive’ (Fig.  5 ).

The maximum costs that the respondents of the BioSistemika’s ELN survey would be willing to pay for an ELN per month, from the perspective of those in Research, and with Purchasing Power

Other comments queried whether funding was available for ELNs in universities; suggesting that web-based systems could significantly cut costs, as they require less hardware.

As evidenced by Fig.  2 , most of the ELNs available in the market are proprietary pieces of software that require purchasing, there are also some free and open source offerings available. The free options would clearly have the advantage of being cheaper to run and test but may have disadvantages depending on the nature of the software. The paid for and free software model (one of the categories in Fig.  2 ) will have enterprise users to generate its revenue, and are able to offer reduced free versions to other users to generate recognition; providing the benefits and stability of proprietary software with a potential lack of cost. However, the fear is that other standalone free offerings are more likely to disappear, potentially alongside the research data. Some of the inactive free ELNs that were identified as part of the University of Southampton’s ELN Study were listed on [ 1 , 24 ] with websites that had seemingly vanished with no new obvious location. Open Source software is often free (although not always) and has a significant advantage over proprietary software with respect to their potential longevity. Both Open Source and Proprietary projects will always be at risk of ceasing to continue, either due to lack of funds or the original developers leaving the project. However, given the licensing of Open Source projects which makes it possible to view and change the source code, other developers are able to access, update and support the software.

Ease of use

Another challenge is the perceived ‘ease of use’ of paper notebooks compared to electronic systems. Paper notebooks are considered easier to use, input data to, read, transport, inexpensive, readily available, ‘turn on’ instantly, have infinite battery life, are socially acceptable during meetings, and require no training and minimal IT support [ 4 , 8 , 11 , 19 , 28 , 50 ]. Whereas, ELN software for taking notes is considered more difficult to use, timely and less flexible; leading to anxieties about ELNs stability, accessibility and availability [ 14 ].

Our interactions with researchers and ELN users demonstrate that ease of use is vital to adoption. In the DaM survey, 99% of respondents indicated that ease of use would influence their ELN choice, with almost 80% rating it as very important. One comment reflected the desire for a flexible generic solution, rather than an ELN designed for a specific research area, due to anxieties that their research “doesn’t fit neatly into one category”.

Attitudes to ELNs

Adopting an ELN only makes sense if the whole department adopts it, which allows for sharing costs and training; repositories, consistency and use of standards could also be relevant [ 10 , 42 ]. Several comments reflected their assumption of students and postgrads rejecting ELNs through “resistance to change in some groups”, noting that some students didn’t like their experiences of ELNs, and might consider using them as an “additional burden”.

Access to ELNs

In the Uses of ELNs in Academia survey, 74% expressed concerns about needing to enter data in both the lab and write-up area, due to a lack of suitable hardware or software capabilities to facilitate ELN usage inside and outside the lab. This can lead to copying and pasting printouts into paper notebooks and manually transcribing data between notebooks and computers; which can result in data loss, transcription errors and records stored haphazardly [ 9 , 32 ]. Popular suggestions were to use mobile computers or tablets for portability in and out of the lab, and that web-based ELNs could improve accessibility.

Lack of appropriate hardware access in the lab lead to 12.5% of participants in the Post Pilot Survey ceasing to use the trialled ELN, and resulted in several needing to perform tasks manually. Other anxieties frequently raised, included risk of damage or contamination, security, ‘hassle’ of carrying laptops around, shortage of computers for sharing, lack of bench space for computers, ELN not supported on chosen mobile platform, and lack of wifi access. Primary workarounds for these issues appeared to be printing out experiments, writing up experiments retrospectively, or using paper notebooks alongside the ELN.

Software and system integration and compatibility

Researchers use different operating systems, but both the ELN Market study and comments from the DaM survey revealed a lack of availability of ELNs for Macs. It was suggested that iPads could work as a shared notebook due to their ease of transport, although software would need to be compliant with iOS and other mobile platforms, or web based. A perceived barrier was linked to integrating ELNs with existing infrastructures. The DaM Surveys had similar concerns that users might be expected to purchase new ELN software at each operating system upgrade; which could contribute to system costs, support costs, and additional training requirements.

Electronic pen data entry, integration with digital repositories for archiving purposes and bibliographic management have also been mentioned with regards to integration with existing tools. The DaM Pilot Program elicited a need for software compatibility, database integration, electronic data, and other ‘common software’ (e.g. Word and Excel), and options to purchase add-ons for increased functionality. Users found problems using the ELN on a 64-bit operating system and on macs, or with Chemdraw, office attachments, uploading photographs, and “…it was too cumbersome to import files from our current systems…”. ELN data input seems to have been a recurring issue, alongside failings in basic expectations about data management that heightened existing anxieties.

Data compatibility and portability

In the DaM Pilot survey just under 70% expressed concern about the ELN capturing information easily, with 81% considering automatic experiment data capture important. Comments indicated that capturing a range of data is important, but raised concerns about the difficulties of instrument integration, partly due to a lack of standards between different manufacturers. Many comments expressed frustrations about not being able to link to specific experimental data such as spectroscopic results.

Several comments indicated worries about the ability to extract and move data between different ELNS and machines; these concerns relate to price hikes with a provider, longevity of commercial packages, and changing institution. Other comments addressed issues of proprietary formats including previous bad experiences of “being tied into data formats” or being left with only a PDF of their data; although the desired transferral formats differed between respondents. Some comments embraced the importance of open data and not being tied to a particular commercial package, suggesting an open source ELN to resolve the problem. This suggests that researchers perceive open source offerings to be more likely to use standard data formats rather than proprietary formats. Concerns were also expressed regarding accessing databases and notebooks across different machines, suggesting that users expect their information to be stored locally or in a centralised system, and are concerned about data security.

What do users do?

What users say they do doesn’t always match their actions; therefore after establishing the main adoption barriers, we investigated how the researchers actually worked. Four focus groups were run with 24 postgraduate chemists, physicists and biologists to discuss their current practices. Additionally, four different chemistry labs were observed to see how scientists operated there.

We found that different researchers vary their working patterns and note-taking, and have contrasting needs when it comes to sharing records with others. Therefore a ‘one size fits all’ approach to tool design wouldn’t be effective. Tools need to provide considerable flexibility and customisation to accommodate different needs. The high level results of these activities across the different disciplines are presented in Table  4 , and will be further discussed later on in this section.

The biologists and physicists from these focus groups were mostly uniform in their methods, whereas the chemists were more diverse, highlighting differences in their approach even within a single discipline.

Computational chemists used some software, with sporadic use of lab books and scraps of paper, whereas the ‘wet’ chemists had stringently organised lab books for different tasks. One chemist used blogs and Word documents alongside their paper notebooks, and the crystallographers relied heavily on their paper sample books. The inorganic and organic chemists used paper lab notebooks during experiments, and only used lab computers to access the instruments they were linked to. Note-taking differed depending on the situation. For experiments, the lab book was typically used to record observations and initial values. The chemists recorded different types of data including energy values, simulations, temperature, masses, observations, schemas, and protocols. These findings have similarities to Reimer and Douglas’s [ 34 ] work, illustrating how information recorded remained much the same; but also demonstrating that different chemists possess contrasting needs for recording their notes. Constructing one’s own ‘templates’ or other mechanisms for standardising data capture appears to be common in academic environments [ 40 ]; therefore providing capabilities to facilitate this is likely to be popular [ 2 , 40 ]. Allowing users to edit their own templates poses challenges. This is illustrated by a comment from one of the lab observation participants, who resented being asked to use a template rather than expressing themselves in their own style.

Chemists also differed in how they linked their paper and electronic notes. The physicists and biologists linked them by date, whereas the chemists inconsistently used a variety of codes; reflecting the personal nature of note organisation [ 40 ]. Despite their differing lab work, there was a common theme of using instruments (e.g. X-ray machines or diffractometers) to read data, and linking statements in their lab book to reference electronic data location and any data values that required inputting to other software. In some situations it may be necessary to capture some information on paper, and ELNs therefore need to facilitate the inclusion of such information with the research record.

Different disciplines had varying restrictions on what equipment could be taken into the lab. The biologists didn’t have specific restrictions, although one biochemist mentioned that there were concerns about bringing in outside equipment in case of contamination. The physicists couldn’t bring equipment into their cleanroom to avoid contaminating the environment; contrastingly, the chemists wouldn’t take technology into the lab in order to avoid damaging it with chemicals. Computers in the lab weren’t often online, and most were connected to specific instruments. When asked, participants indicated a reluctance to use instrument dedicated computers for any other purpose, such as making notes, accessing documents remotely, or using cloud software as they didn’t have network access. One chemist stated that “once you’ve started doing something one way, you don’t want to change it”.

To investigate the participant’s current searching and backup procedures, they were presented with three scenarios to discuss (illustrated in Fig.  6 ):

Imagine you’re trying to locate some work from 6 months ago, how would you locate you notes and associated data?

Imagine there’s a fire in your lab and all of your paper notebooks are destroyed, how much work would you lose and how could you go about recovering it?

If you fell under a bus tomorrow, and were temporarily indisposed, how would your supervisor/industry sponsors/colleagues access your work?

For Scenario 1, participants revealed that they organised their lab books chronologically, and the most common method of locating previous work was to go back through their lab book by date to locate work from a particular time period. Similarly to locate previous work on a computer participants said that they would search by date to find the appropriate data files, or would search by name if that proved unsuccessful.

Cartoon depicting three different scenarios, Scenario 1: Trying to search for some work/data 6 months later, Scenario 2: What would happen if your lab was set on fire and you lost everything in there, Scenario 3: If you were indisposed for a while how would your supervisor/research group access your work

Scenario 2 provoked different reactions. Some participants were unconcerned at the prospect of losing their lab books, and thought reproducing what was needed wouldn’t take too long, as a lot of the information was only ‘useful in the moment’, or a list of things that didn’t work. Whereas other participants elicited responsed such as ‘I’d be ruined’, ‘a nightmare’, ‘might as well stop my Ph.D. now’. Particularly with reference to the idea of their labs catching fire, several participants seemed more concerned at the idea of losing their lab samples or compounds; suggesting that perhaps their lab books would not be the biggest loss in a fire.

Scenario 3 revealed that generally participants don’t have measures in place to enable their supervisors to access their work if something happened to them. One of the biologists had a particularly strict supervisor who required their students to photocopy all of their lab books and work, but that was a rare exception. It did however transpire that the participants believed that other group members would probably be able to access their work and give it to their supervisors, but didn’t believe that they would be able to follow their lab books or the structures they’d put in place to link together their paper and electronic notes.

This continues the earlier theme about participants showing less concern towards backing up their paper based work. They are obviously aware that these scenarios could occur, but clearly don’t perceive them as likely or serious enough to merit much pre-emptive preparation, apart from circumstances where their supervisors have put procedures in place. Capturing notes and data electronically has clear backup and archiving benefits. Not only can electronic information be automatically backed up and securely stored, but the information can become accessible across multiple locations. Outdated information can be archived so that it can be retrieved later if needed, or to be shared with other researchers through deposition or publication.

What do users want?

Having discussed with the users what they actually do, this section will look at what features the users say they want, with information taken from all studies B, D, E and F.

These have been grouped according to the different categories in “ What do users do ” section in addition to a new category of project activities that came out of this research. These features have also been linked to the associated priorities of the iLabber pilot project for those who found these features very or quite important; and it’s been noted which barriers these features aim to address.

The full breakdown of priorities from the iLabber Pilot Project are shown in Fig.  7 .

The main priorities of different ELN features from the respondents of the iLabber Piilot Project, ranging from whether respondents saw them as not important to very important

Based on the needs elicited from our user studies, we formulated a proposal of how to construct an ELN environment that would fit with these requirements. The majority of ELNs have been created from scratch including the underlying ‘notebook’ part [ 31 , 32 , 42 ]; an alternative would be to build on top of a generic Electronic Notebook (which are more popular than ELNs) with domain specific features. Many of these Electronic Notebooks already have collaborative cloud based features, and could be further expanded with domain knowledge and Semantic Web technologies. Additionally, based on our market research, despite the amount of available ELNs there are a minority that are available as free/open source platform independent entities that scientists can use on any device, suggesting a gap that could be filled with this type of ELN.

As part of this vision BioSistemika used their ELN survey to create their own ELN, sciNote [ 38 ]. Taking the path towards interoperability, sciNote has been designed in a modular way and released under the Open Source licence (Mozilla Public Licence). Based on the user needs they are developing new add-ons and at the same time they are encouraging the community to develop their own add-ons, similar to the packages concept of R-statistical. In this way every lab will be able to design their own ELN to fit their needs, which will help them manage their project, share research, gather the metadata directly from instruments and connect with existing software and databases.

Southampton University has looked at the features the users want (shown in Table  5 ) and formulated how these could be achieved using an Electronic Notebook Platform as a base. There is a large overlap of features between Electronic Notebooks, ELNs and SLNs and the main features required by an ELN already exist in generic Electronic Notebooking software [ 34 ]. Furthermore, using a cloud based Electronic Notebook platform would combat some of the accessibility issues and facilitate the collaboration requirements of the users, and incorporating Semantic Web technologies would provide an improved (semantic) search (the top priority listed in Fig.  7 ) and allow for metadata/tagging (as requested).

A cloud based ELN

There will always be concerns about IP with regards to using Cloud based services. The University of Southampton’s Lab Practice study elicited that users with industry sponsors were less likely to use Cloud software. It is thought that once data is ‘in the cloud’ users are no longer in control [ 13 ], and that like with any electronic service there is the potential for data breaches [ 45 ] however many precautions are taken. However this concern certainly isn’t restricted to electronic data. Some of the biologists from the University of Southampton’s Lab Practice Study said that they didn’t consider their work to be safe at conferences as people may take photographs of their posters and steal their ideas, and some of the chemists were aware that previous members of their research group had been ‘scooped’ which resulted in tightened security measures across the group. Despite this, cloud computing is advantageous in that it can provide large volumes of storage and computing power that are accessible from any location [ 13 , 45 ], and it’s worth noting that only 18.9% of respondents in the iLabber Pilot Project Survey thought that ‘Better protection of IP’ was ‘Very important’, ranking significantly below Improved search and secure automatic backup of data, both of which lend themselves greatly to our proposed methods.

Proposed features/design

When investigating the features our users want, we realised that approximately 40% of these features are already implemented within cloud based electronic notebooking software, and the rest of the features are either domain specific or could be achieved using semantic web technologies. Figure  8 shows these desired features elicited from our user studies detailed in Table  5 , which are supported by previous ELN research work [ 4 , 18 , 22 , 34 , 37 , 42 , 46 ].

The desired features that have been elicited from the different user studies. Categorised by whether they are features already included in a cloud based notebook, and then whether they fall into the category of an ELN domain specific feature or a semantic feature

We believe that this approach and the subsequent ELN environment that will be developed can mitigate the current barriers and concerns, these are detailed in Table  6 .

Therefore we propose that building a semantic ELN on top of an existing cloud infrastructure or platform would allow us to make use of these pre-existing features, provide a solid notebook base aligned with software scientists already use, and would also help combat the current adoption barriers. The ability to adapt documents and control input provided by a platform such as Google Docs enables much of the functionality needed for an ELN (e.g. in Fig.  9 ).

An example of adding domain specific features to a pre-existing cloud notebook tool

Conclusions and future work

Our user studies have made one thing very clear, we cannot currently hope to fully replace the paper lab notebook. Until we have the technology where a screen can be written on as accurately and easily as paper; and labs have cheap, durable and easily replaceable tech to use instead of paper, it will always prevail for some tasks. We also need to stop thinking of ELNs as direct replacements for paper lab notebooks that are only useful during experiments in the lab, and consider them in the wider context of the whole experiment process. Therefore we need to build a system that works with paper, and formulate a new digital practice for scientists to use in their current lab environment.

Despite some scientists preferring paper notebooks, they still frequently use technology in their work. Many store data electronically, and use note-taking software such as Word and Evernote to write up their notes, Excel to handle their figures and graphs, and some use speciality software for specific tasks. The cloud is also widely used to backup work and make it available across different locations. Therefore we need to start considering ELNs that can work in this context, and to work out how we can re-use existing successful software to create a better ELN platform.

We propose that we need an ELN environment that can serve as an interface between paper lab notebooks and the electronic documents that scientists create; that is interoperable and utilises Semantic web and cloud technologies. It would fulfil all of the software needs described in “ What do users want ” section and provide a centralised location for the scientists to store their notes. Whilst the ideal long term goal is that adoption of an ELN alongside extensive laboratory automation removes any need for paper, realistically current technology is such that it is desirable that ELN solutions work alongside paper for the foreseeable future. We believe that ELNS will significantly improve reproducibility of scientific experiments, contribute to the data traceability and data annotation and enable scientists to collaborate and share results in an intuitive manner. The wider adoption of ELNs will facilitate interoperability which will ultimately change the ways scientists perform experiments and manage their data. There’s a great potential for future work in these areas, as an ELN that follows our vision has yet to be created, and as hardware and technology as a whole advances, we will be able to support even more of the experimental process digitally.

Abbreviations

Dial-a-Molecule

electronic lab notebook

electronic lab notebooks

intellectual property

resource description framework

semantic lab notebooks

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Authors’ contributions

SK carried out Study C and Study D. CW carried out Study F and was involved with Study E alongside RW who designed and originated the survey. JE, KK and MH carried out Studies A and B. KZ/BioSistemika designed the surveys, did survey analysis and developed a concept of sciNote ELN together with MH. SK, CW and JE all contributed to writing the manuscript. NG and JGF helped draft and revise the manuscript, participated in the design of the research, and the analysis of the results. All authors read and approved the final manuscript.

Author informations

SK is a final year iPh.D. Student in Web Science at the University of Southampton. Her primary research focus is Semantic Web technologies, and she is looking at bringing the modern power of the web to chemical research. She has a First Class M.Eng. Degree in Computer Science and worked as a software developer before starting her Ph.D. CW has recently completed a Ph.D. with Southampton University investigating note-taking behavior of scientists in the lab and the design of tools to help them capture and make use of their experiment information. Before undertaking research at Southampton, she worked at IBM UK Laboratories as a software engineer specializing in software usability and information architecture. NG is an associate Professor in Computer Science at the University of Southampton. His primary research interests are in the Semantic Web, hypertext, and distributed information systems. RW is a Professor of Organic Chemistry at the University of Southampton. He originated and leads the ‘Dial-a-Molecule’ Grand Challenge ( www.dial-a-molecule.org ), which has the 20–40 years aim of making the synthesis of new molecules as quick and easy as it currently is to order a commercial compound. He is interested in total synthesis, flow chemistry, molecular electronics, and cheminformatics. JGF is a Professor of Physical Chemistry at the University of Southampton. His interests span experimental laser spectroscopy and imaging, though chemical informatics and modelling, to the wider area e-science and digital economy. JE has a Ph.D. in Microbiology and Biotechnology. She always follows the latest trends in the Life sciences and believes that great software will be a crucial tool for wet lab or dry lab scientists in the near future. KZ has a Ph.D. in Genetics. He has created several successful companies and he strongly believes that platforms that are able to connect with your instruments and other software seamlessly will help in creating digital laboratories of the future. MH has a Ph.D. in Gene expression technologies. Based on his own experience, he has dedicated his career to developing new software products for researchers. KK has a Ph.D. in Virology. She has a special interest in laboratory management improvement and automation which would enable researchers dedicate more time to their research and innovation and leave tedious routine laboratory tasks to smart software and instruments.

Acknowledgements

We would like to thank all of the people who took part in the different user studies.

Competing interests

BioSistemika’s ELN Webinar Survey and ELN Survey were done as a part of the ELN market research before they started with the development of sciNote Open Source electronic lab notebook. The results of BioSistemika’s market research complement nicely with the data gathered by the University of Southampton. They highlight the current state of the ELN market and show in which direction existing and new ELN solutions should go in order to meet the expectations of the users. JGF is involved with the LabTrove ELN project ( www.labtrove.org ).

Ethical approval and consent to participate

Specific ethical approval was obtained for Study 4 (the most recently conducted study). This study was approved by the University of Southampton’s Ethics Committee for the Faculty of Physical Sciences and Engineering. Focus groups—ethics application ERGO/FPSE/18246. Participant observations—ethics application ERGO/FPSE/18448.

Availability of data and materials

The datasets supporting the conclusions of this article will be available in the Pure repository for the University of Southampton, doi: 10.5258/SOTON/405190 . The datasets supporting the conclusions of this article are included within the article (and its Additional file 1 ).

This work was supported by the Web Science Centre for Doctoral Training at the University of Southampton, funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under Grant No. EP/G036926/1. This work was also supported by the following groups Digital Economy IT as a Utility Network + under Grant No. EP/K003569/1, the South East Regional e-Research Consortium under Grant No. EP/F05811X/1, and PLATFORM: End-to-End pipeline for chemical information: from the laboratory to literature and back again, under Grant No. EP/C008863/1. The Dial-a-Molecule work was also supported by the following Grants: EP/H034447/1 and EP/K004840/1. BioSistemika’s ELN Survey and Webinar were financed by BioSistemika LLC as a part of their ELN market research.

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Additional file 1. A file describing how to access the focus groups and lab observations transcripts from Study D—University of Southampton Lab Practice Study (Focus Groups & Lab Observations).

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Kanza, S., Willoughby, C., Gibbins, N. et al. Electronic lab notebooks: can they replace paper?. J Cheminform 9 , 31 (2017). https://doi.org/10.1186/s13321-017-0221-3

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• Interpret and translate research findings with community members.

A crucial step in the process is discussing the findings with community members and reflecting on any necessary changes. This allows the knowledge to be integrated into the community and encourages members to take ownership of the knowledge and recommended strategies based on public health research.

Types of Community-Based Participatory Research

As a research process based on community connections and researcher involvement, CBPR can be implemented in many different ways. Below are three examples of CBPR models to inform researchers about strategies available to them as they work in communities.

Broad-Based Coalition

The broad-based coalition model connects both informal and formal grassroots organizations to focus on a broad base of community involvement. Unlike other models, which focus on specific issues or specific community groups, a broad-based coalition can help researchers identify the most pressing public health needs and grassroots recommendations for improving community health.

Area-Based Collaboration

Another option for researchers is to focus on a well-established group or organization in the heart of a community. By focusing on this core, researchers can conduct a needs assessment and explore solutions with knowledgeable community members in ways that can be more direct and efficient than a broad-based coalition.

Single-Theme Collaboration

Researchers can also focus on the community collaboration aspect of CBPR by identifying a particular issue or theme. Whether a local environmental concern or a specific health disparity, this single-theme approach helps keep research questions, solutions, and feedback focused.

Benefits of CBPR in Public Health

The strength of community-based participatory research comes from its multilevel approach, combining the community, group, and individual levels. When researchers connect with community knowledge, the result can be one or more of the benefits for public health listed below.

Creating Equity in Research Participation

Many research processes bring top-down decisions to a community based on external research. While these methods may identify effective solutions to health disparities, they can lack community involvement and empowerment. CBPR promotes equity in the solutions and throughout the research process. The findings can create more culturally tailored recommendations by allowing community members to participate in the research process.

Promoting Sustainable Public Health Programs

Equitable research participation can also lead to sustainable programs. Public health recommendations that allow community ownership can last longer and encourage greater community involvement.

Advancing Research on Health Disparities

What causes health disparities in a particular community, and how can a more equitable health model be established? CBPR offers alternative research processes to explore these and other questions related to health equity in a community.

Exploring Culturally Tailored Interventions

For research findings to be most effectively communicated and applied, they must be tailored to that community. When researchers outside of the community connect with community members, they can form a partnership that explores effective ways to apply findings in culturally appropriate ways.

Discover More About CBPR in Public Health

Community-based participatory research can be a highly effective tool for researchers in public health. At Tulane University, you can learn from faculty members how to promote health equity and inclusion within the local community and beyond. Reach out to learn more about Tulane’s Online Master of Public Health (MPH) in Community Health Sciences program to find the next step in your public health career.

Recommended Readings:

How Do Viruses Mutate, and What Is the Role of Epidemiology?

Black Maternal Health in the U.S.

Community Health Promotion in Rural Areas

Agency for Healthcare Research and Quality, AHRQ Activities Using Community-Based Participatory Research to Address Health Care Disparities

American Journal of Public Health, “Community-Based Participatory Research Contributions to Intervention Research: The Intersection of Science and Practice to Improve Health Equity”

Implementation Science , “Community-Based Participatory Research and Integrated Knowledge Translation: Advancing the Co-Creation of Knowledge”

National Institute on Minority Health and Health Disparities, Community-Based Participatory Research Program (CBPR)

The Detroit Community-Academic Urban Research Center, What Is CBPR?

Request Information

Get important details about Tulane's Online MHA, MPH, MSPH, and DrPH programs, such as admission requirements, your financial aid options, and how to apply.

• heart health

Why Heart Disease Research Still Favors Men

Published in partnership with The Fuller Project , a nonprofit newsroom dedicated to the coverage of women’s issues around the world.

Katherine Fitzgerald had just arrived at the party. Before she could even get a drink, she threw up and broke out in a sweat. “I was dizzy. I couldn’t breathe. I had heart pain,” Fitzgerald says.

She knew she was having a heart attack.

What she didn’t know then was that the heart attack could have been prevented. Fitzgerald, a health-conscious, exercise-loving lawyer, should have been taking statin drugs to stop the buildup of plaque in her arteries that caused the heart attack and two others that followed.

Fitzgerald’s case illustrates a dangerous gap in medical care between men and women. While they are equally likely to suffer heart attacks, women are more likely to die from theirs. It’s one of the many symptoms of the medical system’s neglect of women .

Life-saving statins, like so many other medications, have been developed based on clinical trials that primarily recruited men. As a result, many women like Fitzgerald don’t receive prescriptions for the drugs that could help them the most, says Dr. Laxmi Mehta, director of Preventative Cardiology and Women’s Cardiovascular Health at The Ohio State University.

“There were a lot of trials. But women weren’t included as much,” says Mehta, who serves on the American Heart Association’s Research Goes Red Science Advisory Group. When women need treatment for heart conditions, she says, “we are assuming we are providing the best care based on data from men.”

Read More : What It Means if You Have Borderline High Cholesterol—And What to Do About It

More than 30 years ago, Congress directed the National Institutes of Health to include as many women as men in clinical trials. But while some progress has been made, equity remains elusive. And that’s dangerous for women. “Since 2000, women in the United States have reported total adverse events from approved medicines 52% more frequently than men, and serious or fatal events 36% more frequently,” research firm McKinsey & Company said in a report released in January .

Now, the Biden administration is taking a run at it.

Last year, the administration established a White House Initiative on Women’s Health Research and, in February, it announced it would be dedicating $100 million to the newly formed Advanced Research Projects Agency for Health (ARPA-H) to spearhead efforts to increase early stage research focusing on women.

“For far too long, scientific and biomedical research excluded women and undervalued the study of women’s health. The resulting research gaps mean that we know far too little about women’s health across women’s lifespans, and those gaps are even more prominent for women of color, older women, and women with disabilities,” Biden said in an executive order signed in March.

Heart disease should be a bright spot in this black hole of medical research. It was the recognition in the 1980s that heart disease was killing women at similar rates to men that kickstarted passage of the 1993 law requiring equity in clinical trials. The American Heart Association has spent decades funding research and leading awareness campaigns about women’s risks.

But gaps persist, says Dr. Martha Gulati, president of the American Society for Preventive Cardiology and a cardiologist at Cedars-Sinai Hospital in Los Angeles. “We don’t get represented in trials,” Gulati told a seminar sponsored by the Society for Women’s Health Research in February.

Read More : Why Are So Many Young People Getting Cancer?

One example: Dr. Safi Khan of West Virginia University and colleagues reviewed 60 trials of cholesterol-lowering drugs conducted between 1990 and 2018. Not even a third of the people enrolled—28.5%—were women, they reported in JAMA Network Open in 2020. The trials’ findings likely did not accurately represent the public as a whole, they say.

“Medical research is several steps behind on women and heart disease, and that is a major contributor to ongoing ignorance about the problem on the part of both the public and a range of medical professionals,” says Dr. Harmony Reynolds, a cardiologist at NYU Langone Health. “Everywhere along the way, there is different treatment for women, and there is some bias there.”

Statins have been widely described as wonder drugs , lowering the risk of major heart events such as heart attack or stroke by about 25% . Women are less likely than men to be offered these drugs . And when they do take them, women are more likely to stop using them because of perceived side effects. But no major study digs into the actual rate of side effects among females, or what might lie behind such differences.

Further studies might uncover additional benefits, says Dr. JoAnn Manson, professor of medicine at Harvard Medical School and Brigham and Women’s Hospital. There are hints that statins might lower a woman’s risk of dying from cancer , including ovarian cancer.

Failure of recognition

Fitzgerald was 60, had higher-than-optimal blood pressure, unhealthy cholesterol levels, and a family history of heart disease, says Reynolds, Fitzgerald’s new cardiologist. “Katherine had multiple risk factors. Many of my patients are told their blood pressure and cholesterol are ‘borderline’ when really they should be treated,” she says.

Doctors often blame women for failing to recognize their own heart disease symptoms, but the evidence shows medical professionals miss them, too. 

The symptoms of heart attacks in men are widely known: crushing chest pain, a telling sensation in the left arm, or sudden collapse. Women, on the other hand, often feel nausea, jaw pain, or lightheadedness,

Fitzgerald did recognize her symptoms. At the party where she suffered her first heart attack, she begged for an ambulance. But other guests, including a physician friend, said they didn’t think she needed medical attention.

When paramedics finally arrived, they, too, dismissed her fears and diagnosed a panic attack. They sent her home. “If I had been a man, there is no way the paramedic wouldn’t have taken me to the hospital and I wouldn’t be in the mess I am now,” Fitzgerald says.

Fitzgerald waited two days to visit an emergency room. By then, some of her heart muscle had died. She received two stents to hold open clogged arteries, but suffered two more heart attacks in the following months. She now stays out of the courtroom and sticks to less-stressful desk work.

“I take care of all these young women with heart attacks and I hear so many stories about people saying they were ignored,” says Reynolds.

Waiting for attention

The problem is not just anecdotal. Reynolds and colleagues studied the problem by looking at more than 29 million emergency room visits by people under 55 reporting chest pain. 

“In that study we show young women coming in with chest pains and they are waiting longer to be seen,” Reynolds says. “The women are waiting too long and women of color were waiting even longer. So we know there is some subtle bias there.”

Read More : What the Science Says About the Health Benefits of Vitamins and Supplements

Doctors can use risk calculators to try to forecast a patient’s future likelihood of heart disease and treat accordingly. But Dr. Stephanie Faubion, medical director of the Menopause Society , says they do not work well for women.

“That is because we are still using those that were developed and made for men,” says Faubion, who is also director of the Mayo Clinic Center for Women’s Health in Jacksonville, Florida.

Women have many specific heart risks. They have smaller coronary arteries , thinner heart walls, and suffer more heart damage from diabetes. Pregnancy can raise risks in various ways. Autoimmune diseases such as rheumatoid arthritis also add heart disease risks, and women are far more likely than men to have these conditions. 

Women who start menstruation early, or who reach menopause early, have higher heart disease rates. Birth control pills can raise the risk for blood clots, strokes, and heart attacks.

Perhaps the most recent instance of women being left out of heart disease research can be seen in the trials of highly popular diabetes drugs such as semaglutide, sold under the brand names Ozempic and Wegovy .

The drugs cause dramatic weight loss, which made researchers wonder if they might lower heart disease rates, too. They do, according to several studies , and the U.S. Food and Drug Administration now approves their use to prevent heart disease.

But none of the weight-loss trials, published in prestigious medical journals such as the New England Journal of Medicine and the Journal of the American Medical Association , break out separate data on men and women. And while the weight-loss studies did include far more women than men, many of the follow-on heart disease trials did not.

“They report the sex. They report ‘we have this many men, this many women,’” says Faubion. “They didn’t disaggregate the data on sex so they don’t know if it works better, the same, or worse in women than it did in men.”

Dr. Robert Kushner, a professor of medicine at Northwestern University who led some of the weight-loss studies, says he was surprised at the discrepancy between the enrollment of women in the obesity trials of semaglutide—in which about three-quarters of volunteers were women—and in the heart disease trials, in which women represented fewer than 28% of participants.

He says researchers recruited people already being treated for heart disease. “Predominantly, the ones who are getting care and being seen around the world were men,” Kushner says.

Kushner says he has yet to analyze results in his trial of semaglutide and weight loss by sex.

Missing out on breakthroughs

Harvard Medical School’s Manson has been sounding the alarm on discrepancies in medical research for decades.

“Raising more questions is what leads to the major breakthroughs,” she says.

Yet she has been mostly ignored, even though she helped lead the largest-ever study looking specifically at women’s health—the Women’s Health Initiative, which involved more than 160,000 women over 15 years.

The study was initially designed to see if hormone therapy in women past menopause could reduce their rising rates of heart disease and breast cancer. It also later looked for evidence of effects on bone strength, other cancers, dementia and quality of life.

The first results were startling. The hormone therapy used in the trial raised the risk of breast cancer and failed to reduce heart disease.

Read More : Menopause Is Finally Going Mainstream

“Many clinicians stopped prescribing hormone therapy altogether. Many women tossed their pills and patches,” Manson says. When the trial started, an estimated 40% of menopausal women used hormone therapy. Now, Manson estimates, only about 4% do.

The study has since been shown to have been flawed. The average age of the women in the study was 63—well past menopause. And the hormone therapy used was a high-dose hormone distilled from horse estrogens.

Later studies have indicated that lower doses and different formulations such as patches, given to women as they start menopause, may be much less harmful while reducing hot flashes, sleep loss and other symptoms. “These formulations don’t go to the liver and should be safer,” Manson says. There’s also tantalizing evidence they may lower the risk of heart disease.

Meanwhile, the lack of data means that many women who would benefit from hormone therapy are not getting it, says Faubion. 

Back in 1993, it took the considerable efforts of Dr. Bernadine Healy, the first female director of the NIH, to persuade Congress to directly fund medical research on women and heart disease.

“They are just not going to do that again. It’s too expensive,” says Faubion.

Biden asked Congress for $12 billion to improve research planning and to set up a network of research centers to focus on women’s health. And NIH has encouraged requests for money to study women in particular.

But when Congress passed a last-minute spending bill in March, it kept health funding flat . The Republican-led House did not address Biden's request or allocate any cash for additional research into women's health.

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A pocket guide to electronic laboratory notebooks in the academic life sciences

Ulrich dirnagl.

1 Department of Experimental Neurology and Center for Stroke Research Berlin (CSB), Charité Universitätsmedizin Berlin, Berlin, 10117, Germany

2 German Center for Neurodegenerative Diseases, Berlin, 10117, Germany

3 German Center for Cardiovascular Diseases (DZHK), Berlin, 10117, Germany

4 Excellence Cluster NeuroCure, Berlin, 10117, Germany

5 Berlin Institute of Health, Berlin, 10117, Germany

Ingo Przesdzing

UD prepared the first draft of the manuscript. UD and IP designed the survey, which was conducted and analyzed by IP. UD and IP were involved in the revision of the draft manuscript and have agreed to the final content.

Associated Data

Peer review summary.

Every professional doing active research in the life sciences is required to keep a laboratory notebook. However, while science has changed dramatically over the last centuries, laboratory notebooks have remained essentially unchanged since pre-modern science. We argue that the implementation of electronic laboratory notebooks (eLN) in academic research is overdue, and we provide researchers and their institutions with the background and practical knowledge to select and initiate the implementation of an eLN in their laboratories. In addition, we present data from surveying biomedical researchers and technicians regarding which hypothetical features and functionalities they hope to see implemented in an eLN, and which ones they regard as less important. We also present data on acceptance and satisfaction of those who have recently switched from paper laboratory notebook to an eLN.  We thus provide answers to the following questions: What does an electronic laboratory notebook afford a biomedical researcher, what does it require, and how should one go about implementing it?

Introduction

In this article we argue that the implementation of electronic laboratory notebooks (eLN) in academic research is overdue, and we provide researchers and their institutions with the background and practical knowledge to select and initiate the establishment of an eLN in their laboratories. Based on our own extensive experience in moving from laboratory notebooks (LN) to eLN, we try to answer the following questions: What does it afford you, what does it require, and how should you go about implementing it?

Every professional doing active research in the life sciences is required to keep a LN. This is imperative for group leaders, post-docs, students, as well as technicians. LNs are the core element of record keeping, data management, and initial analysis and interpretation of results in research. Details of its specifications, storage, etc. are laid down in institutional, national, as well as international codes of conduct for research integrity and good laboratory practice 1 . These codes usually stipulate sequentially numbered and bound pages, use of permanent ink, storage for a minimum of 10 years; they often require that entries be signed and dated by a witness. The use of LN has a long history, which parallels the development of modern science since the Renaissance. However, while science has changed dramatically over the last centuries, LNs have remained essentially unchanged since pre-modern science 2 ( Figure 1 ). This is highly remarkable for a number of reasons. For one, most of the data gathered is no longer analog, but digital. Gone are the days when researchers read numbers from instrument for transfer to the LN. Today there is a complex mixture of (often repetitive) protocols, digital images, links to large data files, etc. In addition, the recent realization that there is a ‘reproducibility’ crisis in the life sciences, and an increasing number of high profile cases of research misconduct and subsequent retraction of publications has put record keeping in the spotlight. It is therefore not surprising that the pharmaceutical industry, with its superior resources and regulatory pressures (e.g. Code of Federal Regulations Title 21 3 ) has moved to eLNs. Many researchers and institutions in academia now realize that the implementation of eLNs is overdue. However, only a tiny fraction of university laboratories are using them. Major hurdles for implementation appear to include ignorance about practical issues, perceived scarcity of available options, and a lack of resources. As part of the implementation of an ISO 9001-certified quality management system, our department (Department of Experimental Neurology) has recently moved from LNs to an eLN. At this department with approximately 100 students, researchers, technicians we carry out multi-professional academic research in preclinical biomedicine with such standard approaches and techniques as in vivo and and in vitro modeling of disease, cell biology, molecular biology, biochemistry, as well as imaging (from multi-photon microscopy to magnetic resonance imaging). We therefore believe that our experience is applicable to a wide range of research operations in the life sciences.

A : Page from the laboratory notebook of the father of experimental electrophysiology, Emil Dubois-Raymond (7 November 1818 – 26 December 1896). [Staatsbibliothek Berlin, 1865–1868, XIII, 22. VII. 65–9. VI. 68, reproduced with permission]. B : Pages from a contemporary laboratory notebook from the laboratory of the authors.

Why you will switch to an eLN

We believe that the question is not whether eLNs will become standard or even required in the academic life sciences, but when. The advantages of an eLN are as obvious as the disadvantages of the conventional LN 4 . Most of the original data obtained in laboratories worldwide is already digital and can easily be integrated or linked to the eLN. eLNs foster collaboration, as protocols, data and concepts can be shared within or between groups. Entries can be time stamped, changes are recorded, versions controlled. Protocols used frequently can simply be integrated as templates. Project progress and eLN use can be easily monitored by group or project leaders. eLNs are searchable, archiving is simple, and copies are easily made for the institution and the individual researcher, many of whom will leave the institution at some point. These features include just a few of the functionalities which are already available in eLNs and are completely absent in a LN. Future eLNs will provide further benefits, including direct data links to standard laboratory hardware through an application programming interface (API) and automatic alerts when instruments are malfunctioning or not calibrated, or direct links to open data repositories (such as Figshare or Dryad). LNs, on the other hand, tend to get lost, must stay within the institution, which in turn has to keep track of them and is charged with keeping reliable records of LNs, storing them and enabling access for at least 10 years.

Selecting an eLN

If you are contemplating a switch to eLNs, you first need to decide what you expect from it, and match this with your resources (see also below). Table 1 summarizes the principal features of three different categories of eLNs. The simplest form (‘do-it-yourself’ – DIY - type) is a word processor or note-taking system 5 . It is cheap, easy to use, and has many of the features a conventional LN; its major drawback is its lack of any kind of audit trail or certification. Such DIY-eLNs thus do not even conform to the standards of classical LNs, and therefore are not a serious option for their replacement. Dedicated eLNs have many additional features. Importantly most commercially available eLNs are compliant with the Code of Federal Regulations Title 21 (CFR Title 21) of the US Food and Drug Administration (FDA). CFR Title 21 part 11 sets rigorous specifications for electronic record keeping, including electronic signatures and version control. CFR Title 21 is a must if protection of intellectual property or use of the records for regulatory processes (such as FDA) is a factor 6 . Dedicated eLNs also allow complex rights management within institutes and workgroups, and can integrate original data. High-end systems include all the features of an eLN, but also function as laboratory information management systems (LIMS), facilitating inventory management or direct link to laboratory equipment (such as microscopes, sequencers, etc.). Not surprisingly, while DIY-eLNs are very easy to use, the increasing functionality of dedicated eLNs and eLNs integrated into LIMS comes at the price of growing complexity in its use. This might be a particular concern when non-academic personnel need to work with the eLN. Another issue is language – the user menus and help functions of practically all commercially available eLNs are in English; only a few allow the user to switch to other languages. Again, this may, in combination with a complex functionality, pose problems, and hamper the acceptance of the eLN in non-academic and less tech-savy work environments. Several articles have reviewed and compared various eLNs 7 .

Note that ease of use and the availability as well as power of features of eLNs are inversely related.

Abbreviations: API, Application programming interface; 21 CFR 11, code of federal regulations title 21 part 11; LIMS, Laboratory Information Management System. * Indicates that this feature is available in some systems of this category only.

What you need to get started

For the individual researcher planning to move to an eLN very few requirements exist. Several open source eLNs are freely available (e.g. 8 ). Some companies offer basic eLN versions for a limited number of users and only as cloud based solutions free of charge (e.g. Labfolder), but for full feature commercial solutions license fees will apply. If a whole workgroup, department, or institution wants to set up an eLN, it gets more complicated. First and foremost, one needs to make sure that the eLN will be accepted by the users. This is not trivial, as many researchers and technicians have been socialized using a conventional LN. They may not be familiar with the many additional useful features provided by an eLN, and are confronted with the challenge and potential distraction of learning how to use a new tool.

To investigate the willingness of staff in a large academic research institution to switch from paper LN to ELN, and to find out what they expect from an ELN, we have surveyed students, technicians, and scientists. We also queried the staff of a research department in the process of switching from LN to ELN. Across professions and career stages the preference was for an intuitive and easy to use interface, a better integration of digital content, use of templates, and the ability to structure notes better. Features considered much less relevant were annotation and freehand drawing, the ability to use mobile devices, or saving time. On an individual level, user expectations and ratings did not substantially change when they progressed from eLN-naive to eLN. More than 70% of those not using an eLN were eager to start working with one, while almost 82% of those already using an eLN now prefer it over the paper version. For details and full results of the surveys, see Supplementary materials 1–4 . Although our survey revealed that users of paper laboratory notebooks had a strong motivation for switching to an eLN and a high satisfaction rate for eLNs among those using it, we recommend not to enforce the switch to an eLN. Rather, it should be offered as an opportunity to those who are interested, and scale up its implementation as more group members join in. Sceptics will be able to observe its use, and will very likely want to become users within a short time period.

Another important issue relates to information technology (IT). For workgroups and institutes, the program and data storage will need to run on a server, with local clients, or through a browser interface. Obviously, every lab member using the eLN needs access to a computer. Most eLNs can run on mobile devices and can therefore be taken to the bench or site of experiment even if no computer is present at the site. This requires a wireless connection (WLAN) covering the laboratory or institution. Data can be linked to the eLN by assigning the file and drive name where it is stored. More conveniently, clickable links can directly connect to the data, but this requires that the eLN is physically integrated into the data management structure of the institution. All of this means that in most cases the selection and installation of an eLN from a group level on needs the support of the institutional IT department. They will also be responsible for upgrades, backups, etc. For large-scale installations within whole departments and institutions, training and support contracts need to be considered. Table 2 gives an overview of the requirements.

Note that prerequisites vary with type of eLN and number of users (see Table 1 ).

Obstacles and pitfalls

At present no standard exists for eLNs, and the market is still evolving, so that none of the software makers can guarantee support and further development of their eLN beyond a couple of years. As of now there are no standards for data annotation and integration, therefore migration between different platforms may be difficult or even impossible. In a worst-case scenario (eLN provider goes out of business, no further development or support), the existing eLNs must be saved to pdf-format (including time stamps, addresses linking to stored data etc.), or to html/xml formats, as this will help retain some of the functionality. Such a feature should be mandatory, and is provided by most eLNs. This would essentially mean reverting to a conventional lab book, but the pdf would still provide extra features such as searchability and ease of copying and storage. For eLNs evolving on an open source platform, termination of support of proprietary software is not an issue. However, development or bug fixing of open source software may also be terminated. In addition, such systems may have less support than commercial systems, and support be restricted to tech-savy users or environments with programming capabilities. Another issue relates to the complexity and wealth of functions provided in particular by the high-end eLNs (often part of a LIMS). If using the eLN becomes too complex or restrictive, users may start recording their work outside the eLN. Finally, committing to long-term license fees may be a problem, in particular for individual researchers who may have only fluctuating financial or institutional support.

Conclusion and recommendations

How biomedical scientists take notes and document their work has not changed much over the last 200 years: They write with a pen in a bound, paginated laboratory notebook. The only major modification is that today, printouts or images of results are often attached ( Figure 1 ). Data, however, is meanwhile almost exclusively digital, and digital technology provides a plethora of tools for recording, annotating, sharing, processing, and storing all the information that cumulatively drives progress in the life sciences. Scientists use computers for everything and everywhere, privately and professionally, except for documenting their research, experiments, and laboratory procedures. Several reasons may account for the astounding survival of the paper LN. It is a robust and easy to handle ‘technology’, which has been handed down over generations of scientists. At the same time, the emerging eLN market has been dominated by expensive solutions for research and development in large life science companies. Standards for data annotation, exchange or export between different eLN platforms have not yet evolved. There is a hesitation to commit to a specific product that may no longer be supported when the company goes out of business. The inertia of scientists to abandon their cheap and time-honored record keeping system, despite its numerous disadvantages and despite the obvious advantages of electronic solutions, has hampered the development of mature and affordable products for the academic sector. This has led to a vicious circle: Lack of interest on the part of scientists has frustrated the development of dedicated software. Over the last few years, the situation has slowly but substantially changed, and mature and affordable (or even free) eLNs are available. Scientists who overcome their reservation and exchange their LN for an eLN regularly become avid supporters after a short learning period, praising functionalities like group collaboration, use of templates, embedding of data, scheduling, access to the eLN from any computer world-wide, etc. In addition, group leaders and organizations value enhanced documentation and version control, improved supervision of record keeping, as well as backup and archiving of records.

Box 1. Recommendations

Ensure willingness of staff to use the novel record keeping technology (ease of use, language of menus).

Clearly define the functionalities that you expect from the eLN. Do not get lost in the almost limitless portfolio of potential functionalities. Remember: You probably just want to replace your paper LN, and not install a new word processor, graphics editor, or groupware system.

Although you may not be aware of it now, you probably want a product which complies to legal requirements like 21CFR11, as well as good scientific practice (full audit trial, restriction on deletion of data, timestamps, ability to freeze and sign entries, among others).

Unless you will be the only user, flexible and hierarchical rights management is very important.

The system needs to be able to tag, filter and search entries. Organization of data in eLN in projects, subprojects, milestones, etc. is a must.

Make sure that all entries, imported data, and links can be exported to a generic format (pdf, zip, xlm, etc.) for backup and reporting as well as allowing a bailout in case the maker of the software stops development, or your funds to pay for licence fees run dry.

Enlist the support of your IT department at an early stage (selection of particular eLN).

Beware of hidden costs (hardware like server, backup devices; on-site support and user training, if applicable etc.)

Besides serving all the obvious functions of a paper LN, eLNs facilitate scientists’ workflow (quick creation and editing of experiments) and collaboration (sharing and reusing information, independent of location, harmonization of work practices). They allow the integration of data, images, files, etc. and can already read data directly from instruments. They eliminate the need to transcribe or cut-paste data from one system to another, thereby avoiding transcription errors. Templates and boilerplate text modules prevent tedious rewriting. eLNs facilitate the retrieval of data or information over long periods of time, improve data quality (legibility), and allow the detailed reconstruction of individual experiments. They facilitate the mobility of researchers. Last, but not least, eLNs promote compliance with Guidelines on Good Laboratory Practice (GLP) and Good Scientific practice, and help intellectual property protection by their compliance to 21CFR11. We have no doubt that eLNs will become standard in most life science laboratories in the near future.

Acknowledgments

We thank Dr. Niko Offenhauser and Sebastian Major for their help in setting up the eLN.

[version 1; referees: 4 approved]

Funding Statement

Supported by the German Research Foundation (Exc 257), the Federal Ministry of Education and Research (01 EO 08 01), the Herman and Lilly Schilling Foundation, and intramural funding by the Berlin Institute of Health (all to UD).

Supplementary material

Supplementary material 1.

Results of an anonymous survey at the Department of Experimental Neurology.

Supplementary material 2.

Results of an anonymous survey at Charité Universitätsmedizin Berlin.

Supplementary material 3.

Printout of the questions of the survey at the Department of Experimental Neurology.

Supplementary material 4.

Printout of the questions of the survey at Charité Universitätsmedizin Berlin.

Referee response for version 1

1 MTA Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary

In this article the authors present their views on laboratory record keeping procedures and argue that electronic laboratory notebooks (eLN) would be most suitable to support modern scientific research replacing the traditional, paper based version. One major strength of this paper is the personal experience of the authors with eLN from their own department. As it comes clear from the text, researchers are often reluctant to switch to eLN despite their advantages over the old fashioned laboratory notebooks. The authors arguments for using eLN are well taken: original data generated in laboratories are mostly digital, storage of large files, protocols or images requires electronic data management anyway, whilst data sharing or searching large databases, protocols becomes much easier if using eLN. In addition, eLN run on portable devices and entries can be time stamped and changes recorded, which is required by the scientific community and regulatory pressures. Whilst the authors’ preference is obvious for eLN, they are cautious with their recommendations and clearly outline the potential pitfalls of eLN as well.

 In my opinion, the following issues might deserve a short explanation:

• What is the level of detail researchers should record in eLN? In the case of standard LN, complex data files and large figures  mostly remain electronic, whilst some figures, tables, analysis results and conclusions are incorporated into the LN. However, software running on dedicated machines (flow cytometers, imaging devices, etc) generate large files that are only partially extracted in text, PDF or other forms due to their incompatibility with common word processing tools. Should eLN users attempt to incorporate some of these data into eLN considering limitations in storage space, or such files should remain stored and analysed as earlier?
• How safe do the authors feel keeping most of their research data in an organized manner in eLN using cloud-based systems or large databases that are available from external servers or institutions? Are there measures large research units should consider before switching to eLN to support the protection of intellectual property or their patent applications?

Overall, I find this article very useful and informative. I suspect that in the near future most research labs will not be able to avoid using eLN due to a number of reasons explained clearly in the paper. Practical information from experienced users will greatly support the willingness of researchers to start using eLN and this could also contribute to dealing with reproducibility issues in the future.

I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Barry W. McColl

1 The Roslin Institute , Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, UK

The authors present a persuasive argument for replacing conventional lab notebooks with electronic versions (eLNs). Crucially, they outline the current drawbacks of conventional lab books in the current age and why there is a need to consider alternatives. One comment would be that the authors could perhaps have indicated if alternatives other than the systems mentioned in the article exist?

The benefits of adopting eLNs described seem clear and comprehensive but importantly the potential weak points are also considered to give some balance. A similarly balanced tone is evident in discussion of the willingness of researchers to adopt eLNs and their reaction to doing so. Thus while the article is clearly presenting the authors' favoured opinion they also reflect on alternative views.

As commented on by the authors, adopting an electronic system particularly in larger departments or organisations will need the appropriate IT infrastructure and support. While the authors surveyed opinions from researchers it might also have been informative to gauge and record opinion from IT professionals as to some of the practical issues of particular relevance to lab personnel.

Overall, this article is very well structured and presents a helpful and informative perspective and primer on this emerging issue.

Christoph Kleinschnitz

1 Department of Neurology, University of Würzburg, Würzburg, Germany

Eva Geuß

2 University Hospital Würzburg, Würzburg, Germany

Dirnagl and Przesdzing provide a highly innovative and comprehensive summary for the use of electronic laboratory notebooks (eLNs) in life science research. They highlight advantages of eLNs over traditional hand written LNs, comment on possible obstacles and inform readers about distinct features/specification of different types of eLN systems, e.g. complex rights management, integration of original data, direct link to laboratory equipment etc. In addition, they offer a step-by-step instruction of how to establish eLN systems in everyday laboratory practice based on the successful implementation of eLNs in their own institution. From an internal survey of their staff (scientist, students, technicians) they deduce which features of eLN systems were considered most desirable and which ones were regarded less relevant.

In total, the article is highly informative for any researcher working in the life science field and is a very well suited guide for everybody who plans to switch from LN to eLN.

We have read this submission. We believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Thomas A. Kent

1 Department of Neurology, Stroke Outcomes Laboratory, Baylor College of Medicine, Houston, TX, USA

This is a valuable description of the author’s experience with electronic laboratory notebook implementation within their department. There can be much value in educating the broader scientific community with respect to both their experience, the experience of those they surveyed and the available options for the researcher.

The manuscript can be improved through better definition of terms and procedures related to the eLN with which the average laboratory scientist may not be familiar. Some examples follow:

The title is appropriate and the abstract is a good summary.

Introduction:

The authors department pursued ISO 9001-certified laboratory quality management system. Could they expound on what this means, why they chose to pursue it and what it entails? What kind of resources did they devote to this and what did they hope to gain in return?

“Why you will switch to an eLN”

While suitably provocative, perhaps reword the section title as “Why you will switch to an eLN” seems to put the answer before the research is presented. Perhaps a more neutral statement might not appear that the conclusion has been pre-judged.

In this section, the authors list several advantages to an eLN, including for example, that original data can be “easily integrated or linked to the eLN”. I assumed this meant a direct link to the eLN from the laboratory equipment, but later in this paragraph, the authors describe such a direct link as in the future. Could they then explain how data is easily integrated in the eLN? This question may be a major one for those used to using written notebooks where printouts are often physically attached. And if the data is not directly loaded into the eLN, how is it searchable? Are they scanning data through OCL or some other method? Some details would help the reader visualize how this system might help them.

“What you need to get started”

This is a well written section with a nice summary Table of the different options. If possible, it might be beneficial to discuss costs, perhaps within an order of magnitude for the different systems, although not if this is proprietary information. 

With respect to the surveys, while the heat maps are useful, it is not easy to follow whether there is a pattern to the different features. Perhaps an analysis using the highest/lowest scores graphically might be more helpful.  It does not appear that any pitfalls were included in the questions. In the article, the authors later discuss possibility of loss of technical support, updates and possibility that the sponsor may go out of business. It is not clear that the survey included that possibility and how the respondents might have answered.  I would consider this a modest weakness, but would like to hear some comment from the authors.

“Obstacles and pitfalls”

This is an excellent section that is most useful to the potential purchaser of a system and what are the minimum requirements that should be available should the support be terminated.

This is an important section. Are there alternatives? For example, upfront costs and uncertain future of any wholly integrated platform are reasons that some labs have set up their own cloud based systems, although without all the functionality of an integrated system and without FDA certification, but the data can be easily referenced to physical lab books and as such provide some of the advantages of a whole integrated system.

I have a question for the authors: Do they think that “electronic laboratory notebook manager” may become a new, sought after, position analogous to the “network manager” that is needed even though there are multiple commercial products available and standards widely accepted? Perhaps the pharma experience on how to manage a large, integrated eNL might be helpful here if the authors are aware of them, or perhaps they could describe how at the department whether the management of the eLN is the responsibility of specific individuals.

“Conclusions and recommendations”

This is a good summary of the authors’ thoughts.  Perhaps a little harsh with the term “inertia of scientists”, there may be many reasons that scientists have not embraced eLN in their work, particularly if it is a small laboratory or one strapped for resources other than inertia.

The authors only once mention the important issue of need for restrictions on alteration of data, and only in the Box 1.  Perhaps some mention of this issue would be helpful in the text as well.

The final list of recommendations is an excellent primer for exploring the possibility of an eLN.

I commend the authors for their efforts to increase the visibility of such systems and providing their experience and perspective on this topic.