Category Archives: General

Behind the Scenes: Insights from User Testing the new DMP Tool Designs

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TL;DR

  • The rebuild of the technology behind the DMP Tool offered a chance to refresh the user interface
  • We conducted 12 user testing sessions to have real users walk through wireframes of our new tool designs to offer feedback and find issues
  • People liked the new designs but had a lot of small areas of confusion around some aspects like sharing and visibility settings
  • We made tons of small changes based on feedback and continue to make updates for better usability
  • Fill out this short form to have the option to join future feedback sessions

Why we needed new designs

As mentioned in our last blog post, the team behind the DMP Tool has been working on a rebuild of the application to improve usability, add new features, and provide additional machine-actionable features.  To provide all of this advanced functionality, we needed to do a pretty big overhaul of the technology behind the DMP Tool, and it was a good time to give the design a more modern upgrade as well, adding new functionality while hopefully making existing features easier to use.

A graphic showing a Machine-Actionable DMP connected to nodes that say Compliance, Integrity, Guidance, Tracking, and Scalability

How we made the first drafts and tested them

Over the past few months, we’ve worked closely with a team of designers to create interactive wireframes—prototype mockups that allow us to test potential updates to the user interface without fully developing them. These wireframes are crucial for gathering feedback from real users early, ensuring that our vision for a better tool meets their expectations.  While a lot of thought and planning went into these initial designs, we wanted to make sure people were finding the new site as easy and intuitive as possible, while still offering new, more intricate features.

To do this, we recruited three groups of people, 12 total, who work on different parts of the tool to test out these designs:

  • 5 researchers, who would be writing DMPs in the tool
  • 4 organizational administrators, who would be adding guidance to template in the tool
  • 3 members of the editorial board or funder representatives, who would be creating templates in the tool

We recruited volunteers from the pilot project members, from our editorial board, from social media, and from asking those we recruited to share the invitation with others. We conducted virtual interviews with each person individually, where we let them explore the wireframe for their section, gave them tasks to complete (e.g., “Share this DMP with someone else”), and asked questions about their experience.  For the most part we let people walk through the wireframes as if they were using it for real, thinking out loud about what they were experiencing and expecting.

What we found from testing

It was illuminating for the team to see live user reactions from these sessions, and watch them use this new tool we’re excited to continue work on. 

We loved to hear users say how excited they were for a particular new feature or how much they liked a new page style.  At times it could be disheartening, watching a user not find something that we thought was accessible, but those findings are even more important because it means we have an area to improve.  We made a report about the findings after each group of users and worked with the designers on how to address the pain points.  Sometimes the solution was straightforward, while other times we wrestled with different options for weeks after testing.

Overall, we found that people liked the new designs and layout and could get through most tasks successfully.  They appreciated the more modern layout and additional options. But there were many areas that the testers identified as confusing or unclear.  There are specific examples, with before-and-after screenshots, in the Appendix.  Some of the top changes made revolved around the following areas:

  • Decreasing some text in areas that felt overwhelming, moving less important information to other pages or collapsed by default
  • Adding some text to areas that were particularly unclear, such as what selecting “Tags” for a template question would do
  • Connecting pages if people consistently went somewhere else, such as adding a link to sharing settings on the Project Members page since that’s where people looked for it first
  • Moving some features to not show until they’re needed, such as having Visibility settings as an option in the publishing step and not the drafting step
  • Clarifying language throughout when things were unclear, such as distinguishing whether “Question Requirements” was about what the plan writer was required to write when creating their DMP or whether that was about the template creator marking whether a question is required or had display logic
  • Having additional preview options when creating a template or adding guidance to understand what a question or section would look like to a user writing a DMP
  • Making certain buttons more prominent if they were the primary action on a page, like downloading a completed DMP that originally was hard to find

Even though the main structure worked well for people, these small issues would have added up to a lot more confusion and obstacles for users if we hadn’t identified them before releasing.  

Wrapping up and moving forward

The whole team learned a ton from these sessions, and we’re grateful to all the participants who signed up and gave their time to help us improve the tool.  This sort of testing was invaluable to find areas to improve – we made dozens, if not hundreds, of small and large changes to the wireframes based on this testing, and we hope it’s now much better than it was originally. We’re still working on updates as we build our designs for more areas of the site, but feel better now about our core functionality.

If you’d like to be invited to participate in surveys, interviews, or other feedback opportunities like this for the DMP Tool, please fill out this brief form here: Feedback Panel Sign-Up. For anyone that signed up but wasn’t selected for this round, we may reach out in the future! 

We loved seeing how excited people are about this update, and we can’t wait to share more.  The most common question we get is – when is it releasing!  That’s going to be quite some time, and we don’t have more to share yet, as we’re still too early in the development process.  But stay tuned here for more updates as we do! 

We want to thank Chan Zuckerberg Initiative (CZI) for their generous support for rearchitecting our platform. We wouldn’t be able to make all of these helpful updates along with our back-end transformations without it.

Appendix: Specific Examples

Important note: The “updated wireframes” shown here are not final designs. We have not yet completed a design pass for things like fonts, colors, spacing, and accessibility; this is just a quick functionality prototype so we could get early feedback. Even the functionality shown here may change as we develop based on additional feedback, technical challenges, or other issues identified. Additionally, these wireframes are mockups and do not have real data in them, so there may be inconsistent or incorrect info in affiliations, templates, etc; we were focused on the overall user interface in testing, not specific content.

Sharing settings

For those who want some more details and specific examples, here are a few of the top areas of confusion we found:

There was sometimes confusion in how to share a plan with others, and what the distinction is between a Project collaborator (e.g., another researcher on the grant who may not be involved in the DMP) and a DMP collaborator (e.g., a peer who is giving feedback on writing the DMP but not on the project).  The current live tool has both “Project Contributors” and “DMP Collaborators” on the same page which we thought contributed to this confusion, so we wanted to separate those who can edit the DMP into a separate Sharing section.  However, testers had a hard time finding these sharing settings, and often went to the Collaborators page to grant DMP access.  So, we added a link to these settings where people were looking (the new section in the green box), and added more detail to the sharing page about whether they were invited or had access due to being a collaborator, changed some language within this like “Collaborator” to “Project Member,” with the option to change access.


Current tool:

On the current tool, these two types of collaborators are on one page.

Initial wireframes:

The Collaborators page in the initial wireframes, which was part of the overall project details and was not related to sharing access to the DMP itself.
A separate Sharing page on the plan itself had sharing settings, and was completely distinct from Collaborators.

Updated wireframes:

This page was renamed to Project Members for clarity, with a link to the page for sharing access to the DMP since so many people looked for it here.
This page was updated to give more information and control on invitations, and to make clear if people were added on because of an invite or because they were a project collaborator.

Card layout

Many parts of the tool used a new, more modern card format for displaying lists of items to choose from.  This allowed us to show more information than in a list, and adapt to smaller screens. However, we saw in some areas that people had trouble scanning these cards to find what they were looking for, like a plan or template, when they expected to search in alphabetical order.

For example, picking a template in the first draft used a boxier card format. People found it harder to find the template they were looking for, since they wanted to quickly scan the titles vertically.  So we changed it to a different format that should be easier to scan, even if it doesn’t show as many on one page.  Note we also now have the option to pick a template other than from your funder, a common request in the current tool.  

Current tool:

Currently, selecting your funder brings up a list of templates with no other information, and you can’t select a different template.

Initial wireframe:

This format allows more information if we want to add details that might help people pick the right template.

Updated wireframe:

This update still allows us to show more information, but the vertical layout means a person’s eyes can move in the same spot down the list to scan titles more easily if they know what they want.

Flow through the tool

People appreciated that they could move around more freely in the new design, as compared to the more linear format of the current tool. However, that also occasionally made people feel “lost” as to where they were in the process of writing a DMP. Especially as there is now a “Project” level above each plan to help support when people have multiple DMPs for the same research project.  So we added more guidance, breadcrumbs, and navigation while still allowing the freedom of movement throughout the process.

For example, while writing a plan, users will now be able to see the other sections available and understand where they are in the Project tree.  We also reduced some of the text on screen due to people feeling overwhelmed with information, putting some best practices behind links that people can visit if they wish to, and moved the Sample Answer people were most interested in to above the text box for better visibility.

Current tool:

The current tool has more distinct phases from writing a plan to publishing. In this view, a person is answering a single question and then would move on to the next.

Initial wireframe:

In our first draft, people clicked into each question rather than having all one one expandable page. But people weren’t always sure where they were in the process or how to get back.

Updated wireframe:

We added the navigation seen on the left and top here to allow people to see what else is in the plan and more easily get to other sections or the Project. We are also still working on how to reduce how much text is on the screen at once, for example by minimizing the guidance, but this is not final. We also moved the sample text above the question and removed the answer library for now.

Layout changes

In addition, there were tons of small changes throughout, changing layouts, wordings, and ordering of options in response to areas of confusion.  Some places we scaled back a bit of functionality since the number of new options were overwhelming, while other places we added a bit more that people needed.

In the first draft of the wireframes, the visibility settings of the plan were on the main overview page of the plan.  This was concerning to users since they were still drafting at this stage, and even if they may want it public once they published it, the setting in this location made it seem like it was public now.  Instead we added a status and setting on the overview page, but the visibility setting does come up until a person gets to the Publish step, somewhat like the current tool that has those options later than in the plan writing stage.

Current tool:

Currently, setting visibility is later in the “Finalize” stage.

Initial wireframe:

In the first draft, this visibility settings were on the main plan page, which made people think it was public already as opposed to that it would be public once published.

Updated wireframe:

The updated main page, with many changes based on feedback, including visibility as a status on the right, which isn’t set until it is published, and more control over changing project details per plan.
Now, visibility is set only once a person goes to publish their DMP.

We made similar change to creating a template, moving the visibility settings to be selected in the publishing stage instead of being in a Template Options menu people didn’t always see right away.  They expected to set that visibility at the time they published it, so that’s where we moved that option to be, consistent with how the plan creation flow works.

Announcing the DMP Tool Rebuild

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TL;DR

  • We’re starting work on an ambitious project rebuilding the DMP Tool application
  • The rebuilt tool, coming hopefully some time next year, will use machine-actionable structures for the whole DMP and have many new features
  • The current site will remain as it is until the new version is released, though we’re limiting work on it to resolving critical issues
  • Sign up for our newsletter to hear occasional updates about this work!

History of the DMP Tool

Over the past 13 years, the DMP Tool has grown from a grassroots tool beginning at 8 institutions to one that serves thousands of universities across multiple continents. We’ve had a few big milestones in that time, such as adding the ability to register a DMP-ID and publish a DMP publicly, and creating the admin interface to allow universities to provide custom guidance on templates. The tool started in response to new requirements from U.S. funders for data management plans (DMPs; also known as data management and sharing plans–DMSPs), and our growth follows the research and library communities’ needs in this area.

Adding Machine-Actionable Functionality

Now, it’s time for our next big milestone in the DMP Tool: fully machine-actionable data management and sharing plans (maDMSPs).  In 2022, the U.S. CHIPS and Science Act was signed into law, requiring DMPs submitted to the National Science Foundation (NSF) to be “machine-readable.”  Machine-readable, or actionable, means that information is structured in a way that enables automatic connections and transformations without the need for manual intervention.  

A screenshot excerpt from the CHIPS and Science Act of 2022 which reads "(b) DATA MANAGEMENT PLANS.— (1)IN GENERAL.—The Director shall require that every proposal for funding for research include a machine-readable data management plan that includes a description of how the awardee will archive and preserve public access to data, software, and code developed as part of the proposed project."
Excerpt from the CHIPS & Science Act, referring to NSF-funded research

On the current DMP Tool, some parts of the DMP have been made machine-actionable already, such as the DMP-ID and metadata.  When you go to a registered DMP’s landing page, like this public plan for example, you see structure information like title and contributors pulled from a database.  Other systems can work with that information through our public API, allowing for integrations with various research applications.

Now, we want to make all parts of the DMP – such as the narrative responses to the questions describing the plan – machine-actionable, and open up more tooling to work with structured maDMSPs, as was outlined in a Dear Colleague letter in 2019.

There are many benefits to maDMSPs, such as:

  • Having persistent identifiers that allow tracking of data publications and connections to other PIDs, like ORCIDs and ROR and DOIs
  • Creating opportunities for sharing information about DMPs between different campus units
  • Allowing integrations with research systems, like electronic lab notebooks, that can help researchers use DMPs in existing workflows
  • Establishing links to research outputs, like published datasets, that came from a DMP, to help link work and track compliance with the statements in a DMP

Rebuilding the DMP Tool

To implement these major changes, we realized a significant overhaul of the current DMP Tool was needed to accommodate these new features and underlying structural changes.  For years, the DMP Tool rebuild has been a regular discussion point; we’ve long recognized its areas for improvement and regularly fielded requests for specific features.  However, our team of two had limited ability to implement many of our, and the community’s, grand ideas. 

Fortunately, we were able to obtain funding from an NSF EAGER grant that allowed us to explore a rebuild of the application, which would allow us to develop these features of the new tool and bring about these needed changes.

Our official rebuild work kicked off in April 2024 with a week-long workshop with our new team of consultants led by Paula Reeves from Reeves Branding and Zach Antony from Cazinc Digital. During that week, we dove into every aspect of the current application, mapping out existing features and brainstorming how to incorporate new ones. This included the machine-actionable data and formatting required for interoperability and the structured metadata needed to fuel the creation of machine-actionable data management plans. We reviewed the existing architecture, explored user personas, and redesigned workflows to facilitate project-centric planning. We also focused on building and customizing templates, adding guidance tools, and ensuring accessibility as we outlined development timelines and workflows for future phases. 

Photograph of seven team members at the in-person rebuild kickoff meeting
The seven team members at the rebuild kickoff meeting

We’re excited to also get in a few top feature requests as well as maDMSP functionality, though we will be rolling them out in stages and cannot get to everything.  Some of the areas we have currently prioritized include:

  • Additional API functionality, such as the ability with unpublished or in-progress DMPs
  • Ability to upload and register existing DMPs
  • Improved account management, such as being able to add secondary emails
  • Increased flexibility in creating templates, such as additional question types and streamlined ability to copy templates
  • Finding and connecting DMPs to published research outputs like datasets
  • Improved notification, comment, and feedback systems

Since the kick-off, the designers have been developing wireframes for the new tool, while we’ve added some new machine actionable elements to the current DMP Tool for testing.  We’ve been working with the Association of Research Libraries (ARL) on a pilot project with 10 institutions, funded by the Institute for Museum and Library Sciences, gathering feedback from their use of the tool and conducting interviews about their efforts developing local integrations. Our first visit was to Northwestern University, which can read more about on ARL’s blog, with more coming soon.

What’s next

To stay focused on delivering this work, and due to the site’s technological constraints, we will be limiting updates to the current application. We’ll prioritize resolving critical issues while taking feature requests as requests for the new site. 

We can’t wait to share more information over time about this project as it develops.  While it’s too early to announce a release date, we’re hopeful it will be sometime before the end of next year.  We recently wrapped up user testing on the wireframes, and will have a blog post coming soon about what we found.  We’ll also be sharing information at upcoming conferences, such as a talk at IDCC25 called “Piloting maDMSPs for Streamlined Research Data Management Workflows.”  Keep an eye on this space, and sign up for our newsletter, to hear occasional updates about this work!

We want to also thank Chan Zuckerberg Initiative (CZI) for their generous support for rearchitecting our platform. The back-end transformations and refactoring activities were funded through their generous support.

Introducing the new DMP Tool Product Manager

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I’m thrilled to introduce Becky Grady, CDL’s new Senior Product Manager for Data Management Planning. Becky will oversee our work on the DMP Tool and machine-actionable DMP projects. She brings a wealth of experience in technical product management to our team, and we’re excited to have her on board! As for me, I’ve transitioned to a new role as the Associate Director of the UC3 department. While I’ll continue working to support the development of the DMP Tool and new maDMP workflows, Becky will now be the lead contact for all DMP-related projects. – Maria Praetzellis

Hello everyone!  My name is Becky Grady, and I’m thrilled to be joining UC3 to work on Data Management planning.

For the past few years I’ve worked as both a UX researcher and a product manager in the tech industry, working on gaming platforms, account systems, and internal tools.  Before that, I received my PhD in Psychological Science at UC Irvine, studying bias in false memory, fake news, and misinformation under advisors Elizabeth Lofuts and Pete Ditto. 

As a former researcher, I know how important open science practices are at every stage of the process.  I’ve published multiple meta-analyses and know firsthand, both as the requestor and the requestee, of the challenges in finding and sharing data and materials from long ago.  I’ve also conducted many studies, from both academia and industry, about meta-science practices such as survey design and replication processes, because I know how important it is to look at how we conduct research and not just what the output is. 

As a product manager, I know how important it is to provide the right tools for people to get done what they need, understanding their needs and goals to make a great experience for them.  My UX research experience helps me work with users to understand their motivations, getting to their core needs to build the product that does what they need.

I can’t wait to bring my industry and academic experiences together to help in this important area and help plan, track, and preserve critical research data.  Making it easy and intuitive to create and update  data management plans, serving the needs of both researchers and institutions, will be core to advancing open science practices.  Excited to work with all of you more!  You can reach me at becky.grady@ucop.edu or connect with me on LinkedIn.

Connecting DMSPs to Research Outputs

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By Brian Riley, California Digital Library (CDL), and Mary O’Brien Uhlmansiek, The Association of Research Libraries (ARL)

In March, the lead developer for the DMP Tool, Brian Riley, attended a workshop on “Scientometrics Using Open Data” offered by the Centre for Science and Technology Studies (CWTS) at Leiden University. Participation in this session allowed us to share the work we are doing as part of the MAP Pilot project funded by the NSF and IMLS, and to collaborate on scientometric analyses using open data sources such as Crossref and DataCite.

The MAP Pilot project involves working with 10 institutions across the US to test connecting machine-actionable data management and sharing plans (maDMSPs) with related research outputs. Using research project metadata and persistent identifiers to query open data sources, it is somewhat easy to find research articles produced by a particular project, but not the datasets, software and other artifacts that are described in a DMSP. We are investigating ways to improve their findability using automation including machine learning/AI.

When maDMSPs are created in the DMP Tool, users can enter useful project metadata to enable queries with other systems. This includes ORCIDs for contributors, funding opportunity identifiers, RORs for affiliations and funders, anticipated project start and end dates, and the planned data repository for storage. The DMP Tool then assigns a DMP ID to the DMSP.

DMSPs are often created years before the research outputs. The DMSPs in the DMP Tool with good metadata are only 2-3 years old, and their DMSP outputs have not yet been published. Therefore, the institutions contributing to our pilot have been asked to find older, funded research projects and their outputs to use as test cases. Using a new feature to upload an existing DMSP, they will enter basic information about the project (i.e., title, PI, grant identifiers) for research funded by 4 major US agencies (NSF, NIH, DOE, and NASA) and for which we have the most developed API integrations. As potential DMSP outputs are identified, the pilot teams will verify their relation to the research.

Identifying related DMSP outputs within the DMP Tool will give data librarians and research/grant management offices insight into the outputs of research projects, academic departments, and the institution. Users can generate reports for compliance checks (was the data shared according to the funder’s policy), grant reporting, and research management activities. This collaborative effort is being further developed with the Centre for Open Knowledge Infrastructure (COKI) and is funded by the Chan Zuckerberg Initiative (CZI), which supports technical work to connect plans to outputs.

With sufficient metadata, how do we find related DMSP outputs? We start by exploring open data sources like Crossref, DataCite, and COKI. For example, we explore DataCite’s GraphQL API to extract DataCite metadata and compare it with DMP Tool projects. We use an algorithm to compare and score each field in the records. Each data source structures its metadata differently, though, so we must transform that metadata into a standardized format. We then weigh or score the confidence level of any matches found. A high confidence level is when grant IDs match, but this is rare currently. Confidence levels improve with additional identifiers like ORCIDs, RORs, and repository IDs.

Some development challenges discussed at the workshop include:

  • US funding agencies lack a standard way of sharing metadata via their APIs and rarely include Grant IDs. Grant IDs are important but not reliable yet for identification purposes.
  • Research/DMSP outputs associated with older projects frequently lack identifiers such as ROR and ORCIDs in their metadata record. 
  • How can we find datasets and software related to published research articles in systems like COKI? Can we use an article’s references to find these artifacts? What other hooks will allow us to identify these related outputs, and how could improved metadata and the usage of identifiers help facilitate making these connections?  

We are exploring adding more data aggregators to combine findings and create a clearer picture of a research project and its outputs. We will also explore methods to identify related works from research article reference sections, like dataset or software references. We are experimenting with ML/AI techniques to determine if a research output might be related to a DMSP.

Findings from the MAP Pilot will be published as reports and best practices for implementing maDMSP workflows at research institutions after the project ends in 2025. If interested in collaborating on this important developmental work, please contact muhlmansiek [at] arl [dot] org for more information.

New Project Director Joins the MAP Pilot Project

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By Mary O’Brien Uhlmansiek, Project Director, The Association of Research Libraries (ARL)

This February, I joined the MAP Pilot team as Project Director, serving in a joint position with The Association of Research Libraries (ARL) and the California Digital Library (CDL). In this role, I will support ten research libraries in our pilot project, exploring ways to advance institutional coordination around machine-actionable data management and sharing plans (maDMSPs). The project will compile resources for research workflow improvements utilizing maDMSPs, such as for tracking compliance with funder data-sharing requirements or to initiate internal research infrastructure requests upon grant award, for example. Our pilot partners will also help drive improvements in the DMP Tool itself, providing valuable software testing and feedback as new interoperability features are developed, and using real-world examples to ensure the application will meet the needs of researchers and stakeholders alike.

Through my experiences serving as a data and repository manager for sensitive health-related information, in managing research software adoption and implementation at a large medical university, and as a facilitator for the adoption of outputs and recommendations at the Research Data Alliance, I can see the potential for the DMP Tool to provide critical research infrastructure for researchers and administrators alike as they navigate new data-sharing requirements from funders. I am excited to work with the project PIs, Cynthia Hudson Vitale and Maria Praetzellis, and the many other dedicated professionals from research library organizations in the open science movement. Projects such as the MAP Pilot are building blocks for the transition to more open science, and I look forward to the dissemination of the teams’ outputs to aid research institutions in adopting and continuing this important work. 

If you would like to learn more about maDMSPs or to get involved in future work in this area, please consider joining a group such as the Active Data Management Plans Interest Group at the Research Data Alliance.

DMP Tool 5.0 Release

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We are excited to share the latest enhancements in the DMP Tool with the 5.0 release. This update marks a shift in our technology, featuring substantial back-end advancements that set the stage for a more robust, efficient, and scalable future. 

Infrastructure Improvements  

At the core of these updates is an overhaul of our infrastructure. The DMPTool’s back-end, built on legacy Rails code, is evolving. We’re transitioning towards a more modern architecture, separating the front-end and back-end operations. This shift involves transforming existing code into API endpoints and developing a React-based front-end. These changes will allow the DMP Tool to effectively generate the structured data required to realize the potential of machine-actionable plans. 

A New Look and Feel

The first thing you’ll notice is an updated DMP Tool homepage. This redesign aims to streamline how users and prospective partners access information about the tool. Recognizing the frequent inquiries we receive about joining the DMP Tool, we’ve focused on making key information about the application more accessible and straightforward.  

Versioning of Registered DMPs

Plan versioning is a key feature for machine-actionable DMPs and one we have received many requests for. Rather than static, quickly outdated documents, effective DMPs track progress by logging critical events from planning to preservation. Regularly revisiting and updating DMPs as research unfolds creates dynamic records that monitor ongoing activities. 

As a first step to exposing updates to DMPs, this release also includes the introduction of versioning for plans with DMP-IDs. This means a new version is created whenever a registered DMP is updated. Changes made within the same hour are combined into a single version. This feature provides a clear history of updates and ensures that you can easily track and reference different iterations of a DMP.

We welcome your input on these latest updates. Please reach out with any comments, questions, or feedback about these changes or the DMP Tool in general.

Institutions Selected to Pilot Development of Scalable Data-Management Infrastructure

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The Association of Research Libraries (ARL) and the California Digital Library (CDL) have selected five institutional teams to pilot the integration or creation of prototypes and possible workflows for machine-actionable data management and sharing plans (maDMSPs). The pilot project will run January–December 2024. This project is funded by an Institute of Museum and Library Services (IMLS) National Leadership Grant. Additional information about the project is on our project webpage.

Machine-actionable data management and sharing plans are structured, machine-readable documents that allow for dynamic reporting on the intentions and outcomes of a research project, enabling streamlined information exchange across relevant parties and systems. These plans go beyond traditional static document-based DMSPs, and contain an inventory of key metadata about a project and its outputs (not just datasets), with a change history that stakeholders can query for information over the lifetime of the research. Implementing maDMSPs can be a key piece of establishing interconnected, automated systems for research data management and compliance.

The maDMSPs pilot institutions will help shape the development of maDMSPs and gain valuable early experience with new approaches to enable more automated and connected research data management. The institutions are:

  • Arizona State University
  • Northwestern University Feinberg School of Medicine
  • Pennsylvania State University
  • University of California, Riverside
  • University of Colorado, Boulder

An additional five institutions have been selected for the maDMSP extended cohort that will engage closely with the pilot cohort.

Call for Institutions to Pilot Development of Scalable Data-Management Infrastructure

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The Association of Research Libraries (ARL) and the California Digital Library (CDL) are seeking four institutional teams to pilot the integration or creation of prototypes and possible workflows for machine-actionable data management and sharing plans (maDMSPs). The pilot project will run January–December 2024. This project is funded by an Institute of Museum and Library Services (IMLS) National Leadership Grant. Additional information about the project is on our project webpage.

Interested organizations should submit their expression of interest here.

Machine-actionable data management and sharing plans are structured, machine-readable documents that allow for dynamic reporting on the intentions and outcomes of a research project, enabling streamlined information exchange across relevant parties and systems. These plans go beyond traditional static document-based DMSPs, and contain an inventory of key metadata about a project and its outputs (not just datasets), with a change history that stakeholders can query for information over the lifetime of the research. Implementing maDMSPs can be a key piece of establishing interconnected, automated systems for research data management and compliance.

This pilot provides an exciting opportunity for selected institutions to help shape the development of maDMSPs and gain valuable early experience with new approaches to enable more automated and connected research data management.

By agreeing to be part of this pilot program, institutions will:

  • Define a set of success measures for institutional pilot projects of maDMSPs at their organization.
  • Gather a sample set of data management plans from funded research projects to use as test cases for connecting plans with associated datasets and other research outputs.
  • Provide engaged feedback on the maDMSP features and uses at their organization.
  • Conduct ongoing work to meet the locally defined success measures.
  • Attend and actively participate in project meetings every other month.
  • Participate in project communication, outreach, and engagement (such as conference panels, webinars, reports and articles, etc.).
  • Coordinate and manage one program team site visit.

Pilot projects should include a team of three to five people representing institutional stakeholders who will work together to test or prototype an institutional solution to support public access to research data leveraging the maDMSP. Teams may include representatives from the offices of several institutional stakeholders, such as the research office, library, information technology, institutional review board (IRB), high-performance computing units, and/or faculty.

Examples of possible pilot projects include, but are not limited to:

  • Modeling notification workflows that could be automated through maDMSPs to alert stakeholders to key events over the data life cycle. Example use cases include alerts around sensitive data, managing big data, enabling data transfer, and linking datasets to published outputs.
  • Building prototype integrations connecting maDMSPs with existing research information management systems (RIMS) or researcher profile systems. For example, automatically updating and exchanging key metadata between maDMSPs and other research systems.
  • Engaging academic or administrative departments to test the utility of maDMPs for their research workflows and data management needs. Departmental testing would provide feedback to inform the optimization of maDMSP systems.
  • Demonstrating and improving communication workflows between key campus units involved in research data management using maDMSPs as a connecting platform. Example stakeholders include the library, research office, IT/security, IRB, research computing, and high-performance computing units.

Pilot institutions will:

  • Gain early access to new maDMSP features and functionality.
  • Influence technical development and workflow processes of the maDMSP platform.
  • Be reimbursed for up to $6,000 per institution to attend conferences or workshops to communicate pilot project goals or outcomes.

The ARL/CDL project team will produce all required reporting to IMLS; there are no federal grant reporting requirements for pilot partners.

We are seeking a range of institutions that are diverse in size, research activity, and level of development of services and infrastructure for research data management and sharing. Even if your institution has just begun planning for research data management and sharing, we invite you to apply.

Applications will remain open until Friday, November 10, 2023, and we anticipate notifying applicants by the end of November.

If you are interested in learning more, you are invited to register to attend an optional, informational webinar on Thursday, November 2, at 10:00 a.m. PDT/1:00 p.m. EDT.

Please direct any questions to Cynthia Hudson Vitale cvitale@arl.org or Maria Praetzellis maria.praetzellis@ucop.edu.

Association of Research Libraries and California Digital Library Receive Grant to Advance Data Management and Sharing

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Cross-posted from ARL News and written by Cynthia Hudson-Vitale | cvitale@arl.org | August 4, 2023

image by Markus Spiske on Unsplash

The Association of Research Libraries (ARL) and the California Digital Library (CDL) have received a $668,048 National Leadership Grant from the US Institute of Museum and Library Services (IMLS) to assist institutions in managing and sharing federally funded research data. This project will build a machine-actionable data-management plan (maDMP) tool by enhancing and developing new DMPTool features utilizing persistent identifiers (PIDs). CDL and ARL will work together to further strengthen institutional capacity for tracking research outputs by piloting the institutional integration of maDMPs across an academic campus and building community across institutions for maDMPs.

The promise of the maDMP is to be a vehicle for reporting on the intentions and outcomes of a research project that enables information exchange across relevant stakeholders and systems. maDMPs contain an inventory of key information about a project and its outputs with a change history that stakeholders can query for updated information about the project over its lifetime. By incorporating open persistent identifiers (PIDs) into DMPs and leveraging all DMP metadata for interoperability across infrastructures, institutions—and specifically libraries—will be better equipped to track and manage their institutional research data products.

CDL and ARL have collaborated before on advancing PIDs and maDMPs, including joint efforts on the 2019 National Science Foundation (NSF) grant Implementing Effective Data Practices that led to stakeholder recommendations for collaborative research support. The new IMLS project builds on this prior work by piloting maDMP workflows in the DMPTool, gathering feedback from partner institutions, and iterating on maDMP features to put those recommendations into practice at scale.

“We are thrilled to work with ARL on this timely project to advance open science by utilizing machine-actionable DMPs,” said Günter Waibel, associate vice provost and executive director, California Digital Library. “Facilitating the sharing and tracking of research data furthers our goals of supporting open scholarship and leveraging innovative technology to situate research data within an open knowledge graph of scholarly activity. We look forward to collaborating with ARL and partner institutions to build new tools and workflows to strengthen the research data ecosystem.”

“ARL is eager to engage its members and the broader research library community in testing new DMPTool features to improve cross-institution communications around open-science practices and research integrity,” said Mary Lee Kennedy, executive director, Association of Research Libraries.

In addition to developing DMPTool workflows to link research outputs and track relationships, this project will also work with four institutions to pilot the new features and improve capabilities. The call for institutional teams will be distributed in the next few months. Stay tuned for information on community calls and other project updates.

About the Association of Research Libraries

The Association of Research Libraries (ARL) is a nonprofit organization of research libraries in Canada and the US whose vision is to create a trusted, equitable, and inclusive research and learning ecosystem and prepare library leaders to advance this work in strategic partnership with member libraries and other organizations worldwide. ARL’s mission is to empower and advocate for research libraries and archives to shape, influence, and implement institutional, national, and international policy. ARL develops the next generation of leaders and enables strategic cooperation among partner institutions to benefit scholarship and society. ARL is on the web at ARL.org.

About the California Digital Library

The University of California (UC) founded the CDL in 1997 to take advantage of emerging technologies that were transforming the way digital information was being published and accessed. Since then, in collaboration with the UC libraries and other partners, we assembled one of the world’s largest digital research libraries and changed the ways that faculty, students, and researchers discover and access information. In partnership with the UC libraries, the CDL has continually broken new ground by developing systems linking our users to the vast print and online collections within UC and beyond. Building on the foundations of the Melvyl Catalog, we developed one of the largest online library catalogs in the country. We saved the university millions of dollars by facilitating the co-investment and sharing of materials and services used by libraries across the UC system. We work in partnership with campuses to bring the treasures of our libraries, museums, and cultural heritage organizations to the world. And we continue to explore how services such as digital curation, scholarly publishing, archiving, and preservation support research throughout the information life cycle. Serving the UC libraries is a vital component of our mission. Our unique position within the university allows us to provide the infrastructure and support commonly needed by the campus libraries, freeing them to focus their resources on the needs of their users. Looking ahead, the CDL will continue to use innovative technology to connect content and communities in ways that enhance teaching, learning, and research. CDL is on the web at cdlib.org.

About the Institute of Museum and Library Services

The Institute of Museum and Library Services is the primary source of federal support for the nation’s libraries and museums. We advance, support, and empower America’s museums, libraries, and related organizations through grantmaking, research, and policy development. IMLS envisions a nation where individuals and communities have access to museums and libraries to learn from and be inspired by the trusted information, ideas, and stories they contain about our diverse natural and cultural heritage. To learn more, visit www.imls.gov and follow us on Facebook and Twitter.

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Supporting the FDP NIH Data Management and Sharing Pilot Project

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The FDP (Federal Demonstration Partnership) NIH Data Management and Sharing Pilot Project aims to simplify the process of creating an NIH DMSP. The Pilot is testing the effectiveness and usability of two distinct templates.

The goal of the FDP pilot project is not only to test the two templates but also to gather data from both the researcher’s perspective and that of the NIH program. Feedback from these two perspectives will be instrumental in refining the templates based on the pilot data.

DMPTool supports researchers in fulfilling data management requirements efficiently and effectively. In light of this, we have developed templates based on the two FDP pilot templates, Alpha and Bravo. These templates follow the same design principles as the two FDP pilot templates, making it easier for researchers to navigate and comply with the requirements of their respective projects.

DMPTool administrators can customize the FDP templates like other DMPTool templates, including adding custom guidance and example answers and customization of the Research Outputs tab. 

We are proud to support the FDP NIH Pilot Project and aid researchers in creating comprehensive NIH DMSPs that foster open science. As always, feel free to contact us with any questions or feedback.