Community Pilot — Jennifer Stubbs × Spring–Fall 2026

[jt14den]

Community Pilot — Jennifer Stubbs × Spring–Fall 2026

A community instructor is interested in piloting this lesson.

Instructor: Jennifer AW Stubbs, Bradley University / CARLI
Contact: jastubbs@bradley.edu | @jas58
Timing: Spring or Summer 2026 at Bradley University (grants/research admin offices); possibly October 2026 at CARLI / Illinois Library Association conference
Audience: Either librarians via CARLI, or non-library grant support and research administration staff at Bradley University
Source issue: ucla-imls-open-sci/ucla-imls-open-sci.github.io#64

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Context

Jennifer is a librarian at Bradley University who is also a member of the LCGC. She's interested in piloting DMP 101 in two possible contexts:

1. CARLI / ILA — a traditional library audience in Illinois
2. Bradley University offices — grants administration and research support staff who work with DMPs but are not librarians

The second context is a particularly useful test: it would show whether the lesson holds up with an audience that already deals with DMPs operationally rather than learning about them for the first time.

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Checklist

• Instructor connected with lesson author(s)
• Pre-pilot briefing held
• Observer identified (optional — LCGC can provide one)
• Workshop held — Date: Tuesday 19th May 10am-1pm Central_
• Post-pilot feedback filed as issues on this repo or as comments on this issue
• pilots: entry added to lesson YAML

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Questions? Comment here and @jt14den.

[jas58]

Announced in CARLI (Illinois list serv) and LC-Midwest.

[jt14den]

Intro email going out today connecting Hannah Sutherland (@sutherlandhk, UCLA Library) with Jennifer and the lesson authors — see #20 for Hannah's pilot interest. Hannah may reach out about joining the May 19 session as an observer or helper.

[jas58]

Question for this iteration, and for designers: Is this NSF update worth adding?
New NSF notice, NSF 26-202, to use their DMP template/webform
https://www.nsf.gov/policies/document/pappg24-1-supplement-2 (published January 22, 2026)
Required as of April 27, 2026.
Description of changes and fields: https://www.research.gov/research-web/content/DMSP

There are 8 subsections, which may already be covered in the episode exploring freely available samples.

1. Data or Research Product Category General Information
2. Access Policies and Limitations
3. Data Standards and Metadata
4. Data or Research Product Provenance
5. Public Archiving
6. Timeline for Public Accessibility
7. Data Availability
8. Accountability

[jas58]

Adding my CodiMD template for observation notes

[jas58]

Try to mention NIH update and share their new form (mostly y/n).

[jas58]

Rehearsal Time stamps:

1. 25 min
2. 20-25 min
3. 15-20 min
4. 15 min
5. 5 min
   Total: 100 minutes

Real time stamps:

1. 45 minutes (after launch, opening); extensive discussion based on questions raised by attendee (1), our grants officer.
2. 20 minutes (raced through), at end distributed discipline related DMP from DMPTool, in print; I had highlighted better and worse phrases. The officer had to leave for another meeting by the end of the 2nd hour.
   3.-5. did not present (some was covered in the first 45 minutes based in the questions.)

[jas58]

Grants officer offered to connect me with their account to request a demo account of research.gov, where the new DMP webform is.

This webform is probably unstable. I could only view the original "training" document through the wayback machine: . I believe the screenshots lack alt-text and may be why it came down so fast. But the demo (and live site when I was added to a current grant to help the PI with the new DMSP webform) do not match the images. The drop-down menus are empty of well-known tools, file formats, or metadata standards. Those are fields that inform what menus populate later fields; so a real problem.

My observer reported I sound natural and the material flowed sensibly.

Collecting all the jargon on the glossary page was requested (FAIR, SPARC, ICPSR which are explained in their first sentences throughout). Also, options to explain,

1. translating metadata to citation styles: APA, Chicago, or MLA are different ways to label the same information. Sure a human can translate one to another, but a machine might confused title, author, journal unless those are clearly labeled (metadata tags).
2. formats or filetypes are like dates: Month, day, year or YYYYMMDD or the confusion of single digits between military and civilian or different cultures. This kind of documentation and clarity are the goal of the DMP.
3. listing one metadata system for each major discipline. E.g.: Engineers use IEEE, ANSI, ISO, building codes. Anything with maps or locations: GIS, decimal degrees, lat-long: how is that saved? Which software or device or website did you use to collect it?

To be less US centric: citing Australia, UK, or European DMP initiatives. I recall several links to international colleges for metadata, and often to some of these tools, but their country codes are lost in the URLs.
Charles Stuart's RDMP guide
Nanyang Technological University in Singapore's guide
Or adding a label to DCC's links as UK specific and OpenAIRE's as EU-endorsed

One suggestion: hand out the DMPs from DMPTool at the beginning rather than as an exercise later. To illustrate items as introduced in part 1. Then one exercise is circle or make of list of every term you are uncertain of. This might become an agenda for meeting with your local data services office, IT, or librarian.

[jas58]

Here's what I saw in the DMSP demo (and live)
Links to PAPPG
and Supplement 2 --this feels a bit circular, but that's what they show there.
and NSF 24-589

Options to declare:
None is an option, if true, must explain with clear justification instead.

• no data
• no samples
• no physical collection
• no software
• no curricular materials
• no other materials will be produced

PIs need prior approval to request and state in advance these exceptions:
privileged/confidential info only in aggregate or form that protects privacy
When to request exception to share results/data:

• to safeguard privacy/rights of individual/subjects
• validity of results
• integrity of collections
• accommodate legitimate interests of investigators

As for the main webform: only 4 "Data or Research product categories" allowed, each as 8 sections.
Open New
1/ Data or Research Product Category General Information
--"add new" only option, title, description
"Select the broad category that best fits the data or research product. If the appropriate category is not available, select 'Add New' (last option) and provide a title and short description for the custom entry. The selection will also determine the options displayed in the 'Data Standards and Metadata' and 'Public Archiving' sections."
Title = mostly commonly used term in your field

2/ Access policies and limitations
---select up to 6 or check "n/a" box
-data sovereignty
----Any of a set of considerations related to ownership of data by independent sovereign groups, such as Native American tribes, and any related data use agreements.
-dual use concerns
----Any of a set of considerations related to the potential misuse of shared data for purposes that might harm individual human rights or the national interest.
-human data protections
----Any of a set of considerations related to the protection of human data sources and respect for their individual rights, including but not limited to breaches of their privacy, exposure to harm or bias, and data use agreements such as consent forms.
-legal
----Any of a set of considerations arising from preexisting agreements, laws, or regulations that may limit data sharing, including but not limited to: international treaties, commercial data use agreements, protected health information (HIPAA).
-national competitiveness
----Any of a set of considerations related to the potential of shared data to harm US security or economic interests, such as technologies that if shared would diminish US competitiveness.
-natural resource protection
----Any of a set of considerations related to the potential of shared data (e.g., geolocation) to harm critical natural resources, including but not limited to endangered species, natural wonders, and critical resources.
-resource limitation
----Any of a set of practical considerations related to the resources needed to enable full data sharing, including but not limited to computing costs, necessary personnel, and the lack of available repositories.
"Select up to six exceptions or limitations explaining why data or research products in this category will not be publicly shared. Please ensure any applicable Directorate- or solicitation-specific guidance regarding appropriate exceptions. Selections may include legal, privacy, ethical, technical, confidentiality, security, or intellectual property concerns, as well as restrictions from data use agreements or IRB requirements. If your exception isn't listed in the dropdown, select 'Add New' (last option) to enter one custom option.

Note: Unless 'Not Applicable' is selected, an explanation and justification of the concern must be provided below."

3/ Data Standards and Metadata
broken: nothing to select from, just type and pray (based on first field, but that has no requirement) circular argument of brokenness

4/Data or Research Product Provenance
-Existing data resource
----Any data that will be drawn from an existing large-scale data resource (e.g., census data, climate databases). Please specify the data resource in the provided text field.
-existing dataset
----Any data that has already been collected and will be reused in the current project, generally existing shared data.
-new data collection
----Any data that is expected to be newly generated by the proposed project.

5/public archiving
same circular break at metadata stds

6/timeline for public accessibility

• N/A box or
• At time of collection
• at time of publication
• < 6 months after pub
• <1 year post pub
• <2 years after collection
• by end of award
• add new

7/data availability (longest range possible)

• N/A checkbox or
• <2 years

• = 2 years

• 3 years

• 5 years

• 10 years

• indefinitely
• add new

8/ accountability
names from PIs listed in award already (or co-PIs)
add via manage personnel and subaward orgs or link via non-lead proposals

[jas58]

This might be a useful link to add to further reading. It might belong in a specific section on supporting researchers's challenge
Cornell on how to create a good readme file. While talking with a PI, he was aware there would be a readme file at the end of the grant, but did not yet know what it would list.

[jas58]

Another resource to consider: Teaching research data management / edited by Julia Bauder. ISBN: 9780838937976
Ch 5: Data Literacy on Demand by Ginny Boehme, Kristin Adams, and Matt Benzig of Miami U offers two useful graphics or groupings of categories to scaffold the content in the lesson. These might be sub lists or (p)reviews for PIs who don't understand the value of the lesson. These could also inform librarians crafting advertisements or letters to recruit participants.

p. 78 Twelve core competencies for data information literacy from Carson et al 2011
(In no specific order, the image is a 3x4 grid)

• Intro to data formats
• quality assurance
• data preservation
• metadata
• discovery and acquisition (or licensing) of data
• data curation and reuse
• data management and organization
• cultures of practice
• data conversion and interoperability
• data ethics
• data analysis
• data visualization

p. 84, General Outline of Data Mgmt and Organization module

1. Why DM is important
   a. Whys and Hows of Good data
   b. Best practices
2. Tidy data concepts
   a. guidelines for effective data organization
   b. relational databases
3. Working with Messy Data
   a. identifying problems with sample dataset
   b. reorganizing messy data
4. Quality assurance & control
   a. before, during, and after data collection
   b. correcting sample datasets

[jt14den]

@dmorl @mihertz @quetzal1234: Jennifer Stubbs left thorough feedback above from the May 19 DMP 101 pilot. Rather than hand you a raw list, I'd like to set up a short working session to walk through the Carpentries editorial flow for turning pilot feedback into lesson updates, and I'm happy to open some of the PRs myself to get things moving:

• NSF 26-202 DMP webform (required as of Apr 27 2026; research.gov form currently unstable)
• NIH DMS form update
• Consolidated jargon glossary
• Less US-centric examples (AU/UK/EU)
• README further-reading resource
• Pacing pass (pilot covered 2 of 5 sections in 2 hours)

I'll reach out to find a time. Thanks Jennifer for the detailed notes.