Data Management Plans (DMP) and the Role of Libraries

Data Management Plans (DMP) and the Role of Libraries IS262A Tim Dennis — UCLA Library Data Science Center Jamie Jamison — Data Repository & Collections Manager Slides:10.5281/zenodo.17360886 Why DMPs Matter Intro ● DMPs aren’t paperwork. They are living guides to data reuse. ● They describe what data you’ll collect, how you’ll manage and preserve it, and who’s responsible. ● They connect compliance, stewardship, and reproducibility. Think of the last time you documented your data workflow. How specific were you? The Research Data Lifecycle Proposal → Active Research → Preservation → Reuse ● DMPs should anticipate transitions between these phases. ● Each phase has different risks and responsibilities. Anatomy of a Strong Plan Data Description What will be created and in what format Documentation Metadata standards, README files, versioning Storage & Backup Where data live during the project Sharing & access Who can see it and under what conditions Ethics & compliance Privacy, consent, and IRB considerations Roles & responsibilities Who maintains, who deposits Preservation How it remains usable after the project What makes a strong DMP Area Weak Strong Data description “Survey data” “De-identified survey responses, CSV, 200 records” Storage “Stored securely” “Stored on UCLA Box with nightly backup” Sharing “Available upon request” “Deposited in UCLA Dataverse under CC-BY license” Documentation “TBD” “README with variable definitions in OSF repository” How Librarians Support Researchers ●Reviewing and improving DMP drafts. ●Mapping repository and funder requirements. ●Providing guidance on metadata, formats, and licensing. ●Offering infrastructure: UCLA Dataverse, Redivis, Merritt. ●Teaching FAIR and open-science practices. The Data Interview ●Like a reference interview, but focused on data. ●Ask early: What formats? ○What volume? ○How sensitive? ○Who owns it? ●These questions shape both the plan and long-term access. Common Fixes Librarians Might Make ● Clarify data type and format. ● Add preservation and backup details. ● Replace vague sharing statements. ● Align metadata with repository requirements. ●Add ethical and legal compliance details. Quick Demo: DMPTool ●Log in through UCLA SSO. ●Open a funder template—NSF or NIH. ●Show how institutional fields auto-populate. ●Export a sample plan to PDF. Question: Which section do you think most researchers struggle to complete? Connecting DMPs to Repositories ● DMPs are roadmaps that lead to actual deposits. ● UCLA repositories enable FAIR principles: ○Dataverse: open, citable data. At UCLA: https://dataverse.ucla.edu/ ○ Dryad: https://datadryad.org/ ○Redivis: restricted or sensitive data: https://redivis.com/UCLALibrary ○Merritt: preservation storage: https://merritt.cdlib.org/ Metadata and Documentation ● Metadata is what turns data into knowledge. ● Key elements librarians ensure: ○ Persistent identifiers (DOI) ○ Controlled vocabularies ○Reproducible documentation Example: Dataverse “Terms” tab → aligns with DMP fields. Repository Selection Exerciese Ask: Which repository fits these datasets? 1. Sensitive clinical interviews 2. 3D drone imagery 3. Open survey CSVs Use re3data.org to find matches Also, NIH Data Sharing Resources, Domain Specific and Generalist https://www.nlm.nih.gov/NIHbmic/domain_specific_repositories.html Repository comparison: https://zenodo.org/records/3946720 Credits and Contact Adapted from Library Carpentry DMP101 (CC BY 4.0) Slides: 10.5281/zenodo.17360886 Contact Tim Dennis - [email protected] Jamie Jamison [email protected] UCLA Library Data Science Center