Defining Meaningful Metrics for DataverseNL: Stakeholder Perspectives & Practical Solutions
Bosman, Jeroen; Flores, Jacques; Veldkamp, Coosje Lisabet Sterre; Weijdema, Felix
- Publisher
- Zenodo
- Language
- en
Abstract
Abstract DataverseNL provides multiple ways to track dataset activity, but are the existing metrics sufficient for all stakeholders? This interactive workshop will bring together researchers, institutional managers, data stewards, and policymakers to explore what metrics they need, how current DataverseNL metrics align with these needs, and where gaps exist. Through collaborative exercises, participants will define key use cases, assess available metrics, and propose new ways to measure data reuse and impact. The session will result in actionable insights to help improve the usefulness of DataverseNL’s metrics. For whom? Anyone interested in research data metrics, including researchers, data professionals, institutional managers, and DataverseNL administrators. Duration 2.5 hours Format Interactive discussions, group activities, and hands-on problem-solving.
Full text
DANS, DataverseNL 10th anniversary event, Utrecht, 20250916 Felix Weijdema & Jeroen Bosman Research Data Support & Publishing Support, Utrecht University Library Original slides prepared by Coosje Veldkamp and Jacques Flores Defining Meaningful Metrics for DataverseNL: Stakeholder Perspectives & Practical Solutions edu.nl/k7k97 License details on final slide
Workshop programme Part 1: •Who’s in the room? (15 minutes) •Reviewing existing metrics Dataverse and elsewhere (15 minutes) •Use case mapping (30 minutes) Part 2: •Deep dive into a selection of use cases (75 minutes) •Closing and next steps (15 minutes) SLIDES edu.nl/k7k97
Who’s in the room? (15 minutes) •Who are you: affiliation, role •What data metrics did you encounter in the past week/month? Do we have... •Researchers? •Institutional managers? •Data stewards & librarians? •Funding bodies & policy makers? •DANS & DataverseNL Admins? •General public & citizen scientists?
Reviewing existing metrics Dataverse(NL) (15 minutes)
Dataverse Metrics https://dataverse.nl/dataverse-metrics/
Dataverse Metrics https://dataverse.nl/dataverse-metrics/ Data retrieved via the Dataverse Metrics API Feedback is welcome via https://github.com/gdcc/dv-metrics or any other channel. Default metrics from UU Dataverse
https://doi.org/10.34894/HE6NAQ
Dataverse metrics API: Datasets, Files, Downsloads, Accounts
Reviewing existing metrics (15 minutes) DashBoard Maastricht https://dans.knaw.nl/en/news/dataversenl-at-maastrichtuniversity-usage-insight/ https://github.com/MaastrichtU-Library/dataverse-analysis
What is already being tracked? Dataverse •Dataverses by category •Dataverses by subject Datasets •Total published datasets (per year) •Total number of draft datasets •Datasets by license •Datasets by published status •Datasets by subject •Datasets producer name? •Total aggregated downloads of all files in this dataset Files •Files by type •Files by tag •Files by access •Downloads per file
What is not shown but could/should be tracked? Datasets •Datasets with at least 5 keywords •Datasets without a person PID •Datasets without related publication PID •Dataset views (website) •Dataset citations •Dataset mentions •Dataset FAIR(ness) Metrics •Dataset location (of data collection) •Datasets by license •Metadata downloads Dataverse •Size •SDG relation •… •… •… •... Files •Size •… •… •… •...
Use case mapping (30 minutes)
Format: "As a [stakeholder], I need to know [X] because [Y].“ Example: "As a researcher, I need to know how often my dataset is downloaded because it helps demonstrate impact to funders."
Selection of (1-3) use cases for deep dive
BREAK
Deep dive into a selection of use cases (75 minutes)
Reference slides –data metrics https://www.fairsfair.eu/f-uji-automated-fair-data-assessment-tool
Reference slides –data metrics Global Research Initiative on Open Science (GRIOS) –under development Open Science Monitoring Initiative (OSMI, in progress, no results shared yet) PathOS is a Horizon Europe project aiming to collect concrete evidence of Open Science effects
https://makedatacount.org/ Reference slides –data metrics https://doi.org/10.5281/zenodo.14261210
