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How to make your data count webinar, 26 Nov 2018

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Slides from the 26 Nov Make your data count webinar. The research community has long grappled with the problem of assessing and tracking the results of scholarship. Research data is no exception. The Make Data Count (MDC) project (https://makedatacount.org/), funded by the Sloan Foundation, has delivered a data usage metric standard (Code of Practice) and a workflow for the retrieval and display of standardised usage and citation metrics in your repository interface.

Listen to this webinar to learn more about the Make Data Count project and the 5 steps you can take to make the data in your repository count. Hear from MDC project team members who have already implemented MDC in the dash (https://dash.ucop.edu) and DataOne (https://search.dataone.org/data) repositories. Learn from their experience, see the results.
Our international speaker line-up includes Daniella Lowenberg (California Digital Library) and Patricia Cruse (DataCite).
Recording available: https://youtu.be/Lkysz0Mc7fo

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How to make your data count webinar, 26 Nov 2018

  1. 1. How To Make Your Data Count Patricia Cruse, Exec Director, DataCite Daniella Lowenberg, Project Lead, MDC November 26, 2018
  2. 2. Agenda ❏ What is our initiative about? ❏ Milestones in 2018 ❏ Our first release ❏ Implementation at your repository ❏ Code of Practice ❏ Log Processing ❏ Sending Usage Logs ❏ Pulling & Displaying Usage & Citation Metrics ❏ Questions
  3. 3. What is MDC?
  4. 4. Imagine a world where data are considered a first-class research output and are valued as such...
  5. 5. Making Data Count 2014 - 2015 ▪2014 - 2015 5
  6. 6. “ 6
  7. 7. 1. Formal recommendation for measuring data usage 2. Develop Hub for all Data Level Metrics (DLM) 3. Make usage tracking easier 4. Drive adoption by showing how it can be done (easily) 5. Engage across all research communities 6. Iterate! 8 Make Data Count 2017 - 2019
  8. 8. 9 DevelopNewDataLevelMetricsHub 101110 01101001 10100101 00111001 10100110 Data Citations Repository Usage Metrics Future Metrics Leverage Existing Initiatives Develop New Recommendation ServerLog Processing Drive Adoption - Engage Communities Display Data Metrics
  9. 9. Milestones thus far
  10. 10. We created a data usage metrics standard
  11. 11. We gave MDC a narrative
  12. 12. We built out an open hub for usage metrics https://api.datacite.org/events
  13. 13. We implemented at our own repositories
  14. 14. We began to address citations
  15. 15. What does it look like?
  16. 16. How does this relate to Scholix?
  17. 17. Scholix is not a thing - it is a change initiative MDC & Scholix work hand in hand to advocate for best data citation practices ● Scholix is an information framework for submitting data citations ● MDC allows for displaying data citations back at the repository
  18. 18. Implementation at your repository
  19. 19. Why it is important Community has long grappled with the problem of assessing and tracking the results of scholarship ● Researchers ● Repositories ● Funders ● Publishers
  20. 20. Five simple steps to Make YOUR Data Count 1. Read the data usage metrics standard “Code of Practice for Research Data” 2. Process your usage logs against this standard 3. Send processed and standardized usage logs to an open hub 4. Pull usage and citation metrics from an open hub 5. Display standardized usage and citation metrics on your repository interface
  21. 21. Getting Started We have built a “Getting Started” guide walking through these steps as implemented in CDL’s Dash https://github.com/CDLUC3/Make-Data-Count/blob/master/g etting-started.md
  22. 22. 1. Code of Practice for Research Data
  23. 23. 2. Log Processing
  24. 24. Standardized Logs ● Specialized logs that are processed against Code of Practice ● Views ● Downloads ● Users: at the country level, access during a session ● Session: de-duplicate access to page within 30 seconds
  25. 25. 3. Sending Usage Reports
  26. 26. JSON Report - HeaderJSON Report - Body
  27. 27. The Usage Metrics Hub
  28. 28. Usage Metrics Hub (hosted by DataCite) ● Aggregator of research data usage reports ● Usage reports are made available via API (in original JSON format) and soon web interface and CSV ● Usage reports are broken down by dataset (and request method), and can then be aggregated over time ● Information in usage reports can be combined with data citations and dataset metadata
  29. 29. 4. Pulling Usage and Citations
  30. 30. Pulling Usage and Citations ● Data usage metrics and citations are made available via public API, with one “event” for each data citation or monthly usage count. ● Data citations are provided by DataCite metadata (i.e. come from data repositories) and Crossref, with more to come ● Currently separate APIs for usage and citations, and a third API for dataset metadata, will be combined into single API for easier retrieval of information
  31. 31. What’s next?
  32. 32. Looking Ahead ● Outreach and Adoption ○ Repository & Publishers ● Iterating on our implementation ○ Adding volume and usage by regions ○ Provide aggregation through DataCite hub ○ Beyond the DOI: metrics for other types of identifiers ○ Possible: altmetrics
  33. 33. Questions? www.makedatacount.org @makedatacount

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