Make Data Count Update: November, 2017

This blog post by Daniella Lowenberg was cross-posted from the Make Data Count blog.

The Make Data Count (MDC) project is moving ahead with full force and the team wanted to take a moment to update the research stakeholder community on our project resources and roadmap.

In September, the MDC team sat down and mapped out the project plan for our two-year grant. Working in an agile method, we defined a “minimum viable product” (mvp) that comprises a full ecosystem of data usage and citation metrics flowing in and out of the technical hub and displayed on the DataONE repositories, Dash (California Digital Library Data Publishing Platform), and DataCite by summer of 2018.

This fall the MDC team also spent time traveling to several conferences to gather early adopters and gauge interest in data usage metrics. Many energetic and thoughtful discussions occurred regarding what the MDC-envisioned full ecosystem of data usage metrics will look like and how various stakeholders can contribute. The main takeaway: there is a need for a comprehensive and standardized way to count and display data level metrics.

Coming up, representatives from the MDC team will be (and hope you can join us) at:

  • American Geophysical Union (AGU), December 11-15
  • NISO Webinar “Advancing Altmetrics: Best Practices and Emerging Ideas”, December 13

So, what is MDC working on outside of these presentations?

All of the MDC project work can be tracked on Github, and we encourage you to follow along.

  • MDC and COUNTER are gathering community feedback from the COUNTER Code of Practice for Research Data Draft and turning this outline into a full narrative to be posted as a preprint in December.
  • DataCite is working to build out a Data Level Metrics Hub that will ingest data citations and data usage metrics, use the COUNTER recommendation as a standard to log crunch, and push out standardized usage metrics for display on repository interfaces.
  • Our first repositories, listed above, will be working to log process usage metrics against the COUNTER recommendation and technical hub for implementation.
  • Designs for displayed data metrics on repository interfaces will be created and tested.
  • Conversations with any groups that may want to be involved will continue- the more community feedback & support the better!

How can you help?

Everyone: We put out a COUNTER Code of Practice for Data Usage Draft and would appreciate community feedback. As stated above, this recommendation is what the usage metrics ecosystem will be standardized against. We also need help with mass outreach about our project, so please help us spread the word!

Repositories: We are collecting the names of those who would be interested in log file crunching against our COUNTER recommendation and hub and be early adopters of data level metrics; please get in touch if your repository supplies DOIs and would be interested.

Publishers: Support data citations! The data citation information is coming from CrossRef Event Data and DataCite, and the more that publishers support data citations in article publication, the more data can be fed into our hub.

Researchers: We want to give you credit for your research data. We are always looking for beta testers of our system and would appreciate your input. Please get in touch if you or your labs are interested in getting involved.

Join our mailing list & follow us on Twitter (MakeDataCount)

Daniella Lowenberg
Research Data Specialist and Product Manager at California Digital Library | Blog posts