https://doi.org/10.60804/CQWN-8V24 Following advice from our workshop attendees at RDA13, we invite you to join us for our spring webinar. Join us on May 8th at 8am PST/3pm GMT as we demo our new aggregation services at DataCite and DataONE. This webinar is intended to spotlight the features and services we can build off of our central infrastructure such as aggregated usage and citations.

https://doi.org/10.60804/YC0V-QF31 *Crossposted from DataONE blog: https://www.dataone.org/news/new-usage-metrics * Publications have long maintained a citation standard for research papers, ensuring credit for cited work and ideas. Tracking use of data collections, however, has remained a challenge.

https://doi.org/10.60804/TPAK-S352 With Make Data Count now in its second year, the focus is shifting from building infrastructure to driving adoption of our open data-level metrics infrastructure.

https://doi.org/10.60804/3HWB-S535 Crossposted from COUNTER on September 13, 2018 There is a need for the consistent and credible reporting of research data usage. Such usage metrics are required as an important component in understanding how publicly available research data are being reused.

https://doi.org/10.60804/X35C-CS33 It’s been two exciting months since we released the first iteration of our data-level-metrics infrastructure.  We are energized by the interest garnered and questions we’ve received and we wanted to share a couple of highlights! July Webinar Soon after launch we hosted a webinar on “How-To” make your data count.

https://doi.org/10.60804/FH8J-T722 Many publishers have implemented open data policies and have publicly declared  their support of data as a valuable component of the research process. But to give credit to researchers and incentivize behavior for data publishing, the community needs to promote proper citation of data.

https://doi.org/10.60804/N5R2-P643 The Make Data Count team is rapidly approaching the first release of standardized and comparable data level metrics (DLMs) on California Digital Library’s Dash and DataONE repositories. Resources on this release will be available shortly, but in the meantime the team would like to share updates on work completed in winter and our spring roadmap.

https://doi.org/10.60804/8A5Y-KR76 Kicking off Love Data Week 2018, the Make Data Count (MDC) team is pleased to announce that the first iteration of our Code of Practice for Research Data Usage Metrics Release 1 has now been posted as a preprint. Beginning in June, members from the MDC team and COUNTER began conversations around what a standard for data usage metrics may look like.

https://doi.org/10.60804/V609-3D16 Following our draft update and executive summary, Make Data Count and COUNTER are proud to release our first draft of a Code of Practice for Research Data . This first iteration is meant to be a draft, and our goal is to receive input and feedback from the community. We ask that you please comment on and mark up the document with questions, suggestions, and/or overall feedback.

https://doi.org/10.60804/D1MF-EC47 As a research and scholarly communications community, we value methods to gauge the impact of research outputs, and we do this in the forms of citations and downloads. But, until now this has been limited to traditional journal publications, and scholarly research is much more than an article. Foremost, data play a major role in the research process and deserve to be valued as a first-class scholarly output.

https://doi.org/10.60804/NKCP-PZ96 COUNTER is a non-profit organization supported by a global community of library, publisher and vendor members, who contribute to the development of the Code of Practice through working groups and outreach. COUNTER and MDC  are collaborating to develop and publish a Code of Practice for Research Data. This set of recommendations will focus on how data usage should be measured and reported.