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Make Data Count
Partners California Digital Library, PLOS, and DataONE
NSF Grant Record: Grant No. 1448821 Proposal PDF in eScholarship repository
Project page h,p://arCclemetrics.github.io/MDC/
Prototype h,p://dlm.plos.org LagoGo soHware is Open Source h,ps://github.com/arCclemetrics/lago,o 2
Scholars access, share, cite, & reuse papers in many ways. ArCcle-‐level metrics:
3
figshare
PMC Europe PMC Europe Data- base Citations DataCite
ScienceSeeker
F1000 Prime
But, data… • Also 1st class scholarly object • Broader role in research process • Has its own use & reuse profile • Infrastructure services to collect metrics are lagging
• Common best pracCces are not enshrined in research communiCes
Mechanisms for usage collecCon How do we count usage stats?
Independent downloads? EnCre package? • Sum downloads: 1733 • Average downloads: 346 • Maximum downloads: 586 • Whole package: 35
How do we count across versions? • Sum downloads across all version? • Average downloads across versions?
Only some objects change in a new package
How do we standardize usage collecNon pracNces to compare across providers?
• Standard means of reporCng usage of arCcles • COUNTER reports remove: – Web robots from search engines – Repeat visits in short Cme window (double clicks) – All accesses from Python, Java, curl, wget, etc.
• ScienCsts frequently use these to access data • COUNTER issues with composite objects • COUNTER issues with versioning
We will propose changes to COUNTER for data and data package downloads.
h,p://www.projectcounter.org/
Make Data Count Project Plan 1. DLM Field Research What: Surveys, interviews, focus groups to determine requirements for DLM Output: metrics design & requirements
2. Data Usage Tracking What: Extend DataONE usage tracking capacity Output: extended usage API (COUNTER-‐based)
3. Data AcCvity AggregaCon What: Formulate a set of metrics to text; extend technology Output: DLM applicaCon
4. DLM IntegraCon & PresentaCon What: Develop tools for the community to use metrics Output: DLM Reports applicaCon & widgets Bibliometric Analysis What: Analyze, write up results from project Output: final report &recommendaCons
Tell the broader story: create an aggregate narraCve of research acCvity by bringing metrics on data &
arCcles together Create a report • Keyword • Author • InsCtuConal affiliaCon • PublicaCon date • Subject areas • Funder
Stanford University + NaNonal Cancer InsNtute
Visualize the data
Thank you
Jennifer Lin, PLOS [email protected]
Ma, Jones, DataONE [email protected]
Make Data Count Team h,p://arCclemetrics.github.io/MDC/
• MarCn Fenner, PLOS • Kristen Ratan, PLOS • John Chodacki, PLOS • Dave Vieglais, DataONE
• Patricia Cruse, CDL • Carly Strasser, CDL • John Kratz, CDL