Make Data Count: developing standardized data-level metrics · Five steps to Make Data Count 1....
Transcript of Make Data Count: developing standardized data-level metrics · Five steps to Make Data Count 1....
Make Data Count: developing
standardized data-level metrics
September 11, 2018
Why it is important
Community does not have an established way of tracking data-level metrics
● Researchers● Institutions● Funders● Publishers
The project
Five steps to Make Data Count
1. Read the data usage metrics standard “COUNTER 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. Retrieve usage and citation metrics through an open API
5. Display standardized usage and citation metrics
Getting Started
CDL built a “Getting Started” guide walking through these steps as implemented in CDL’s data repository
https://github.com/CDLUC3/Make-Data-Count/blob/master/getting-started.md
1.Code of Practice for Research Data
https://www.projectcounter.org/code-practice-research-data
2. Log Processing
Standardized Logs
● Logs are processed against Code of Practice to enable data repositories to produce consistent, comparable, and credible usage metrics for research data
● Specifies what should be included and excluded
● Focus on:Views = investigationsDownloads = requests
● Distinguish: total/unique and human/machine
3. Sending Usage Reports
Data Usage Metrics Hub - hosted by DataCite
● Reports are sent using a standard protocol (SUSHI) via API
● Data usage metrics hub functions as an aggregator of research data usage reports
● Information is available at the dataset (DOI) level and aggregated over time
● The hub converts all this information into ‘events’ which are made available through a query API
JSON Report - HeaderJSON Report - Body
4. Pulling Usage and Citations
Citations: leveraging Scholix
Pulling Usage and Citations
● Data usage metrics and citations are made available as events via public API, with one “event” for each data citation or monthly usage count.
● Single API for retrieval of all data-level metrics
● For more information: https://support.datacite.org/docs/eventdata-apis
5. Displaying data metrics
What’s next?
Looking Ahead
● Outreach and Adoption○ Working with repositories to send usage metrics○ Working with publishers to send data citations○ Working with all interested organizations on displaying data-
level metrics
● Iterating on our implementation○ Beyond the DOI: metrics for other types of identifiers○ Optional: altmetrics
Questions?