dv-api-metrics 0.2.8

Python code to collect metrics from datasets in Dataverse collections

dv-api-metrics

• Python code to collect metrics from datasets in Dataverse collections.
• Used primarily to support the CAFE project.
• Note: This library will become obsolete when the Dataverse Hub supports more metrics including dataset download metrics.

Objectives

• Track collection change over time. Collection change could include tracking unique depositors and datasets created.
• Track dataset engagement over time. Dataset engagement could include tracking dataset and file download counts, as well as dataset citations (where possible).

Desired Metrics

• Number of datasets created per month
• Number of collections per month
• Number of dataset downloads per month
• Dataset keyword frequency per month
• Number of (unique) depositors per month
• Number of file downloads per month per dataset
• Make Data Count (MDC) metrics
  • Number of Make Data Count unique downloads per month
  • Number of Make Data Count unique views per dataset
  • Number of Make Data Count citations per dataset
• Total number of harvested datasets
• Number of datasets per subject
• Number of datasets per Geographic Coverage Country / Nation
• Number of datasets per keyword term (available via the UI facets, so should be in search API)

Additional Metrics

• Number of harvested dataset engagements (Note: not available via APIs)

Desired Formats

Open questions:

• Are reports preferred to raw data outputs?
  • Raw data (e.g., outputs from API queries)
  • Reports (e.g., summaries of API query output)

Technical Limitations

• Metrics will be collected using existing Dataverse Metrics API endpoints or Native API endpoints.
• Make Data Count metrics range from 2020-09 to the present.