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- Label exact match search supports unsupervised automated batch add URIs to existing data.
- ATOM feed is an API that gives the delta, to update cached data based on changes.
- Generally, there's a need to not build separate ETL processes for each dataset for caching locally data for indexing to support local workflows
- Filtering is useful in a number of workflows, whether automated, supervised batch, or single entity search. What to filter on is a significant challenge, with a need to understand both the data model and consumer needs.
- Of the use cases defined, there seems to be two schools of thought on where to start, first focus on a consistent return of data with agreed upon data models across different data sets (because without it deciding what to search for each in each dataset is really hard) or first focus on providing a general search that returns a URI, label with other context in a consistent format (which would punt the modeling questions, but provide consistent access technology-wise)
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Attendees
- Kevin Ford (LOC)
- Nate Trail (LOC)
- Kirk Hess (OCLC)
- Rick Bennett (OCLC)
- John Chapman (OCLC)
- Nancy Fallgren (NIH)
- John Graybeal (Bioportal)
- Lydia Pintscher (Wikidata)
- Jens Ohlig (Wikidata)
- Hetty van Zutphen (ISNI)
- Steven Folsom (Cornell)
- Christine Fernsebner Eslao (Harvard)
- Jeremy Nelson (Stanford)
- Justin Littman (Stanford)
- E. Lynette Rayle (Cornell)
- Rob Sanderson (independent)
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