Per discussion at meeting 2014-06-24. See LD4L Use Cases for full set of use cases.
| Use case | institutions planning to work on this use case (#local-priority) | Who | Notes |
|---|---|---|---|
| Use Case 1.1: Build a virtual collection | Cornell (#1) | Lynette, Simeon | Lynette started Open Annotations in Hydra. Locally we think of replacing CuLLR as a key application of this use case. |
| Harvard | (Michael Vandermillen as advisor) | Library Cloud via localized Omeka | |
| Stanford | |||
| Use Case 1.2: Tag scholarly information resources to support reuse | Cornell (#2) | Lynette | Locally this is the case of tagging many items for inclusion in CuLLR and to appear as a facet on the main D&A system (Such as "Entomology collection"). Interface must support selection of large numbers of items by criteria such as LCSH heading, in addition to selection of individual items |
| Stanford | |||
| Use Case 2.1: See and search on works by people to discover more works, and better understand people | Cornell | ||
| Harvard | yes | FacultyFinder (incomplete)? | |
| Stanford | yes | CAP, local authority for SearchWork | |
| Use Case 3.1: Search with Geographic Data for Record Enrichment and Pivoting | Cornell | has code to share | Climate Change; has semantic search for synonym expansions, etc. |
| Harvard | Paolo dbpedia place stuff | ||
| Stanford | yes | Geo, Darren W. has examples of architecture of ontology triples with API ... | |
| Use Case 3.2: Search with Subject Data for Record Enrichment and Pivoting | |||
| Use Case 3.3: Search with Person Data for Record Enrichment and Pivoting | |||
| Use Case 3.4: Authority tool for more accurate data entry | |||
| Use Case 4.1: Identifying related works | defer for now? | Exaclty which data? (should we narrow our data first) exactly which sort of queries? Canned examples vs. ad hoc queries. | |
| Cornell | could take it on now, but won't be first priority among use cases. Start with "one step away" cases before taking on deeper cases. | ||
| Stanford | Darren W.: implementation to try to look at this – it takes weeks or months to run code against data to pull out interesting stuff??? | ||
| Use Case 4.2: Leverage the deeper graph to surface more relevant works | (see 4.1) | ||
| Use Case 5.1: Research guided by community usage | Cornell | Demo: would like Solr index with appropriate fields from all three institutions. Could do as harvested data from 3 institutions that Paul (Harvard) builds Stack Life on it??? Cornell and Stanford give Harvard ?? BibFrame ?? Other triples?? | |
| Harvard | Would need to refactor Stack Life code to populate Solr from linked data; it's currently populated from bib data with stack score. | ||
| Stanford | |||
| Use Case 5.2: Be guided in collection building by usage | Harvard | they have Haystack - which has classification data (bib data via subject). uses API of LLC classifications. | |
| Use Case 6.1: Cross-site search | NEED WORK TO REFINE/AGREE EVEN BASICS OF USE CASE |
Essential shared plumbing
| Shared infrastructure task | Institutions | Who | Notes |
|---|---|---|---|
| Local MARC->BibFrame conversion | Cornell | Rebecca | |
| Stanford | Already done? Updates? | ||
| Harvard | |||
| Share BibFrame data with partners | Cornell | ||
| Stanford | |||
| Harvard | |||
| Conversion of BibFrame->LD4L | Cornell | ||
| Stanford | |||
| Harvard |
