MODS and RDF Call 2016-04-04
Time: 9am PDT / Noon EDT
Call-In Info: 712-775-7035 (Access Code: 960009)
Homework Reminder:
Subject Individual Mappings: Subject Individual Institution Usage And RDF Conversion
Moderator: Steven Anderson (Boston Public Library)
Primary Notetaker: Eben English (etherpad link: https://etherpad.wikimedia.org/p/RDF-MODS-20160404)
Attendees:
@sanderson (BPL)
@Eben English (BPL)
@sonoe (UNC-CH)
Steve DiDomenico (Northwestern)
@Juliet Hardesty (Indiana University)
Jennifer Liss (Indiana University)
@soriordan (Emory)
@Danny Pucci (BPL)
Melanie Wacker (Columbia University)
Eric O'Hanlon (Columbia University)
@Kelcy Shepherd (Amherst College)
@Sara Rubinow (NYPL)
@saverkamp (NYPL)
Agenda:
Introductions
Conversion Code Update / Notes Testing
This work is still ongoing. Currently investigating speed/performance differences between minting objects and storing strings as objects of triples.
Subject Element Mappings
UNC-CH
Explored using dcterms:subject, foaf:topic, and dcterms:temporal
Minting subject objects with skos:prefLabel for value.
NYPL
moving away from complex (precoordinated) subjects, using FAST, but may have complex subjects from legacy data.
minting local subjects (nypl:Concept), using skos:exactMatch or skos:closeMatch for URIs from vocabularies
would use multiple skos:exactMatch triples for terms existing in multiple vocabs
Needs to support local subjects
using edm:Place (geographic subjects); edm:TimeSpan (temporal subjects)
Indiana
Using dcterms:subject, dcterms;temporal, dcterms:spatial
Leaning away from complex subjects, but needs to do more internal research
Might need to support local subjects
For <mods:hierarchicalGeographic>, would likely just use TGN URI for most specific place in hierarchy
BPL
Using DCE:subject (Dublin Core elements), as this has a range of both strings and URIs
dcterms:spatial for geographic subjects (following modeling from Hydra geo_concerns)
DCE:coverage for points and bounding boxes, where values are strings conforming to DCMI Point or Box syntax
For complex subjects, storing the full precoordinated string as skos:prefLabel, and component parts as rdfs:Label in a minted subject container
Using skos:exactMatch, skos:closeMatch, and skos:inScheme to provide connections to existing vocabularies
Amherst
Still working on mapping
Leaning toward complex subjects (many legacy records), not concerned with making individual component terms accessible
Columbia
Still working on examples
Using FAST for new digital collections, but have legacy data with complex subjects
possibly using bf:subject, dcterms:subject, dcterms:spatial, dcterms:temporal, but still undecided on vocabularies
Emory
Still working on examples, have added use cases to their mapping document
Assignments for next time:
Revise mappings based on today's discussion
Next meeting: Monday April 4th, 9:00 AM PST (12:00 PM EST)