Webinar: From MARC silos to Linked Data silos? Data models for bibliographic Linked Data
Many libraries are experimenting with publishing their metadata as Linked Data to open up bibliographic silos, usually based on MARC records, to the Web. The libraries who have published Linked Data have all used different data models for structuring their bibliographic data. Some are using a FRBR-based model where Works, Expressions and Manifestations are represented separately. Others have chosen basic Dublin Core, dumbing down their data into a lowest common denominator format. The proliferation of data models limits the reusability of bibliographic data. In effect, libraries have moved from MARC silos to Linked Data silos of incompatible data models. There is currently no universal model for how to represent bibliographic metadata as Linked Data, even though many attempts for such a model have been made.
In this webinar, you’ll see:
- a survey of published bibliographic Linked Data, the data models proposed for representing bibliographic data as RDF, and tools used for conversion from MARC records
- an analysis of different use cases for bibliographic Linked Data and how they affect the data model
- recommendations for choosing a data model
We also present efforts at the National Library of Finland to open up our bibliographic metadata, including the national bibliography Fennica, the national discography Viola and the article database Arto, as Linked Data while trying to learn from the examples of others. We are setting up a conversion process from MARC records to BIBFRAME and Schema.org compliant RDF, which we are going to publish as Linked Data using various technologies including a SPARQL endpoint, HDT compressed RDF dumps and a Linked Data Fragments API.
This webinar is an extended, in-depth version of the SWIB16 conference presentation ”From MARC silos to Linked Data silos?”
Minimum Participant Experience Level: Basic familiarity of bibliographic metadata and Linked Data assumed