Mapping Manuscript Migrations Knowledge Graph: Data for Tracing the History and Provenance of Medieval and Renaissance Manuscripts

Burrows, Toby; Emery, Doug; Fraas, Mitch; Hyvönen, Eero; Ikkala, Esko; Koho, Mikko; Lewis, David; Morrison, Andrew; Page, Kevin R.; Ransom, Lynn; Thomson, Emma; Jouni, Tuominen; Velios, Athanasios and Wijsman, Hanno. 2020. Mapping Manuscript Migrations Knowledge Graph: Data for Tracing the History and Provenance of Medieval and Renaissance Manuscripts. Journal of Open Humanities Data, 6(1), pp. 3-5. ISSN 2059-481X [Article]

[img]
Preview
Text
14-193-1-PB.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (831kB) | Preview

Abstract or Description

The Mapping Manuscript Migrations (MMM) project transformed three separate datasets relating to the history and provenance of medieval and Renaissance manuscripts into a unified knowledge graph. The source databases are: Schoenberg Database of Manuscripts, from the Schoenberg Institute for Manuscript Studies, University of Pennsylvania; Bibale, from the Institut de recherche et d’histoire des textes (IRHT-CNRS, Paris); and Medieval Manuscripts in Oxford Libraries, from the Bodleian Libraries, University of Oxford. The data consist of more than 20 million RDF triples which have been mapped to the MMM Data Model. The model combines classes and properties from CIDOC-CRM and FRBR, together with some specific MMM elements. The Knowledge Graph was created using the MMM data transformation pipeline. The MMM dataset is available from the Zenodo repository, and can be directly deployed on a SPARQL endpoint using a docker recipe. To test and demonstrate its usefulness, the MMM Knowledge Graph is in use in the MMM Semantic Portal: https://mappingmanuscriptmigrations.org.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.5334/johd.14

Keywords:

Digital Humanities, Manuscript studies, Linked Data, Medieval manuscripts, Renaissance manuscripts, CIDOC-CRM, FRBR, provenance, knowledge graphs

Related URLs:

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
7 May 2020Accepted
11 June 2020Published

Item ID:

28830

Date Deposited:

23 Jun 2020 10:33

Last Modified:

23 Jun 2020 10:33

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

http://research.gold.ac.uk/id/eprint/28830

View statistics for this item...

Edit Record Edit Record (login required)