Museum Linked Open Data: Ontologies, Datasets, Projects Cover Image

Museum Linked Open Data: Ontologies, Datasets, Projects
Museum Linked Open Data: Ontologies, Datasets, Projects

Author(s): Vladimir Alexiev
Subject(s): Social Sciences, Museology & Heritage Studies, Library and Information Science, Archiving, Cataloguing, Classification, Information Architecture, Library operations and management, Electronic information storage and retrieval
Published by: Институт по математика и информатика - Българска академия на науките
Keywords: semantic technologies; museum data; LODLAM; CIDOC CRM

Summary/Abstract: The Galleries, Libraries, Archives and Museums (GLAM) sector deals with complex and varied data. Integrating that data, especially across institutions, has always been a challenge. Semantic data integration is the best approach to deal with such challenges. Linked Open Data (LOD) enable large-scale Digital Hu-manities (DH) research, collaboration and aggregation, allowing DH researchers to make connections between (and make sense of) the multitude of digitized Cul-tural Heritage (CH) available on the web. An upsurge of interest in semtech and LOD has swept the CH and DH communities. An active Linked Open Data for Libraries, Archives and Museums (LODLAM) community exists, CH data is published as LOD, and international collaborations have emerged. The value of LOD is especially high in the GLAM sector, since culture by its very nature is cross-border and interlinked. We present interesting LODLAM projects, datasets, and ontologies, as well as Ontotext's experience in this domain. An extended version of this paper is available. It has 77 pages, 67 figures, de-tailed info about CH content and XML standards, Wikidata and global authority control.

  • Issue Year: 2018
  • Issue No: VIII
  • Page Range: 19-50
  • Page Count: 32
  • Language: English