Back to articles
Articles
Volume: 17 | Article ID: art00016
Image
Artificial Intelligence for Content and Context Metadata Retrieval in Photographs and Image Groups
  DOI :  10.2352/issn.2168-3204.2020.1.0.79  Published OnlineApril 2020
Abstract

In the age of the WWW consistent efforts have been made to make information from the archives available for the general public to facilitate access to the wealth of documentary history for research, consultation or education purposes. Linked Open Data (LOD)[1] provide a well suited framework to expose archival content to the general public while enriching it with content from other sources. This paper describes the creation of the first of its kind linked open data prototype to access data from the Historical Archive of the European Commission (HAS), carried out within ISA2 programme of the European Commission [2]. We present the designed ontology based on ISAD(G)[3], ISAAR(CPF)[4] and RIC-CM [5] models and the business processes of HAS, and the created knowledge base from a sample of HAS data, re-using authority lists from the Publication Office [6] and EuroVoc [7] and allowing querying via SPARQL endpoint [8].

Subject Areas :
Views 47
Downloads 18
 articleview.views 47
 articleview.downloads 18
  Cite this article 

Peter Fornaro, Vera Chiquet, "Artificial Intelligence for Content and Context Metadata Retrieval in Photographs and Image Groupsin Proc. IS&T Archiving 2020,  2020,  pp 79 - 82,  https://doi.org/10.2352/issn.2168-3204.2020.1.0.79

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2020
72010361
Archiving Conference
archiving
2161-8798
Society for Imaging Science and Technology