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Using an RDF Data Pipeline to Implement Cross-Collection Search
David Henry and Eric Brown, Missouri History Museum, USA
Abstract
This paper presents an approach to transforming data from many diverse sources in support of a semantic cross-collection search application. It describes the vision and goals for a semantic cross-collection search and examines the challenges of supporting search of that kind using very diverse data sources. The paper makes the case for supporting semantic cross-collection search using semantic web technologies and standards including Resource Descriptive Framework (RDF), SPARQL Protocol and RDF Query Language (SPARQL ), and an XML mapping language. The Missouri History Museum has developed a prototype method for transforming diverse data sources into a data repository and search index that can support a semantic cross-collection search. The method presented in this paper is a data pipeline that transforms diverse data into localized RDF; then transforms the localized RDF into more generalized RDF graphs using common vocabularies; and ultimately transforms generalized RDF graphs into a Solr search index to support a semantic cross-collection search. Limitations and challenges of this approach are detailed in the paper.
Using an RDF Data Pipeline to Implement Cross Collection Search
The Missouri History Museum launched a first version cross-collection search in mid-2010. That implementation uses SOLR as a search engine with data from multiple domains (objects, archives, and photo collections) indexed to SOLR documents with various PHP scripts. Although some attempts were made to map data values to specific locations, dates, and subjects, most of the data is ind
Building Linked Data For Cultural Information Resources In Japan
Tetsuro Kamura, The Graduate University for Advanced Studies; Hideaki Takeda, Ikki Ohmukai and Fumihiro Kato, The National Institute of Informatics; Toru Takahashi, ATR Media Information Science Laboratories; Hiroshi Ueda, ATR-Promotions.inc, JAPAN
Abstract
Museum information in Japan is maintained distributedly and nonuniformly. This leads to difficulty in crossover searching for museum information. The LODAC (Linked Open Data for ACademia) project is building a prototype system (LODAC-Museum) to aggregate information across multiple sources. We identify and associate artists and works from different museum collections to provide integrated views for them. The key technology is Linked Data. All the aggregated data is transformed to the standard metadata schema and linked to each other via generated ID resources.
Keywords: Linked Data, Linked Open Data (LOD), Semantic Web, Metadata, RDF, Museum information