In this paper, we propose an ontology-based metadata integration methodology for the cultural heritage domain. The proposed real -world approach considers an integration architecture in which CIDOC/CRM ontology acts as a mediating scheme. In this context, we present a mapping methodology from Encoded Archival Description (EAD) and Dublin Core (DC) metadata to CIDOC/CRM, and discuss the faced difficulties.
Digital folklore collections are valuable sources for studying the cultural and oral tradition of a country. The main difficulty in managing such collections is material heterogeneity (handwritten texts, photographs, 3D objects, sound recordings etc.) that imposes different digitization, description and maintenance practices. A multi-layer metadata model for the description of a digital folklore collection is presented. The proposed meta-data policy considers a collection as a hierarchy of entities and combines different metadata schemas for the management of each entity. The metadata model integrates elements from different metadata schemas ensuring efficient information recovery from all structural levels. Furthermore, interoperability between the used metadata schemas is discussed and a Topic Maps model is presented as an approach for developing mappings.
In this paper, we discuss the use of ontologies for data integration. We consider two different settings depending on the system architecture: central and peer-to-peer data integration. Within those settings, we discuss five different cases studies that illustrate the use of ontologies in metadata representation, in global conceptualization, in high-level querying, in declarative mediation, and in mapping support. Each case study is described in detail and accompanied by examples.
An extension of the Dublin Core Collections Application Profile (DCCAP ) suitable for representing context-dependent collection level metadata, is presented in this paper. The extended model, called Multidimensional DCCAP, is based on a multidimensional extension of RDF. Contexts are specified by assigning values to a set of appropriately chosen parameters called dimensions. The proposed extension allows the user to encode metadata for each defined context enriching substantially in this way the expressive power of the metadata model. Multidimensional DCCAP metadata model allows to represent the collection development evolution as well as to keep information created for various users categories, with various degrees of detail, or even in different languages.
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