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Abstract

OCLC's Crosswalk Web Service (Godby, Smith and Childress, 2008) formalizes the notion of crosswalk, as defined in Gill,et al. (n.d.), by hiding technical details and permitting the semantic equivalences to emerge as the centerpiece. One outcome is that metadata experts, who are typically not programmers, can enter the translation logic into a spreadsheet that can be automatically converted into executable code. In this paper, we describe the implementation of the Dublin Core Terms application profile in the management of crosswalks involving MARC. A crosswalk that encodes an application profile extends the typical format with two columns: one that annotates the namespace to which an element belongs, and one that annotates a 'broader-narrower' relation between a pair of elements, such as Dublin Core coverage and Dublin Core Terms spatial. This information is sufficient to produce scripts written in OCLC's Semantic Equivalence Expression Language (or Seel), which are called from the Crosswalk Web Service to generate production-grade translations. With its focus on elements that can be mixed, matched, added, and redefined, the application profile (Heery and Patel, 2000) is a natural fit with the translation model of the Crosswalk Web Service, which attempts to achieve interoperability by mapping one pair of elements at a time.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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Abstract

The purpose of this paper is to examine the current state of Linked Data (LD) in archival moving image description, and propose ways in which current metadata records can be enriched and enhanced by interlinking such metadata with relevant information found in other data sets. Design/methodology/approach Several possible metadata models for moving image production and archiving are considered, including models from records management, digital curation, and the recent BIBFRAME AV Modeling Study. This research also explores how mappings between archival moving image records and relevant external data sources might be drawn, and what gaps exist between current vocabularies and what is needed to record and make accessible the full lifecycle of archiving through production, use, and reuse. Findings The author notes several major impediments to implementation of LD for archival moving images. The various pieces of information about creators, places, and events found in moving image records are not easily connected to relevant information in other sources because they are often not semantically defined within the record and can be hidden in unstructured fields. Libraries, archives, and museums must work on aligning the various vocabularies and schemas of potential value for archival moving image description to enable interlinking between vocabularies currently in use and those which are used by external data sets. Alignment of vocabularies is often complicated by mismatches in granularity between vocabularies. Research limitations/implications The focus is on how these models inform functional requirements for access and other archival activities, and how the field might benefit from having a common metadata model for critical archival descriptive activities. Practical implications By having a shared model, archivists may more easily align current vocabularies and develop new vocabularies and schemas to address the needs of moving image data creators and scholars. Originality/value Moving image archives, like other cultural institutions with significant heritage holdings, can benefit tremendously from investing in the semantic definition of information found in their information databases. While commercial entities such as search engines and data providers have already embraced the opportunities that semantic search provides for resource discovery, most non-commercial entities are just beginning to do so. Thus, this research addresses the benefits and challenges of enriching and enhancing archival moving image records with semantically defined information via LD.