Search (7 results, page 1 of 1)

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Abstract

The concept of Linked Data has been an emerging theme within the computing and digital heritage areas in recent years. The growth and scale of Linked Data has underlined the need for greater commonality in concept referencing, to avoid local redefinition and duplication of reference resources. Achieving domain-wide agreement on common vocabularies would be an unreasonable expectation; however, datasets often already have local vocabulary resources defined, and so the prospects for large-scale interoperability can be substantially improved by creating alignment links from these local vocabularies out to common external reference resources. The ARIADNE project is undertaking large-scale integration of archaeology dataset metadata records, to create a cross-searchable research repository resource. Key to enabling this cross search will be the 'subject' metadata originating from multiple data providers, containing terms from multiple multilingual controlled vocabularies. This paper discusses various aspects of vocabulary mapping. Experience from the previous SENESCHAL project in the publication of controlled vocabularies as Linked Open Data is discussed, emphasizing the importance of unique URI identifiers for vocabulary concepts. There is a need to align legacy indexing data to the uniquely defined concepts and examples are discussed of SENESCHAL data alignment work. A case study for the ARIADNE project presents work on mapping between vocabularies, based on the Getty Art and Architecture Thesaurus as a central hub and employing an interactive vocabulary mapping tool developed for the project, which generates SKOS mapping relationships in JSON and other formats. The potential use of such vocabulary mappings to assist cross search over archaeological datasets from different countries is illustrated in a pilot experiment. The results demonstrate the enhanced opportunities for interoperability and cross searching that the approach offers.

Source

International journal on digital libraries. 2015, S.1-17 DOI: 10.1007/s00799-015-0166-y

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Abstract

Purpose - The purpose of this paper is to describe a new approach to a well-known problem for digital libraries, how to search across multiple unrelated libraries with a single query. Design/methodology/approach - The approach involves creating new Dewey Decimal Classification terms and numbers from existing Dublin Core records. In total, 263,550 records were harvested from three digital libraries. Weighted key terms were extracted from the title, description and subject fields of each record. Ranked DDC classes were automatically generated from these key terms by considering DDC hierarchies via a series of filtering and aggregation stages. A mean reciprocal ranking evaluation compared a sample of 49 generated classes against DDC classes created by a trained librarian for the same records. Findings - The best results combined weighted key terms from the title, description and subject fields. Performance declines with increased specificity of DDC level. The results compare favorably with similar studies. Research limitations/implications - The metadata harvest required manual intervention and the evaluation was resource intensive. Future research will look at evaluation methodologies that take account of issues of consistency and ecological validity. Practical implications - The method does not require training data and is easily scalable. The pipeline can be customized for individual use cases, for example, recall or precision enhancing. Social implications - The approach can provide centralized access to information from multiple domains currently provided by individual digital libraries. Originality/value - The approach addresses metadata normalization in the context of web resources. The automatic classification approach accounts for matches within hierarchies, aggregating lower level matches to broader parents and thus approximates the practices of a human cataloger.

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Abstract

Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine-based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.

Date

22. 8.2014 17:12:54

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Abstract

Subject terms play a crucial role in resource discovery but require substantial effort to produce. Automatic subject classification and indexing address problems of scale and sustainability and can be used to enrich existing bibliographic records, establish more connections across and between resources and enhance consistency of bibliographic data. The paper aims to put forward a complex methodological framework to evaluate automatic classification tools of Swedish textual documents based on the Dewey Decimal Classification (DDC) recently introduced to Swedish libraries. Three major complementary approaches are suggested: a quality-built gold standard, retrieval effects, domain analysis. The gold standard is built based on input from at least two catalogue librarians, end-users expert in the subject, end users inexperienced in the subject and automated tools. Retrieval effects are studied through a combination of assigned and free tasks, including factual and comprehensive types. The study also takes into consideration the different role and character of subject terms in various knowledge domains, such as scientific disciplines. As a theoretical framework, domain analysis is used and applied in relation to the implementation of DDC in Swedish libraries and chosen domains of knowledge within the DDC itself.

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Abstract

Controlled terminologies such as classification schemes, name authorities, and thesauri have long been the domain of the library and information science community. Although historically there have been initiatives towards library style classification of web resources, there remain significant problems with searching and quality judgement of online content. Terminology services can play a key role in opening up access to these valuable resources. By exposing controlled terminologies via a web service, organisations maintain data integrity and version control, whilst motivating external users to design innovative ways to present and utilise their data. We introduce terminology web services and review work in the area. We describe the approaches taken in establishing application programming interfaces (API) and discuss the comparative benefits of a dedicated terminology web service versus general purpose programming languages. We discuss experiences at Glamorgan in creating terminology web services and associated client interface components, in particular for the archaeology domain in the STAR (Semantic Technologies for Archaeological Resources) Project.

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Abstract

The recent ISKO-UK conference considered the question of whether the traditional thesaurus has any place in modern information retrieval. This note is intended to continue in the spirit of that good-natured debate, arguing that there is indeed a role today and highlighting some recent work showing the continued relevance of the thesaurus, particularly in the linked data area. Key functionality that a thesaurus makes possible is discussed. A brief outline is provided of prominent work hat employs thesauri in three key areas of infrastructure underpinning advanced retrieval functionality today: metadata enrichment,vocabulary mapping and web services.