2018
DOI: 10.1007/s00799-018-0233-2
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Benchmarking and evaluating the interpretation of bibliographic records

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Cited by 4 publications
(4 citation statements)
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“…Billey mentioned that with the help of the ‘FRBF Family’, cataloguers can describe bibliographic entities more than required, and as a result, the information is misidentified or censored [209]. Aalberg et al [210] proposed BIB-R, the first public benchmark for the FRBRisation process.…”
Section: Resultsmentioning
confidence: 99%
“…Billey mentioned that with the help of the ‘FRBF Family’, cataloguers can describe bibliographic entities more than required, and as a result, the information is misidentified or censored [209]. Aalberg et al [210] proposed BIB-R, the first public benchmark for the FRBRisation process.…”
Section: Resultsmentioning
confidence: 99%
“…This could be related to our use of ISBNs to identify work sets. Thus, a further step in the development of an approach to complexity-sensitive book metrics could be an exploration of other FRBRisation methods that have been developed for use in library catalogues (Aalberg et al , 2019; Hickey and Toves, 2009).…”
Section: Discussionmentioning
confidence: 99%
“…Considering the practicalities of the identification and representation of the WEMI entities in bibliographic records (also known as the FRBRisation), several methods have been proposed (for an overview, see Aalberg et al , 2019). The well-known OCLC work-set algorithm that underpins work identifiers in WorldCat utilises keys generated from titles and author names to identify groups of records (Hickey and Toves, 2005, 2009).…”
Section: Conceptualising Complexity-sensitive Book Metricsmentioning
confidence: 99%
“…Tennant (2002) argued that though MARC has certain limitations including its incapability to conversion of data in RDF format for machine readability, still libraries are using MARC standard. Migration of library legacy catalogues into the formats based on the semantic of FRBR is the main obstacle for libraries (Aalberg et al, 2018).…”
Section: Linked Data Challengesmentioning
confidence: 99%