A catalogue quality audit tool

Abstract

The current need for performance measurement and quality targets for services to users requires suitable performance indicators for libraries to use. This paper looks at the selfassessment audit tool for catalogue quality developed by UKOLN in collaboration with Essex libraries. For the tool a checklist of errors was drawn up, which can then be used to assess the quality of records within a catalogue using a sample of library stock. The tool can be used to assess the quality of catalogue records for monographs and non-book materials (but not serials), for complete collections or parts of collections and for records created at different periods. This paper describes the tool and the process of making the assessment and reports on the results of the pilot study carried out at the University of Bath Library in 2000.

An Assessment of Google Books’ Metadata

“…Ryans (1978), Ballard and Lifshin (1992), Chapman and Massey (2002), and Beall (2005) provide important analyses of the role that errors take in reducing findability in bibliographic data systems ranging from OPACs to Digital Asset Management Systems. Misspellings have traditionally been the focus of most studies; Ryans (1978) focuses on the most frequent cataloging errors; Ballard and Lifshin (1992) find 1000 spelling errors among 117,000 keywords (a rate of about .85%); Chapman and Massey (2002) find an overall error rate of 34.4% in their study of errors in MARC records at the University of Bath, but most of the errors are considered "minor". Only 7.6% -11.4 % of errors are considered "major," or "those that affect access" (Chapman & Massey, 2002).…”

“…Misspellings have traditionally been the focus of most studies; Ryans (1978) focuses on the most frequent cataloging errors; Ballard and Lifshin (1992) find 1000 spelling errors among 117,000 keywords (a rate of about .85%); Chapman and Massey (2002) find an overall error rate of 34.4% in their study of errors in MARC records at the University of Bath, but most of the errors are considered "minor". Only 7.6% -11.4 % of errors are considered "major," or "those that affect access" (Chapman & Massey, 2002). These studies seem to suggest that anywhere between 1% and 12% rates of major errors would be comparable to the standards found in libraries' rich, metadata-centric systems.…”

“…Many of these studies, however, emphasize "mechanical accuracy" over that of "subjective intellectual accuracy" (Chapman & Massey, 2002). This study takes another approach by focusing not merely on mechanical accuracy such as misstrokes, transpositions, interchange and migration errors, but also looks at some of the problems involved with preserving semantic meanings in metadata: omissions, insertions, misattributions, and other factual errors, including the frequency in the misuse of dates.…”

Investigation into Diligence in Metadata Records of Mysore University Library

“…The study extracts a total of 341 CIP records (January to April 2000) in an attempt to observe, compare and evaluate the CIP records. 12 have argued that the number of records in the sample depends on the acceptable margin of error in the result, but it does not depend on the size of the population (provided fewer than 10% of records are to be sampled, which is almost always the case). Hewitt 13 has taken 2500 records for his study.…”

Snakes and ladders: towards a post‐maturity evaluation index of integrated library system ownership

“…However, measures such as a checklist of desirable features will vary between libraries, any enumerated list of features would soon become out of date and functionality is more substantially a critical selection criteria at the point of purchase. Building on these considerations, a series of selfassessment questions will point the way forward, especially if based on results of user surveys and other tools such as those described for assessing catalogue quality by Chapman and Massey (2002). Few libraries can exist in the present environment without running regular user satisfaction surveys.…”