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OCLC’s iCAS Service as a Tool for Collection Managers Richard Ovenden Director of Collections, Edinburgh University Library.

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Presentation on theme: "OCLC’s iCAS Service as a Tool for Collection Managers Richard Ovenden Director of Collections, Edinburgh University Library."— Presentation transcript:

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2 OCLC’s iCAS Service as a Tool for Collection Managers Richard Ovenden Director of Collections, Edinburgh University Library

3 Outline zOCLC’s iCAS Service (Interactive Collection Analysis System) zPilot Project zFindings zRecommendations zPersonal View zSummary

4 OCLC’s iCAS Service zOCLC Lacey Product Center zACAS: Automated Collection Assessment and Analysis Services zBased on WLN Conspectus zIndividual Collection analyses zCombined analyses with overlap and uniqueness measures zEmphasis on publication dates

5 Pilot Project zFunded by CURL/RSLP zPartners: Hull, Imperial College London, Edinburgh, SOAS, Liverpool, Natural History Museum zReported February 2002

6 Process (1) z2, 767, 669 book format bibliographic records submitted zDe-dupe zMatched No Call Number items against identical records within CURL

7 Process (2) zMatch against WorldCat zThis found an additional 570, 075 records with call numbers zRejected 12, 802 ‘ill-formed’ call numbers zTotal number of records analysed 2, 268, 225 (84%) zOnly 16% of records could not be processed because they could not be allocated a call- number.

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14 Number/Percent of Records Analysed

15 Group Analysis

16 Findings (1) zData Problems ymapping inconsistencies (SOAS mapping to Celtic/Chinese) zClassification yHull had used wrong country subdivisions in some parts of the LC schedules yMatching against other utilities vs. local classification needs zMethodologies: COPAC yLoading variants Liverpool, Edinburgh

17 Findings (2) zConspectus yThe sub-divisions perceived as weak in some areas (eg biology) y Need to update categories: Where is Artificial Intelligence? yFit with collections not good. Vet Medicine in Agriculture? zQuality & relevance of data yUnique items? zAccuracy of Conspectus match at highly granular level

18 Findings (3) zAutomated matching routines are rough & ready ySpecial topics in Computer Science included two books 1800-1899 zDate breakdowns - currency indications zBased only on OPAC data zSubject groupings don’t fit collections –compare holdings by site library? zBrings out worst in Librarians zBrings out worst in Chief Librarians

19 Recommendations zRealise limitations zKnow your data (=know your collections) zTalk to your colleagues (cataloguers, systems, as well as collections specialists) zRecord data decisions (eg CURL uploads) zCollections analysis not collection description (OPAC analysis …)

20 Personal View zLabour saving zObjectivity? zAdjunct to other methods yPeople still matter zResource sharing yCompare like with like? yCompare against regional centre? yBasis for funding collaborative collection management?

21 Summary zICAS has value zICAS has limitations zICAS costs money zICAS has potential for UK libraries zIt does exactly what it says on the tin

22 FIN zrichard.ovenden@ed.ac.uk


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