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Online Statistics for Australian, New Zealand & Asian Academic Libraries Cathie Jilovsky

Online Statistics for Australian, New Zealand & Asian Academic Libraries Cathie Jilovsky. Outline. library benchmarking CAUL Statistics CAUL Online Statistics Asian Academic Libraries online statistics pilot project progress report evaluation. Online Statistical Benchmarking.

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Online Statistics for Australian, New Zealand & Asian Academic Libraries Cathie Jilovsky

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  1. Online Statistics for Australian, New Zealand & Asian Academic Libraries Cathie Jilovsky

  2. Outline • library benchmarking • CAUL Statistics • CAUL Online Statistics • Asian Academic Libraries online statistics pilot project • progress report • evaluation

  3. Online Statistical Benchmarking • online statistical benchmarking service developed by CAVAL • gather, store, analyse & provide access to data • data about users, operations, personnel, services, collections & user populations • for better business & service decisions, improve library visibility, increase user satisfaction

  4. CAUL Statistics • the Australian & New Zealand Academic Library (CAUL) Statistics • CAUL = Council of Australian University Librarians • CONZUL = Council of New Zealand University Librarians

  5. CAUL Statistics 1953 • 9 Australian University Libraries • 14 data elements • staff • collections • expenditure

  6. CAUL Statistics Website • commenced in 1997 • all data back to 1983 available as Excel spreadsheets • New Zealand University library data since 1974 • data definitions • published reports • links to other statistical websites www.caul.edu.au/stats/

  7. CAUL Online Statistics http://statistics.caul.edu.au

  8. CAUL Statistics Focus Group • accurate, relevant & authoritative data • consistency of data over time • data available widely – accessible, public & widely promoted • data which permits analysis of trends • collection of both traditional & new information • training/feedback opportunities for relevant university library staff • statistics - cheap, useful & valid

  9. CAUL Statistics: Deemed List

  10. Statistical Data Issues • data relationships • when does evolution become change? • e.g. “monographs” = “non-serials” • e.g. “opening hours” not = “opening hours during semester” • data quality • accuracy, timeliness, completeness, consistency

  11. Asian Online Statistics • sponsored by the iGroup (Asia) • pilot project objectives • development & provision of an online statistical website • implementation of sophisticated functionality • improvements to the collection processes for the individual libraries • provision of a sustainable online statistical service for the iGroup & Asian member libraries

  12. Participating Libraries • Hong Kong – 8 libraries • Malaysia – 4 libraries • Singapore – 2 libraries • Thailand – 8 libraries

  13. Pilot timeline

  14. Asian Online Statistics site http://statsasia.caval.edu.au/

  15. Pilot benefits (1) • local benefits • tracking each library over time • developing staff expertise • institutional benefits • showing the contributions of the library • national benefits • comparing with other institutions • gaining national overview of library services

  16. Pilot benefits (2) • regional benefits • comparing with similar libraries in other countries • learning from the differences • global benefits • greater understanding of the role of libraries • an opportunity to be involved & contribute to this regional development

  17. Functionality • compare institutional data • calculate ratios • display summary statistics • produce graphs • download data • input data module

  18. Data elements • Library Organisation • Library Staff • Library Services • Information Resources • Library Expenditure • Institutional Population

  19. Asian Statistics pilot - challenges • cultural & language differences • physically located across a wide geographic area • practical issues • different currencies • different financial & academic years • varying technical backgrounds • varying local infrastructure support • little tradition of sharing data • lack of familiarity with practicalities

  20. Evaluation Process • usability of the site • clear & consistent definitions • individual feedback from participants • benchmarking possibilities • resolving issues – data differences • can’t compare apples with oranges

  21. What next? • peer Libraries • Asian Libraries • CAUL Libraries • ARL Libraries • global Libraries • compare like with like …

  22. Questions?

  23. CAVALLinking Leading Libraries Cathie Jilovsky Email: cathie.jilovsky@caval.edu.au Web: http://www.caval.edu.au Online Statistics http://statistics.caul.edu.au http://statsasia.caval.edu.au

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