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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

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Online Statistics for Australian, New Zealand & Asian

Academic LibrariesCathie Jilovsky

Outline

• library benchmarking

• CAUL Statistics

• CAUL Online Statistics

• Asian Academic Libraries online

statistics pilot project progress report evaluation

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

1998

2001

2004

1998

2001 2004

3.2

3.4

3.6

3.8

4.0

4.2

4.4

4.6

4.8

Type 1 Type 2 Type 3

CAUL Statistics

the Australian & New Zealand Academic Library (CAUL) Statistics

CAUL = Council of Australian University Librarians

CONZUL = Council of New Zealand University Librarians

CAUL Statistics 1953

• 9 Australian University Libraries

• 14 data elements

staff

collections

expenditure

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/

CAUL Online Statistics

http://statistics.caul.edu.au

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

CAUL Statistics: Deemed List

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

Asian Online Statistics

• sponsored by the iGroup (Asia)

• pilot project objectivesdevelopment & provision of an online statistical

website implementation of sophisticated functionality improvements to the collection processes for

the individual librariesprovision of a sustainable online statistical

service for the iGroup & Asian member libraries

Participating Libraries

• Hong Kong – 8 libraries

• Malaysia – 4 libraries

• Singapore – 2 libraries

• Thailand – 8 libraries

Pilot timeline

2006

Introductory workshops

Initial site development

Pilot data entry CAVAL Help Desk

2007

Further workshops

Phase 1 data entry

Malaysia & Thailand begin

2008

Hong Kong & Singapore join

Phase 2 commences

Evaluation

Asian Online Statistics site

http://statsasia.caval.edu.au/

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

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

Functionality

• compare institutional data

• calculate ratios

• display summary statistics

• produce graphs

• download data

• input data module

Data elements

• Library Organisation

• Library Staff

• Library Services

• Information Resources

• Library Expenditure

• Institutional Population

Asian Statistics pilot - challenges• cultural & language differences

• physically located across a wide geographic area

• practical issuesdifferent currenciesdifferent financial & academic yearsvarying technical backgroundsvarying local infrastructure support little tradition of sharing data lack of familiarity with practicalities

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

What next?

• peer Libraries

• Asian Libraries

• CAUL Libraries

• ARL Libraries

• global Libraries

• compare like with like …

Questions?

CAVALLinking Leading Libraries

Cathie Jilovsky

Email: [email protected]

Web: http://www.caval.edu.au

Online Statistics

http://statistics.caul.edu.au

http://statsasia.caval.edu.au