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UKSG Conference April 2010, Edinburgh. The UKSG Usage Factor Project A Progress Report Richard Gedye and John Cox UKSG Conference April 2010, Edinburgh.

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Presentation on theme: "UKSG Conference April 2010, Edinburgh. The UKSG Usage Factor Project A Progress Report Richard Gedye and John Cox UKSG Conference April 2010, Edinburgh."— Presentation transcript:

1 UKSG Conference April 2010, Edinburgh

2 The UKSG Usage Factor Project A Progress Report Richard Gedye and John Cox UKSG Conference April 2010, Edinburgh

3 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

4 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Some early recommendations  Anticipated issues that will need to be addressed  Next steps

5 The challenge…….  ISI's Impact Factor compensates for the fact that larger journals will tend to be cited more than smaller ones  Can we do something similar for usage?  In other words, should we seek to develop a “Usage Factor” as an additional measure of journal quality/value?

6 For example….. Usage Factor = Total usage over period ‘x’ of articles published during period ‘y’ Total articles published during period ‘y’

7 Usage factor advantages  Especially helpful for journals and fields not covered by ISI  Especially helpful for journals with high undergraduate or practitioner use  Especially helpful for journals publishing relatively few articles  Data available potentially sooner than with Impact Factors

8  “Authors select journals that will give their articles prestige and reach. Impact Factor is a widely used surrogate for the former, while perceived circulation and readership reflect the latter. But usage is becoming more important as a measure of reach” Carol Tenopir

9 Modelling and Analysis Using Real Data

10  Real journal usage data is currently being analysed by John and Laura Cox  Participating publishers:- –American Chemical Society –Emerald –IOP –Nature Publishing –OUP –Sage –Springer

11 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

12 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

13 Key data issues we have addressed  Consistency – numerator/denominator  Defining article usage year  Defining article publication date  Different usage patterns by subject

14 Data issues we have addressed 1. Consistency –Items in numerator must be in denominator –Clear definition of qualifying “items”  Machine recognisable  Unambiguous Solution? All items with a DOI? –This will include items such as editorial board listings, calendars of events, sponsoring society announcements, etc.

15 Other Possible Solutions  Rejected –Item must have references –Item must not have an empty author field –Item must be more than one page in length  Possible –Cross mapping items against one of the large and inclusive A and I services or citation databases –Examining article DTD tags –Intelligent textmining

16 Longer-term Solutions  Encourage publishers to:- –Lodge more detailed article metadata with CrossRef –Adopt the NLM DTD, use its article categories element, and make the results harvestable

17 Key Data Issues  Consistency – numerator/denominator  Defining article usage year  Defining article publication date  Different usage patterns by subject

18 Data issues we have addressed 2. Article usage year –Inter-journal comparisons can be distorted by different patterns of article publication during the calendar year –Usage in the first calendar “year” could be as little as one month and as much as 12 months Solution –provide data about the first 12, 24, 36 months of usage of articles published in each chosen calendar year rather than calendar year usage

19 Key Data Issues  Consistency – numerator/denominator  Defining article usage year  Defining article publication date  Different usage patterns by subject

20 Data issues we have addressed 3. Article publication date –Early online version –Final online version –Printed issue publication date  Some early or even “final” versions of articles are published online many months (sometimes years) before the official publication date of the journal issue of which they are nominally a part. Solution –Supply usage data at the article version level, showing usage patterns of different versions separately

21 Key Data Issues  Consistency – numerator/denominator  Defining article usage year  Defining article publication date  Different usage patterns by subject

22 Data issues we have addressed 4. Potential differences by subject –Might usage patterns vary between subject areas? –To find out, we needed to identify a third party schema which had classified by subject all journals participating in our project Solution –Use the Dewey Decimal Codes (DDC) which the British Library have assigned to all the journals for which they hold records (>20,000)

23  With key data issues addressed, we developed a specification for a report via which participating publishers would deliver their usage data for analysis

24 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

25 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

26 JUF variables to be tested  All journal content (excluding standing matter)  Articles only: –Version of Record –All versions of the article on the publishers’ platform  Differing publication periods – 1 or 2 years ( )  Differing usage periods: –Single year of usage from the online publication date –Two years of usage from the online publication date –Single year of usage from a year after the online publication date –Two years of usage from a year after the online publication date  Samples of calendar year usage

27 JUF variables to be tested – continued… Subject comparisons  Broad subjects: –Physical Sciences –Medicine and Life Sciences –Social Sciences –Humanities –Engineering  Narrow subjects –Business and Management –Clinical Medicine

28 Methodology Journal Content type All content Articles only Version VoR All versions Publication Year Usage period Months 1-12 Months 1-24 Months Months 13-36

29 The data

30 The calculation Journal Usage Factor = Total usage over period ‘x’ of items published online during period ‘y’ Total items published online during period ‘y’  ‘x’ is the usage period  ‘y’ is the publication period Create comparative subject data  JUFs for each journal into seven spreadsheets (one per subject) –All content JUFs –Article only JUFs –VoR only JUFs –All version JUFs

31 Comparing results VariableArticle & Non-article content JUFs Publ. Year Usage Period Journal Title Journal A Journal B VariableArticle only JUFs Publ. Year Usage Period Journal Title Journal A Journal B

32 Determine the best definitions for the calculation  To include non-article content or not  To include versions of articles other than the VoR  Which definitions of ‘x’ and ‘y’ work best  Does calendar year create as meaningful data  Are the differences between subjects significant – do they need different definitions or calculations  What will be easiest for publishers

33 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

34 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed

35 Issues to address in next phase of project  Detecting and deterring gaming  Differences between disciplines and journal types  What about print usage  What about offline usage  How to integrate usage data when journal content hosted on multiple sites  Responding to technological innovations

36 Responding to technological innovations  Prefetching to local cache (E.g. PubGet, WebFeat) –Need to establish list of user-agent names –Then ignore prefetch requests and count only those with a “304” response

37 Responding to technological innovations  Bulk downloading to local hard disk (E.g. Quosa, PubGet bulk download plug-in) –If specifically requested (e.g. Quosa), these should ideally be counted but considered separately –We are still considering ways to address the automated downloading of articles to hard disk

38 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

39 UKSG Usage Factor Project  Brief background  Issues addressed before data collection and analysis  Collecting and analysing the data  What data we have collected  Methodology  Issues and challenges  Anticipated issues that will need to be addressed  Next steps

40 Next steps  Submission to UKSG of final report from John and Laura Cox – end of July 2010  This report will:- –Outline the various metrics assessed –Recommend which of them prove consistent and robust enough to be adopted for scaled up onward monitoring –Suggest any ways in which data providers might amend the way they capture, structure, label, and maintain their data which would make the measurement of Usage Factors:-  Easier  More reliable –Propose ways to audit Usage Factors for accuracy

41  UKSG Research Committee will consider the report and decide whether it justifies seeking funding for a further (third) phase for the Project

42 UKSG Usage Factor Phase 3  Scaled up testing of candidate metric(s) recommended in Cox report  Address outstanding issues revealed during the course of the project so far  In collaboration with data suppliers, develop agreed standards and templates which, going forward, will streamline the process of data collection and analysis  More detailed practical recommendations for a cost- effective infrastructure to manage the Usage Factor process.

43 UKSG Usage Factor Project  Many thanks to the sponsors of this latest phase:-  GOLD  SILVER –ALPSP –American Chemical Society –STM –Nature Publishing Group –Springer

44 Thank you for your attention!


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