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This project update discusses the progress of the Usage Factor Project, including data harmonization and analysis of journal usage data from multiple publishers, aggregators, and hosting services. Key data issues addressed include consistency in numerator/denominator, defining article usage year and publication date, and different usage patterns by subject. The update also outlines the data analysis and modeling process, recommendations for metrics adoption, and proposals for improving data capture and maintenance. For more information, visit http://www.uksg.org/usagefactors.
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The Usage Factor ProjectUpdateRichard Gedye, Research Director, Oxford Journals UKSG ConferenceTorquay 31 March – 2 April 2009
Usage Factor = Total usage over period ‘x’ of articles published during period ‘y’ Total articles published during period ‘y’
Preparing and harmonising data for analysis • Journal usage data from multiple publishers to be ingested and analysed by expert third party • 6 publishers • 1 aggregator • 1 hosting service • All interested in the insights to be gained from contributing data to the project
Key Data Issues • Consistency – numerator/denominator • Defining article usage year • Defining article publication date • Different usage patterns by subject
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.
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
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
Key Data Issues • Consistency – numerator/denominator • Defining article usage year • Defining article publication date • Different usage patterns by subject
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
Key Data Issues • Consistency – numerator/denominator • Defining article usage year • Defining article publication date • Different usage patterns by subject
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
Key Data Issues • Consistency – numerator/denominator • Defining article usage year • Defining article publication date • Different usage patterns by subject
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)
With key data issues addressed, we have developed a specification for the report via which participating publishers will transfer their usage data to the appointed third party for analysis
Data Analysis and Modelling • Using the data provided, the appointed contractor will produce a report which 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
Usage Factor Project • More information at:- • http://www.uksg.org/usagefactors • Or contact:- Richard Gedye richard.gedye@oxfordjournals.org