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How University of Bath is using JUSP

How University of Bath is using JUSP. Lizz Jennings – Information Librarian (E-Resources) - Chartered. Before JUSP. Lists of core titles maintained, but not matched to usage Often asked to assess value of package based on statistics for whole platform

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How University of Bath is using JUSP

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  1. How University of Bath is using JUSP Lizz Jennings – Information Librarian (E-Resources) - Chartered

  2. Before JUSP • Lists of core titles maintained, but not matched to usage • Often asked to assess value of package based on statistics for whole platform • Process of lookups, manual checking, good memory • Statistics for particular title could involve visit to three or four sites to get true picture of demand

  3. Before JUSP • Financial year or most recent 12 months involved matching two sets of statistics – easy for single titles, but very time consuming for packages • Time spent cleaning data where providers have put commas in titles • Only knew of data errors if it was notified on mailing lists

  4. Data analysis • Providing analysis of package deals meant bringing together data from three or four different sources: • Usage (one, two or more years) • Core titles / Package titles • Cost information • May not have identifiers (e.g. ISSN) • May not identify usage from third parties • May not take into account use of archives • Changes to requirements meant repeating this process

  5. Spreadsheet of core vs package titles pre-JUSP LOOKUP from publisher stats LOOKUP from collection title list LOOKUP from internal core title list

  6. Spreadsheet of core vs package titles in JUSP Same data, single download

  7. After JUSP • Lists of core titles maintained and attached to usage • Can compare in single report value of package compared to core titles • Once entered, core title lists just need copying (usually done same day on request to JUSP team) and updating • Individual title statistics usually include intermediaries such as Jstor

  8. After JUSP • Easy to obtain reports for different time periods, and data is checked so matching lists is easy. • Data checked by JUSP team so errors and discrepancies are noticed and corrected/withdrawn quickly • Can quickly obtain individual title stats for most major publishers from single site – perfect when checking subject lists

  9. Data analysis • Providing analysis of package deals means matching cost with a list already including usage and titles • Has consistent identifiers • Identifies usage from third parties • Includes use of archives • Easy to gather same information for previous years

  10. Plans for 2013 • Investigate use for SCONUL returns • Possibility of providing standardised package assessments • Analysis of backfile usage

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