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EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition
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EVA (ErwerbungsVorschlags-Assistant) assists in collection building! Using ILL data for patron-driven acquisition

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The “ErwerbungsVorschlags-Assistant” (EVA) explores the methodology of patron driven …

The “ErwerbungsVorschlags-Assistant” (EVA) explores the methodology of patron driven
acquisition in regard to printed material, specifically interlibrary loan requests. The
requests are automatically compared to specific criteria in regard to their suitability as
an acquisition, enriched with external data and presented to the appropriate subject
librarian. Since October 2011, EVA is in production with several German university
libraries. This paper describes the project and its underlying concepts.

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  • 1. EVA assists in collection-building! Using ILL data for patron-driven acquisition Dr. Ania López, UB Duisburg-Essen Peter Mayr, hbz KölnIFLA World Library and Information Congress 2012 122. Mai 2012
  • 2. ErwerbungsVorschlagsAssistent 2
  • 3. Agenda● Motivation● Opportunity● Results● EVA in practice● Reactions 3
  • 4. Motivation 4
  • 5. Interlibrary-loans canhighlight deficits in localholdings 5
  • 6. 6
  • 7. Tear down this wall! 7
  • 8. Opportunity 8
  • 9. Basic Concepts9 ● Avoid “unnecessary” ILL requests ● Simple and comfortable use for the subject librarians ● General Approach
  • 10. Solution10 ● „Intercept“ ILL requests that meet specific criteria ● Waiting period, in which the decision ILL/acquisition is made
  • 11. 11
  • 12. Alternative Workflow12 ● Subsequent use of ILL data
  • 13. 13
  • 14. Results 14
  • 15. Project ResultsPrototype with 3 modules:● Automatic Analysis of ILL requests● Admin-Interface● Tracking-Interface 15
  • 16. Automatic Analysis of ILL Data16 ● General criteria ● e.g. availability in the book trade ● Specific criteria per institution ● e.g. year of publication, language ● Subject classification by the patrons ● Waiting period or parallel request
  • 17. Automatic Analysis of ILL requests 17
  • 18. Admin-Interface18 ● Manage subjects ● Adjust waiting period ● Activate email notification ● Requests ● Transfer to acquisitions ● Export as CSV ● Initiate ILL
  • 19. Admin-Interface 19
  • 20. Admin-Interface 20
  • 21. ILL-Server 21
  • 22. Tracking-Interface22 ● EVA-Id ● Status in discovery system
  • 23. Tracking-Interface 23
  • 24. Tracking-Interface 24
  • 25. In der Praxis EVA In Pr actice 25
  • 26. EVA In Practice26 23 libraries 167 subject librarians 48,000 EVA requests
  • 27. Reactions Reaktionen 27
  • 28. 28
  • 29. Reactions29 „In our daily work, acquisitions and inter- library-loan are, in my opinion, not competitors, but two tools towards a common goal: providing information for patrons“
  • 30. Reactions30 „EVA is – within means - a useful tool for adjusting, according to our needs, the balance between two modes of providing print materials (acquisitions and ILL)“
  • 31. Reactions31 „EVA is helpful as an additional means for collection building“
  • 32. Reactions32 „the EVA module in some cases allows integrated work flows between ILL department and the subjects librarians resp. the acquisition department”
  • 33. Reaktionen33 “I find EVA useful as a tool providing information about the topics and titles that are of interest to our patrons” “Even if I can only buy few titles due to budget restrictions, I wouldnt want to go without EVA.”
  • 34. 34 Pr eliminar y Figures
  • 35. Preliminary Figures35 “In July 2012, out of 1,112 monograph orders, 106 originated in EVA (9.5%)”
  • 36. Preliminary Figures36 “Since October 2011, 318 titles (of 1,302 EVA requests) have been transferred to the acquisitions department. That means roughly one in four ILL orders that meet the criteria and have been halted for consideration is purchased.”
  • 37. Fazit Conclusion 37
  • 38. Peter Mayrmayr@hbz-nrw.de@hatorikibbleDr. Ania López 38ania.lopez@uni-due.de
  • 39. Credits● Wikipedia Commons ● Folie 2: http://commons.wikimedia.org/wiki/File:Albrecht_ Dürer_002.jpg● Flickr Creative Commons Pool ● Folie 5:http://flic.kr/p/8vAkkF ● Folie 7: http://flic.kr/p/5Z7Shd ● Folie 14:http://flic.kr/p/5JE4z7 ● Folie 26: http://flic.kr/p/8pusbC ● Folie 28: http://flic.kr/p/5Eyjt2 ● Folie 34: http://flic.kr/p/9UAzzu● Sonstiges ● Folie 38: http://www.public-domain-image.com/objects-public-domain-images-pictures/too 39

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