JUSP - The JISC Journal Usage Statistics Portal Ross MacIntyre, Mimas The University of Manchester

Timeline 1998 Nesli 2000 UKSG w/shop 2002 COUNTER* 2003 *J&Db[R1] 2004 Evidence Base report: Nesli2 Analysis of Usage Statistics 2005 *J&Db[R2] 2006 Key Perspectives report: Usage Statistics Service Feasibility Study 2007 Content Complete report: JUSP Scoping Study 2008 JISC ITT: JUSP Scoping Study 2 *J&Db[R3] 2009 JUSP Report 2010 April JISC fund JUSP to service Areas for Discussion Different perspectives: Publishers, Aggregators, Learning Institutions, Commercial Organisations, Product Vendors... What do you want to monitor & why? What is usage? Are you getting enough? What are you supplying/gathering? What do you do with it? What is your holy grail? JISC Collections USAGE STATISTICS PORTAL SCOPING STUDY: PHASE ii TECHNCIAL DESIGN AND PROTYPING INVITATION TO TENDER Summary 1.This invitation to tender invites bidders to submit proposals to undertake to the technical design and prototyping for a Usage Statistics Portal 2.The deadline for proposals is 12:00 noon on Monday 14 July The work should start no later than end of July The work a detailed technical specification and design for the Usage Statistics Portal, and a scoping of costs required to bring it to production, and final report should be complete by 1st March 2009.

Mission to assist and support libraries in the analysis of NESLi2 usage statistics and the management of their e-journals collections. 20+ NESLi2 e-journal deals/Publishers 130+ HEIs taking up NESLi2 deals 3 Intermediaries (gateway/host)

JISC JUSP service Refine user requirements for usage portal Develop portal in line with requirements To be based on COUNTER usage reports: JR1 (total number of full-text article requests) JR1A (requests from archives or backfiles) Harvest usage statistics via SUSHI JR1 = Number of Successful Full-Text Article Requests by Month and Journal JR1a = Number of Successful Full-Text Article Requests by Month and Journal for a Journal Archive JR2 = Turnaways by Month and Journal JR3 = Number of Successful Item Requests and Turnaways by Month, Journal and Page Type JR4 = Total Searches Run by Month and Service JR5 = Number of Successful Full-Text Article Requests by Year of Publication and Journal DB1 = Total Searches and Sessions by Month and Database DB2 = Turnaways by Month and Database DB3 = Total Searches and Sessions by Month and Service

Technical – conversion from.xls

Technical – conversion to.xml

DEMO of JUSP

1. Single point of access to all JR1 and JR1A usage statistics as currently downloaded individually from publisher websites User informational text From this page, you can download JR1 and JR1A (archive) reports. You can select data from & to Interface shows Report – drop down list (JR1 (all), JR1A (archive only) Publisher – drop down list Date Span – from Month & Year – to Month & Year

2. Addition of host/gateway JR1 statistics where relevant User informational text To get a full picture of usage you may need to add usage statistics provided by other services such as Swetswise. This will depend on the publisher. Select publisher and date range to download JR1 reports with Ingenta, Swetswise, Ebsco EJS etc included where appropriate. Interface shows Report – drop down list (JR1 (all)) Publisher – drop down list Date From (m/y) & To (m/y)

3. Excluding usage of backfile collections User informational text JR1 reports include all usage. Some publishers also produce JR1A reports which give only usage of their archive or backfile collections. If you have access to these, you can download here reports that exclude backfile use and show only usage of current titles. Interface shows Publisher – drop down list Date From (m/y) & To (m/y) Data processing notes Titles in JR1 and JR1A matched by ISSN. JR1A usage subtracted from JR1.

4. SCONUL Return (Society of College, National and University Libraries) User informational text Use this data for SCONUL return, which requires total use by Publishers by Academic Year. These tables are used to look at usage trends over time, and to compare usage of the various publisher deals. Interface shows Publisher – drop down list Academic year

5. Summary table to show use of host/gateways User informational text Use this table to see how much of your total usage goes through intermediaries, e.g. Ingenta and Swetswise Interface shows Publisher – drop down list Calendar Year(s) Data processing notes Separate columns for publisher, gateway, host and total. JR1 usage shown in each. Percentage use from each source calculated.

6. Summary table to show use of backfiles User informational text Use this table to see how much of your total usage comes from backfiles Interface shows Publisher – drop down list Calendar Year(s) Data processing notes JR1 total including intermediaries. Shows percentage of total JR1 usage that comes from JR1A.

7. Some more figures [sic] User informational text Find the average, median, (monthly) maximum number of requests, standard deviation and variance. Interface shows Publisher – drop down list Calendar year(s)

8. Which titles have the highest use? User informational text Find the (20) titles which have the highest use Interface shows Publisher – drop down list Calendar year(s) Display (20) titles with the highest usage, including publisher, title, issn, no. of requests (descending order).

9. Tables and graphs User informational text See your monthly or annual usage over time as a chart Interface shows Publisher – drop down list Calendar years Data processing notes Show table of monthly totals for each year Draw line graph

10. Benchmarking User informational text Compare usage with others in the same JISC band Interface shows Publisher – drop down list Calendar year(s) JISC Band (A-J & All) Data processing notes Give total for all libraries in the JISC band and average.

Usage Statistics Portal: Benchmarking functionality 76 Institutions responded to our short survey in reference to the usage statistics portal (benchmarking functionality). Our findings are as detailed below. Question 1: How useful would it be for you to benchmark your institutions journal usage for each individual NESLi2 publisher against that of other HE institutions? (76 responses) 38 / 76 (50%) = Very useful 36 / 76 (47.4%) = Somewhat useful 2 / 76 (2.6%) = Not useful JISC Collections Benchmarking Survey – March 2010

Question 5. Regarding questions 2-4 above, please indicate which would be your preferred choice regarding benchmarking (74 responses) 37 / 74 (50%) = Named institution 23 / 74 (31.1%) = Listed anonymously (same JISC band) 14 / 74 (18.9%) = Average usage by institutions in the same JISC Band

Questions 10: Regarding questions 7-9 above, which would be your preferred choice? (74 responses) 37 / 74 (50%) = Being anonymised within my JISC Band 30 / 74 (40.5%) = Other institutions being able to see my institution's name 7 / 74 (9.5%) = Being part of an average figure for the Band I am in

Question 6. Is there any other benchmarking criteria you would like to see? Same mission group Select our own particular subset of named institutions Similar size and structure Usage, spend and budget for resources Cost per download & cost per FTE - Student and Staff at department / subject level SCONUL divisions (RLUK, old, new, collHE) and by area Scotland / Wales would also be useful Trend over a period of years

Question 11: Please add any additional comments you would like to make If OK with the licence then comparing named institutions would be best/ Happy to be named if all institutions are named Averages are not helpful unless accompanied by other institutional data. Anonymised usage figures would be more useful Institutions within the same JISC Band can vary widely (e.g. do they have a medical school, do they still have a chemistry dept) so you really need the institution name to give any sort of useful benchmarking. Pulling data like FTE and RAE would save us all from having to do that ourselves. Would be useful for NESLi2, however the majority of our deals are outside NESLi2

Participation Agreement - Library 3.PERMITTED USES/ACTIVITIES 3.1The Institution hereby agrees to: permit the Consortium to include its COUNTER-compliant Usage Statistics in the database created for the Journal Usage Statistics Portal Service; permit the Consortium to display the COUNTER-compliant Usage Statistics via the Journal Statistics Portal Service; permit the Consortium to show the COUNTER-compliant Usage Statistics to other participating libraries in the Journal Usage Statistics Portal Service for benchmarking purposes; and be identified in the Journal Usage Statistics Portal Service by: (1) institutional name; (2) JISC Band and (3) institutional group.

Participation Agreement - Library 4.RESPONSIBILITIES OF THE CONSORTIUM 4.1The Consortium agrees to: only provide access to any COUNTER-compliant Usage Statistics collected by the Consortium to authorized users from other participating institutions in the Journal Usage Statistics Portal Service and the Consortium partners; use authentication for access to the Journal Usage Statistics Portal Service; and permit JISC Collections to use the COUNTER-compliant Usage Statistics in the Journal Usage Statistics Portal Service database for negotiation purposes with publishers within the framework of NESLi2.

Participation Agreement – Publisher/Intermediary 3.PERMITTED USES/ACTIVITIES 3.1The Publisher hereby agrees to: provide the Consortium with the COUNTER Usage Statistics of the Institutions, including by using the SUSHI Protocol; 3.1.2permit the Consortium to include the collected COUNTER- compliant Usage Statistics in the database created for the JISC Journals Statistics Portal Project; 3.1.4permit the Consortium to show all COUNTER-compliant Usage Statistics to any NESLi2-eligible Institutions for their own usage assessment and for benchmarking their own usage against that of other Institutions; permit the Institutions to use the information in the JISC Journals Statistics Portal for their SCONUL returns and any other uses agreed between the Publisher and the Consortium; provide the Consortium with usage statistics which are in compliance with the latest COUNTER guidelines; and implement the SUSHI Protocol.

Some slight modifications…

SUSHI Processing OUP –Of the 51 sites now signed up, 24 had 2010 data from OUP but no 2009 data. SUSHI used to collect 12 months worth of JR1 and JR1a data for these sites. –(24 sites x 12 months x 2 files per month = 576 files.) –Total time to collect files from OUP - 25 minutes –Total time to quality check them - 15 minutes –Total time to load them - 20 minutes –Total processing time for 2009 data for OUP for 24 sites - 1 hour Publishing Technology –2009 data collected, processed and loaded for 25 institutions. –Total time required: 17 minutes AIP –15 sites now have complete 2009 data loads for AIP. This involved the collection, processing and loading of 180 sushi files took just under 25 minutes.

Observations SUSHI – rare indeed! NIL Upload of publisher price lists – lack of machine-readable sources (why not ONIX Serials – SPS?) Authority files to populate the Journal and Supplier tables Subject categorisation of journals

Authentication/Authorisation UK Access Management Federation eduPersonScopedAffiliation: or eduPersonEntitlement:

Final Observations Open Source – available to institutions or other consortia Complementary not in competition with licensed software offerings

Q&A This artwork by ADA+Neagoe, originally published in Omagiu Magazine.ADA+NeagoeOmagiu

Raptor Athens -> Shibboleth = loss of stats Stats important for making budgetary decisions about eResources Raptor is a Java based AuthN system log file parser Shibboleth, Ezproxy and OpenAthens Future release may see some integration directly in Shibboleth Designed for non technical users. But will have technical components. Statistics per institution as well as aggregated to higher levels e.g. UK federation

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