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IGeLU 2014

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Presentation at IGeLU 2014

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IGeLU 2014

  1. 1. Analytics @ Lancaster University Library IGeLU 2014 John Krug, Systems and Analytics Manager, Lancaster University Library http://www.slideshare.net/jhkrug/igelu-analytics-2014
  2. 2. Lancaster University, the Library and Alma • We are in Lancaster in the UK North West. • ~ 12,000 FTE students, ~ 2300 FTE Staff • Library has 55 FTE staff, building refurbishment in progress • University aims to be 10, 100 – Research, Teaching, Engagement • Global outlook with partnerships in Malaysia, India, Pakistan and a new Ghana campus • Alma implemented January 2013 as an early adopter. • I am Systems and Analytics Manager, at LUL since 2002 to implement Aleph – systems background, not library • How can library analytics help?
  3. 3. Alma Analytics reporting and dashboards • Following implementation of Alma, analytics dashboards rapidly developed for common reporting tasks • Ongoing work in this area, refining existing and developing new reports
  4. 4. Results
  5. 5. Fun with BLISS B Floor 9AZ (B) 347 lines of this!
  6. 6. Projects & Challenges • LDIV – Library Data, Information & Visualisation • ETL experiments done using PostgresQL and Python • Data from Aleph, Alma, Ezproxy, etc. • Smaller projects: • e.g. Re-shelving performance – required to use Alma Analytics returns data along with the number of trolleys re-shelved daily. • Challenges – Infrastructure, Skills, time • Lots of new skills/knowledge needed for Analytics. For us : Alma analytics (OBIEE), python, Django, postgres, Tableau, nginx, openresty, lua, json, xml, xsl, statistics, data preparation, ETL, etc, etc, etc
  7. 7. Alma analytics data extraction • Requires using a SOAP API (thankfully a RESTful API is now available for Analytics) • SOAP support for python not very good, much better with REST. Currently using the suds python library with a few bug fixes for compression, ‘&’ encoding, etc. • A script get_analytics invokes the required report, manages collection of multiple ‘gets’ if the data is large and produces a single XML file result. • Needs porting from SOAP to REST. • Data extraction from Alma Analytics is straight forward, especially with REST
  8. 8. Data from other places • Ezproxy logs • Enquiry/exit desk query statistics • Re-shelving performance data • Shibboleth logs, hopefully soon. We are dependent on central IT services • Library building usage counts • Library PC usage statistics • JUSP & USTAT aggregate usage data • University faculty and department data • Social networking • New Alma Analytics subject areas, especially uResolver data
  9. 9. Gaps in the electronic resource picture • Currently we have aggregate data from JUSP, USTAT • Partial off campus picture from ezproxy, but web orientated rather than resource • Really want the data from Shibboleth and uResolver • Why the demand for such low level data about individuals?
  10. 10. The library and learner analytics • Learner analytics a growth field • Driven by a mass of data from VLEs and MOOCs …. and libraries • Student satisfaction & retention • Intervention(?) • if low(library borrowing) & low(eresource access) & high(rate of near late or late submissions) & low_to_middling(grades) then do_something() • The library can’t do all that, but the university could/can • Library can provide data
  11. 11. The library as data provider • LAMP – Library Analytics & Metrics Project from JISC • http://jisclamp.mimas.ac.uk • We will be exporting loan and anonymised student data for use by LAMP. • They are experimenting with dashboards and applications • Prototype application later this year. • Overlap with our own project LDIV • The Library API • For use by analytics projects within the university • Planning office, Student Services and others
  12. 12. The Library API • Built using openresty, nginx, lua • Restful like API interface • e.g. Retrieve physical loans for a patron • GET http://lib-ldiv.lancs.ac.uk:8080/ploans/0010215?start=45&number=1&format=xml (or json) <?xml version="1.0" encoding="UTF-8"?> <response> <record> <call_no>AZKF.S75 (H)</call_no> <loan_date>2014-07-10 15:44:00</loan_date> <num_renewals>0</num_renewals> <bor_status>03</bor_status> <rowid>3212</rowid> <returned_date>2014-08-15 10:16:00</returned_date> <collection>MAIN</collection> <rownum>1</rownum> <material>BOOK</material> <patron>b3ea5253dd4877c94fa9fac9</patron> <item_status>01</item_status> <call_no_2>B Floor Red Zone</call_no_2> <bor_type>34</bor_type> <key>000473908000010-200208151016173</key> <due_date>2015-06-19 19:00:00</due_date> </record> </response> [{ "rownum": 1, "key": "000473908000010-200208151016173", "patron": "b3ea5253dd4877c94fa9fac9", "loan_date": "2014-07-10 15:44:00", "due_date": "2015-06-19 19:00:00", "returned_date": "2014-08-15 10:16:00", "item_status": "01", "num_renewals": 0, "material": "BOOK", "bor_status": "03", "bor_type": "34", "call_no": "AZKF.S75 (H)", "call_no_2": "B Floor Red Zone", "collection": "MAIN", "rowid": 3212 }]
  13. 13. How does it work? • GET http://lib-ldiv.lancs.ac.uk:8080/ploans/0010215?start=45&number=1&format=xml • Nginx configuration maps REST url to database query location ~ /ploans/(?<patron>w+) { ## collect and/or set default parameters rewrite ^ /ploans_paged/$patron:$start:$nrows.$fmt; } location ~ /ploans_paged/(?<patron>w+):(?<start>d+):(?<nrows>d+).json { postgres_pass database; rds_json on; postgres_query HEAD GET " select * from ploans where patron = $patron and row >= $start and row < $start + $nrows"; }
  14. 14. Proxy for making Alma Analytics API requests • e.g. Analytics report which produces • nginx configuration location /aa/patron_count { set $b "api-na.hosted.exlibri … lytics/reports"; set $p "path=%2Fshared%2FLancas … tron_count"; set $k "apikey=l7xx6c0b1f6188514e388cb361dea3795e73"; proxy_pass https://$b?$p&$k; } • So users of our API can get data directly from Alma Analytics and we manage the interface they use and shield them from any API changes at Ex Libris.
  15. 15. Re-thinking approaches • Requirements workshops • Application development • Data provider via API interfaces • RDF/SPARQL capability • LDIV – Library Data, Information and Visualisation • Still experimenting • Imported data from ezproxy logs, GeoIP databases, student data, primo logs, a small amount of Alma data • Really need Shibboleth and uResolver data • Tableau as the dashboard to these data sets
  16. 16. Preliminary results More at http://public.tableausoftware.com/profile/john.krug#!/
  17. 17. • First UK Analytics SIG meeting Oct 14 following EPUG-UKI AGM • Questions?
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    Dec. 1, 2017

Presentation at IGeLU 2014

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