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Analytics @ Lancaster University Library 
IGeLU 2014 
John Krug, Systems and Analytics Manager, Lancaster University Library 
http://www.slideshare.net/jhkrug/igelu-analytics-2014
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?
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
Results
Fun with BLISS 
B Floor 9AZ (B) 
347 lines of this!
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
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
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
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?
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
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
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 
}]
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"; 
}
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.
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
Preliminary results 
More at http://public.tableausoftware.com/profile/john.krug#!/
• First UK Analytics SIG meeting Oct 14 following EPUG-UKI AGM 
• Questions?

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IGeLU 2014

  • 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. 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. 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
  • 5. Fun with BLISS B Floor 9AZ (B) 347 lines of this!
  • 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Preliminary results More at http://public.tableausoftware.com/profile/john.krug#!/
  • 17. • First UK Analytics SIG meeting Oct 14 following EPUG-UKI AGM • Questions?