discovery impact erl2014

Not always discovered: Phase two of a study of the effect of discovery systems on online (journal) usage

ER&LMarch 18, 2014

Michael Levine-Clark, University of DenverJohn McDonald, University of Southern California

Jason Price, SCELC Consortium

http://bit.ly/discovery-impact-erl2014

“…a steep increase in full text downloads and link resolver click‐throughs suggests Summon had a dramatic impact on user behavior and the use of library collections during this time period.”

The Impact of Web-scale Discovery on the Use of a Library CollectionDoug Way (2010) http://scholarworks.gvsu.edu/library_sp/9/

http://www.oclc.org/partnerships/econtent/solutions.en.html

Vendor marketing

Does implementation of a discovery service impact usage of publisher-

hosted journal content?

Publisher-hosted journals are only part of the picture

eBooks, pBooks, aggregator journal content, etc.publisher journal contentThe six publishers in this study

What did we measure?

• Whether there is an effect

• NOT why that effect exists (that’s a future study!)

• “Society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why, but only what”

• (Cukier & Mayer-Schonberger. 2013. Big data: A revolution that will

transform how we live, work, and think.)

Data collection• List of libraries with discovery services

>Searched on lib-web-cats

• Surveyed Libraries>Discovery service Implemented>Implementation Date (month/year)>Search box location>Marketing effort

• 149 Libraries Gave Approval>33 libraries selected for this phase>6 for each of the 4 major discovery services and a

group of 9 libraries with no service

Dataset• 33 Libraries

– 28 US, 2 CA, 1 each from UK, AUS, NZ

–WorldCat book holdings>Average: 1,114,193 ; Range: ~300k to ~2.6mil

• Implementation dates (Discovery Libraries): >2010 (3), 2011 (19), 2012 (2)

• 6 Publishers

• 9,206 Journals

• 163,545 Usable Observations

Methodology

Compared COUNTER JR1 total full text article views for the

12 months before vs 12 months after implementation date

June

201

0St

art

Impl

emen

tatio

nM

ay 2

011

May

201

2En

d

Year 1 Year 2

Included implementation month in Year 1 to ensure that both periods included an entire academic year

Examine Data for Outliers

Observations by Library & Service

Observations by Publisher

Average Usage Change By Discovery & Publisher

Analyzing Usage Change: % vs Total

Use 12 months before

Use 12 months

after% Change Total

Change

Journal A 500 600 20% 100

Journal B 5 15 200% 10

Which is the better measure?

Is it the same for publisher- & journal-level data?

Reducing variation due to institution sizeCurrently converting to change per FTE

Values are shown as x 1,000 to bring the change metric back per journal-library combination to a minimum of 0.1

2013 JISC Discovery study took a similar approach

Average Usage Change By Discovery & Publisher

Per Journal & Per 10,000 FTE

Full Model

Including Discovery Service, Publisher, and Library

Including Discovery Service, Publisher, and Library

Nested ANOVA Model

[all three factors – preliminary results]

Does usage change vary across libraries?

Institution (sorted by Mean Change)

Does usage change vary across libraries using the same service?

Library 10-15 Library 16-21 Library 22-27 Library 28-33Library 1-9

Does usage change vary across publishers?

Publisher (sorted by Mean Change)

B

AAA A A

Does usage change vary across discovery services?

A

BB

C

D

Publisher

Does the effect of discovery service differ across publishers?

ResultsCan we detect differences between Discovery Services, Publishers, and/or Libraries and/or their interactions? • Library – Yes• Publisher – No• Discovery Service – Yes

• Differential discovery service effect by publisher – Yes

Next Steps• Design & test for effects of:

–Aggregator full text availability–Publisher Size–Journal Subject–Overall usage trends (Requires Disc Srvc ‘control’)–Configuration options in Discovery services

• Expand pool of libraries• Perhaps explore WHY

Sharing Data• With participating libraries

–Customized reports for each library• With participating publishers

–Customized reports for each publisher–Presentations as requested

• With discovery vendors–Presentations as requested

• In publications and presentations–Maintaining anonymity of data

Past/Future Presentations• Ithaka Sustainable Scholarship Conference (October 2013)• Charleston Conference (November 2013)• ER&L/Library Journal Webinar (December 2013)• Shangai Jiao Tong Univ / Beijing Univ Forum (Jan 2014)• SCELC Colloquium (March 2014)• ER&L (March 2014) http://bit.ly/discovery-impact-erl2014 • UKSG (April 2014)• Presentations posted on slideshare :

–http://visualcv.com/lpq4t1s

michael.levine-clark@du.edu | johndmcd@usc.edu | jason@scelc.org