california digital library niso standardized usage statistics harvesting initiative (sushi): z39.93...

California Digital Library

NISO Standardized Usage Statistics Harvesting Initiative (SUSHI):

Z39.93

Chan Li


ALA Midwinter 2009


Agenda

• SUSHI: What it is and Isn’t• Why is SUSHI important• SUSHI/COUNTER relationship• How does SUSHI work and how to implement

SUSHI• How does CDL deal with usage statistics• What have we accomplished and Next Steps• Discussion?


SUSHI: What it is and Isn’t

• What it is:– A web-services model for

requesting data• Replaces the user’s need to

download files from vendor’s website

– SUSHI schema is to define the expected values that move from one place to another

• What it isn’t:

– A model for counting usage statistics (that's what the COUNTER Code of Practice does)

– A usage consolidation application

Slide courtesy of Adam Chandler, Cornell University Library

SUSHI---Standardized Usage Statistics Harvesting Initiative


Why is SUSHI important?• As the usage data continues to proliferate, libraries are still

managing the usage data by hand and SUSHI is going to solve the difficult usage data collection/management problem without human intervention.

• SUSHI is a collaboration initiative that builds on and reinforces COUNTER standard work.

o SUSHI is now capable of supporting any of COUNTER reports in Release 3, including the consortium reports

o SUSHI support becomes a requirement for COUTNER Code of Practice compliance In Release 3.


COUNTER/SUSHI relationshipDate Standard Event

January 2003 COUNTER COP 1 for journals and databases

April 2005 COUNTER COP 2 for journals and databases

Feb 2006 NISO SUSHI Version 0.1 of the SUSHI schema (proof of concept)

September 2006 NISO SUSHI Version 1.0 of the SUSHI schema: Draft Standard for Trial Use, NISO Z39.93-200X

October 2007 NISO SUSHI Version 1.5 of the SUSHI schema: ANSI/NISO Z39.93-2007

July 2008 COUNTER COP 3 for journals and databases

November 2008 NISO SUSHI a) Version 3.0 of the COUNTER Code of practice XML Schema; b) Version 1.6 of the SUSHI schema

Slide courtesy of Adam Chandler, Cornell University Library


Technically, how does SUSHI work

Usage Consolidation Application / ERM

Content Provider

Usage Reports

SOAP

SUSHI Request for COUNTER

report

SUSHI Response with COUNTER report in

XML format

SUSHI simplifies the work by automatically connecting the Usage Consolidation Application with a content provider

SUSHI Client

SUSHI Server


Implementing SUSHI• SUSHI is not a stand-alone application, it works with

another system to retrieve COUNTER usage reportso SUSHI Client on the library’s server / usually integrated with an

ERM systemo SUSHI server on content provider’s system

• COUNTER reports need to be loaded into another system for processing and reporting

• For SUSHI to be effective, a Usage Management system must be in place


How does CDL deal with usage statistics

• Usage statistics is one of the major measures used at CDL to evaluate journals / databases performance

Annual usage statistics collection project for major journal packages and databases licensed by UC libraries

Data analysis for the e-resources when we have ad-hoc packages review projects: usage data, cost per use, citation data, Bergstrom-McAfee data, UC publication data, cost per article, use per article, etc.

• Downloading usage stats for 10 UC campuses and merging the usage stats with other data points are time consuming.

ScholarlyStats serviceManually manage the usage stats for the rest of the resources


Data analysis for Publisher A

• ISSN• Journal Title• List Price• Coverage begin date• Broad Subject Category• Average Annual list price increase• Relative cost index from Bergstrom-McAfee

database• Value from Bergstrom-McAfee database• Impact Factor

• No. of articles published by UC authors• UC aggregated usage data• Usage % change from previous year• Cost per Use• 10 Campuses usage data


How will COUNTER and SUSHI help us • Consortium Reports required by COUNTER Release 3 of the Code of

Practice: – Full text requests by title and searches by database with breakdown by

consortium member

– A single login for all the consortium accounts

• We are going to test the SUSHI loads through our ERM implementation


Committee membership• Adam Chandler (co-chair), Cornell University

Library• Oliver Pesch (co-chair), EBSCO Information

Services• Nettie Lagace, Ex Libris, Inc.• Hana Levay, University of Washington Libraries• Chan Li, California Digital Library• and lots of help from NISO staff• Call for more members?


Let’s take a look at SUSHI website and what we have accomplished in

the past


SUSHI Web Site (http://www.niso.org/workrooms/sushi)

Data value registry

Annotated diagrams

SUSHI Compliance List


Next steps

• Continue to refine documentation and support• Track content provider implementations through

COUNTER Code of Practice Release 3 compliance auditing process. Deadline is August 31, 2009


Next Steps for YOU

• For Consolidators & Content Providers:

Implement! Implement! Implement!

• For Librarians:

Support! Support! Support!


Discussion:

•What are your experiences working with COUNTER reports and at your library, how do you use the usage data in the decision making process?

•What are your experiences working with SUSHI?


Thank You

[email protected]

california digital library niso standardized usage statistics harvesting initiative (sushi): z39.93...

Documents

sushi sushi

sushi work slide

campuses usage data

initiative sushi

sushi website

sushi loads

usage stats

initiative slide