Emerging Technology in Usage Statistics:

COUNTER and SUSHI

Library lives in the E-Environment E-Everything, slogan challenge to

library for make most of the information resources in digital form.

Librarians have long experience on evaluating library resources through various methods traditionally, such as reshelving statistics and the circulation list.

Publisher evaluate resources based on their subscription data with advantage of electronic resources.

Growing library services continue to change and diversify with expansion into the electronic environment; assessing usage of library resources has become more complex.

In March 2002, Project COUNTER was launched “as an international initiative, librarian, publishers and intermediaries collaborated to setting standards for the recording and reporting of usage statistics in a consistent, credible and compatible way.”

So Cost per article can be calculated which can given indication of the relative value of the journal and in the era of budget cutting the return on investment can be calculated.

The usage statistics generally refer to the indicators of the volume of user access to electronic resources and services available from content providers or vendors. [Shim & McClure (2002)]

Examples of indicators includes: a count of sessions is a specific database, the time per session in a specific

database, the count of searches performed, the number of times full-text documents

are downloaded

Use and usage of E-Journal is not visible like Print journals.

E-Journals are needed to demonstrate to funding agencies what they are getting for their investments or the latest canopy of Return on investment policy.

For collection development usage statistics are really needed for making decision to decide what to cancel, what to buy less of, and what kinds of E-Journals are needed.

Librarians need the data to know what to promote, for which databases might patrons need more help in using.

License negotiators need data to give them informed leverage for subsequent negotiations.

Understanding some old rules of thumb like the 80/20 rule in the new digital environment.

Defining Terms Used in Usage Statistics Report

Data Processing and Auditing by approved 3rdParty

Only intended usage should be recorded and all requests that are not intended by the users should be removed.

All double clicks on an http link within 10 seconds of each other will be counted as only one request.

Where a PDF is involved, this filter is set at 30 seconds, due to the longer time it takes to render a PDF.

The first Standardized Usage Statistics Harvesting Initiative (SUSHI) was created as ANSI/NISO Z39.93-2007 standard protocol.

Recently on March 5, 2013 NISO at Baltimore, MD announced the publication of maintenance revisions of SUSHI protocol with standard number ANSI/NISO Z39.93-2013.

This Protocol defines “an automated request and response model for the harvesting of electronic resource usage data and is required for conformance with the COUNTER Code of Practice.”

http://www.projectcounter.orghttp://www.projectcounter.org

Apply for COUNTER membership

Apply for COUNTER membership

Data value registry

Annotated diagrams

For libraries and publishers

Usage statistics are being used to inform decisions

They need to be consistent, credible and comparable =

And, easy to obtain =SUSHI

Solve the problem of harvesting and managing usage data from a growing number of providers.

Promote consistency in usage formatting (XML)

Automate the process

Who is asking for the report (requestor); Who is the report for (customer); Which dates do you want (report)

Single Code of Practice New Reports New Data Elements Gold Open Access New Metrics Types

Journal Report 3 Mobile: Number of Successful Item Requests by Month, Journal and Page Type for usage on a Mobile Device

Title Report 1 Mobile: Number of Successful Requests for Journal Full-text Articles and Book Sections by Month and Title (formatted for normal browsers/delivered to mobile devices AND formatted for mobile devices/delivered to mobile devices)

Title Report 3 Mobile: Number of Successful Requests by Month, Title and Page Type (formatted for normal browsers/delivered to mobile devices AND formatted for mobile devices/delivered to mobile devices)

Librarians are able to compare usage statistics from different

vendors; derive useful metrics such as cost-per-use; make better-informed purchasing decisions; plan infrastructure more effectively.

Publishers and intermediaries are able to: provide data to customers in a format they

want; compare the relative usage of different

delivery channels; aggregate data for customers using multiple

delivery channels; learn more about genuine usage patterns.

SUSHI was designed as a general protocol for retrieving XML “reports”

SUSHI can be used for other usage reports

SUSHI can also be used for other XML “messages”, for example, automate delivery of: Holdings data with ONIX-SOH License terms with ONIX PL

COUNTER Consortium reports Updated schema New metrics and reports

SUSHI can be expanded to harvest other data Holdings (ONIX SOH) License terms (ONIX PL) Financial terms

Tools and services to assist with data normalization E.g. XISBN, XISSN projects from OCLC

SUSHI allows to collect (and provide access to) audited COUNTER-compliant usage data on an unprecedented scale and to do so with accuracy and a high degree of reliability.

Without it, require a lot of additional staff to handle the data processing alone and requires a significant time and cost saving

It performs on the data and ensure the highest possible chance that the figures will be presented to the end-user without any problems or errors.

It provides publishers with an additional level of quality assurance.

CONCLUSION Cont…….

With the Project COUNTER

Librarians are able to compare usage statistics from different vendors; derive useful metrics such as cost-per-use; make better-informed purchasing decisions; plan infrastructure more effectively. Publishers and intermediaries are able to: provide data to customers in a format they want; compare the relative usage of different delivery channels; aggregate data for customers using multiple delivery channels; learn more about genuine usage patterns.”

Thank You