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Downloads and Beyond
- new perspectives on usage metrics
This panel consists of three presentations, covering different stages in the
usage by scholars of articles:
Before the download – what happens during the search process?
◦ Marie Kennedy, Loyola Marymount University, Los Angeles, CA
Download-based metrics – new usage-based measures of impact
◦ Peter Shepherd, COUNTER, UK
Beyond downloads – how are journal articles shared and used?
◦ Carol Tenopir, University of Tennessee, Knoxville, TN
New usage-based measures of
impact - Article Level Reporting and the Usage
Factor
Peter Shepherd
COUNTER
Library Assessment Conference
Seattle, 4 August 2014
COUNTER usage-based
measures in the context of
altmetrics Advantages:
Usage can be reported at the individual item and individual researcher level
Usage is more ’immediate’ than citations
Usage potentially covers all categories of online publication
COUNTER usage statistics are independently audited and generally trusted
Two new COUNTER Codes of Practice have been launched:
COUNTER Code of Practice for Articles (COUNTER Articles)
Recording, consolidation and reporting of usage at the individual article level
Standard applies to publishers, aggregators and repositories
COUNTER Code of Practice for Usage Factor
Usage-based measure of impact of journals, institutions and individual scholars
The Usage Factor for a Journal is the Median Value in a set of ordered full-text article usage data ( i.e. the
number of successful full text article requests) for a specified Usage Period of articles published in a journal
during a specified Publication Period.
COUNTER Articles and Usage Factor are both based on the recording and
consolidation of COUNTER-compliant usage data at the individual article level
COUNTER Code of Practice for
Articles
COUNTER Articles covers the following areas:
article types to be counted;
article versions to be counted;
data elements to be measured;
definitions of these data elements;
content and format of usage reports;
requirements for data collection and data processing;
requirements for independent audit (under development);
Release 1 of the COUNTER Code of Practice for Articles is available on the COUNTER website at: http://www.projectcounter.org/counterarticles.html
COUNTER Articles: data and
metadata
Publisher/aggregator organizations should collect the usage data in the format
specified in Article Report 1. The following data and metadata must be collected for
each article:
Either Print ISSN OR Online ISSN
Article version, where available
Article DOI
Date of First Successful Request
Monthly count of the number of successful full-text requests - counts must remain
available for at least 24 months from Online Publication Date OR date of First
Successful Request
The following metadata are optional, but are desirable:
Journal title
Publisher name
Platform name
Journal DOI
Article title
Article type
Article publication date
COUNTER Articles
– 3 Article Reports
Article Report 1: publisher specification for data collection
by article
To be used by publishers for the collection of data and metadata
Article Report 2: number of successful full-text article
requests by author, month and DOI, consolidated from
different sources
To be used by publishers to report individual article usage to
authors, broken down by source of usage
Article Report 3: summary of all successful full-text article
requests for an author, by month
To be used by publishers to provide a summary to authors of usage
for all their articles
Article Report 1: specification for data
collection by article
Usage Factor: aims and outcomes
The overall aim of the Usage Factor project was to explore how online journal usage
statistics might form the basis of a new measure of journal impact and quality, the
Usage Factor for journals.
Specific objectives were to answer the following questions:
Will Usage Factor be a statistically meaningful measure?
Will Usage Factor be accepted by researchers, publishers, librarians and research
institutions?
Will Usage Factor be statistically credible and robust?
Is there an organizational and economic model for its implementation that would
cost-effective and be acceptable to the major stakeholder groups.
Following extensive testing using usage data for over 200 journals from a range of
publishers the main outcome of the project has been the new COUNTER Code of
Practice for Usage Factors. This new Code of Practice uses the article level usage
data collected using the COUNTER Code of Practice for Articles as the basis for the
calculation of the Usage Factor.
The COUNTER Code of Practice for Usage Factors is available on the COUNTER
website at: http://www.projectcounter.org/usage_factor.html
Who will benefit from the Usage
Factor? Four major groups will benefit from the introduction of Usage Factors:
Authors, especially those in practitioner-oriented fields, where citation-based measures understate the impact of journals, as well as those in areas outside the core STM fields of pure research, where coverage of journals by citation-based measures is weak.
Publishers, especially those with large numbers of journals outside of the core STM research areas, where there is no reliable, universal measure of journal impact, because citation-based measures are either inadequate or non-existent for these fields
Librarians, when deciding on new journal acquisitions, have no reliable, global measures of journal impact for fields outside the core STM research fields. They would use usage-based measures to help them prioritise journals to be added to their collections.
Research Funding Agencies, who are seeking a wider range of credible, consistent quantitative measures of the value and impact of the outputs of the research that they fund.
Usage Factor metric:
recommendations
Usage Factors should be calculated using the median rather than the arithmetic
mean
A range of Usage Factors should ideally be published for each journal: a
comprehensive UF ( all items, all countable versions) plus supplementary factors
for selected items
Usage Factors should be published as integers with no decimal places
Usage Factors should be published with appropriate confidence levels around the
average to guide their interpretation
The Usage Factor should be calculated initially on the basis of a maximum usage
time window of 24 months.
The Usage Factor is not directly comparable across subject groups and should
therefore be published and interpreted only within appropriate subject groupings.
The Usage Factor should be calculated using a publication window of 2 years
Usage Factor: Journals
- the calculation
Publishers will be able to generate Usage Factors using the Code of Practice, but will
have to be independently audited for their Usage Factors to be listed in the Usage
Factor Central Registry. Two categories of Usage Factor may be calculated
The 24 month Journal Usage Factor 2010/2011: all content
The median number of successful requests during 2010/2011 to content
published in the journal in 2010/2011
The Journal Usage Factor 2010/2011: full-text articles only
The median number of successful requests during 2010/2011 to full-text
articles published in the journal in 2010/2011
Note:
1.The article-level data collected in COUNTER Article Report 1 will be used as
the basis for the Usage Factor calculation
2. Usage Factors will be reported annually, for 2010/2011, 2011/2012, etc.
COUNTER Articles and Usage
Factor - implementation
Step 1: implement COUNTER Code of Practice
for Articles
Step 2: Collect article-level usage data for
2014/2015
Step 3: Calculate and report Usage Factors
using protocols specified in Code of Practice for
Usage Factors
COUNTER Articles and Usage
Factor
Common threads
Article-based metrics • Can be rolled up to researcher, institutions and journal level
Reliable, audited data • Based on tested COUNTER standards
Common process/ infrastructure requirements • Similar metadata
• Efficient, cost-effective processes
For further information:
http://www.projectcounter.org/index.html
BEFORE THE DOWNLOAD:
THE SEARCH PROCESS FROM A
SOCIAL NETWORK ANALYSIS
PERSPECTIVE
Marie R. Kennedy David P. Kennedy Loyola Marymount University RAND Corporation
The finding
The found
TWO TYPES
OF COUNTING MECHANISMS
COUNTER
Proxy server
EVALUATION AND USE
A MODEL OF A PERSON’S
INFORMATION SEEKING
AN ALTERNATIVE
COUNTING MECHANISM
METHODS
Describe and compare 3 kinds of
measurements of electronic resource usage
Time frame: June 1, 2011-May 31, 2012
COUNTER JR1
PROXY SERVER
SOCIAL NETWORK ANALYSIS
Data extracted from Gimlet
11,444 total service point interactions
4,024 tagged as reference interactions
1,548 of the reference interactions mention an
electronic resource
SOCIAL NETWORK ANALYSIS
New data set created
1,548 of the reference interactions mention an electronic resource
Listed the resource mentioned and counted each time it was suggested
Analyzed and visualized using Ucinet, Netdraw
FINDINGS
Electronic resources and Information Desk staff, by color/shape
Core staff and electronic resources emerge
Connections between electronic resources
DISCUSSION
“Knowledge creation is not confined to
an individual, rather it is a social process
between individuals, groups and
organisations.”
(Zheng and Yano, 2007, p. 5)
FUTURE RESEARCH
Further analysis on existing data set
Kinds of e-resources suggested to kinds of
patrons
Kinds of reference desk staff suggest which kinds
of e-resources
Expand data set to include more years of data
Develop e-resource marketing plan and look at
resulting 3 kinds of usage data
SUMMARY
We find that the perspective gained from
social network analysis provides a context-
aware component that provides a fuller picture
of the “use” of electronic resources, following
the path from “finding” to “found.”
CONTACT US
Marie R. Kennedy David P. Kennedy
[email protected] [email protected]
This presentation is supported by a
Research Incentive Grant from the
William H. Hannon Library at LMU
Preliminary results of this research were presented
at the 2013 QQML Conference (Rome, Italy)
Center for Information and Communication Studies
Beyond Downloads:
How Are Journal Articles Shared and Used?
Carol Tenopir
Professor, School of Information Sciences,
University of Tennessee
Center for Information and Communication Studies
Beyond Project COUNTER
• Secondary usage
• Sharing without
downloading
Center for Information and Communication Studies
Formal sharing methods
Center for Information and Communication Studies
Informal sharing methods
Center for Information and Communication Studies
Interviews / Focus Groups
Two main types of sharing
1.
2.
Most participants who
share, uploaded their own
work into institutional or
subject repositories.
Center for Information and Communication Studies
Interviews / Focus Groups
Participants shared material to further scientific and
academic discovery, to promote their own or someone
else’s work, and to fulfill an information need.
Center for Information and Communication Studies
Overall, the project aims to: • define ways to measure non-download usage of digital
content both within and outside institutional firewalls
• evaluate the relationship between COUNTER usage and
usage of digital articles obtained through other means
• develop practical ways to estimate total digital article
usage from known downloads and non-download usage
• initiate discussion across the publisher, STM research,
and library communities regarding these issues
Center for Information and Communication Studies
Interviews / Focus Groups
• “Bootleg” sharing (e.g., email, print,
internal network): the most frequently
mentioned method of sharing.
• Twitter: the most frequently mentioned
social media tool for sharing.
• Dropbox: the most frequently mentioned
method used for sharing with collaborators.
Center for Information and Communication Studies
Survey launched soon • Population: researchers internationally
• Aim: to estimate amounts of sharing
and calculate averages that take into
account: • Multiple ways to share
• Differences in discipline
• Development of instrument underway
Center for Information and Communication Studies
Stay tuned for further
results!
Carol Tenopir
![STM [UandiStar.org]](https://img.dokumen.tips/doc/110x75/568c339a1a28ab02358d5391/stm-uandistarorg.jpg)
