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Meeting the Challenge: Successful
Electronic Resources Management in the
Absence of a Perfect System
NISO Update on IOTA and SUSHI

Oliver Pesch
Chief Strategist, E-Resources, EBSCO Information
Services
Overview
 SUSHI
 IOTA
 Other NISO Initiatives
SUSHI
Standardized Usage Statistics Harvesting
Initiative
SUSHI
WHAT IT IS ...
 An ANSI/NISO Standard (NISO Z39.93-2007)
 Defines automated request and response model
  for harvesting e-resource usage data
 Designed to work with COUNTER, the most
  frequently retrieved usage reports
SUSHI
HOW TO USE IT …
 Works behind-the-scenes
 It is a client-server technology used by usage
  consolidation solutions (e.g. ERM systems) and
  content providers
 Content providers develop a SUSHI Server to
  deliver COUNTER statistics
 Usage consolidation solutions include a SUSHI
  client to automatically retrieve usage on a
  scheduled basis or on demand
SUSHI
WHY YOU SHOULD USE IT …
 It replaces the time-consuming user-mediated
  collection of usage data reports
 The protocol is generalized and
  extensible, meaning it can be used to retrieve a
  variety of usage reports
SUSHI
CURRENT STATUS…
 Many resources available on SUSHI web site:
  http://www.niso.org/workrooms/sushi
 40+ content providers support SUSHI
    (SUSHI Server Registry: https://sites.google.com/site/sushiserverregistry)

 Works with all COUNTER reports
 Ready for COUNTER Release 4
 SUSHI support is an enforced requirement for
  COUNTER compliance with Release 4
SUSHI
THE COMMITTEE…
   Bob McQuillan, Innovative Interfaces Inc. (Co-chair)
   Oliver Pesch, EBSCO Information Services (Co-chair)
   Marie Kennedy, Loyola Marymount University
   Chan Li, California Digital Library
   John Milligan, ScholarlyIQ
   Paul Needham, Cranfield University
   James Van Mil, University of Cincinnati Libraries
SUSHI
CURRENT ACTIVITES…
 ◦ Continued education and awareness
 ◦ Renovating the web site
 ◦ Exploring “SUSHI Lite” – a protocol that
   would be based on JSON
IOTA
   Improving OpenURL Through Analytics
IOTA
WHAT IS IT…
 ◦ A working group focused on OpenURL
   quality…
 ◦ Using analytics to provide a quantitative measure of
   quality of OpenURLs provided by “Sources”
 ◦ Created the Completeness Index as a measure of
   quality
 ◦ Developed an interactive online tool to provide
   analysis and reporting on real OpenURL log file
 ◦ Producing a Technical Report and
   Recommended Practice related to OpenURL
   quality
IOTA
COMPLETENESS INDEX…
 Based on premise that the success of a link can
  be affected by the data provided in the
  OpenURL
 Identify the required metadata elements
 Determine a “weight” for each element to
  reflect importance
 Score an OpenURL by adding weights for all
  elements provided divided by the total if all
  elements appeared
IOTA
    Simple example assuming equal element weights
Element    Description           Weight   This OpenURL


ATitle     Article title           1
AuLast     Author’s last name      1
Date       Date of publication     1
ISSN       ISSN                    1

Issue      Issue number            1
SPage      Start page              1
Title      Journal Title           1
Volume     Volume number           1
TOTAL                              8
IOTA                                 SAMPLE OPEN URL DATA
                                     ?date=2/4/2008
                                     &issn=1083-3013
    Simple example assuming equal element weights
                                     &volume=13
                                     &issue=20
 Completeness Score...
                                     &atitle=the+casualties+of+war
Element         Description                      Weight           This OpenURL
(Total for This OpenURL)
       Total Weights
ATitle          Article title                      1                  1
AuLast     5 / 8Author’s last name                 1
Date                                                                  1
         = .625 of publication
              Date                                 1
ISSN            ISSN                               1                  1
Issue           Issue number                       1                  1
SPage           Start page                         1
Title           Journal Title                      1
Volume          Volume number                      1                  1
TOTAL                                              8                  5
IOTA
RECOMMENDED PRACTICE…
 Defines a technique for determining element
  weights
 Tested with real link resolvers and real
  OpenURLs
 Based on research which looked for a
  correlation with data elements on the
  OpenURL and “success” of the OpenURL
A Statistical Approach to
Determining Element Weights
   Select a set of “perfect” OpenURLs
    ◦ include all key data elements and resolve to full
      text
   Perform step-wise regression
    ◦ Test failure rates for each element by removing
      that element
 Use failure rates as basis for weights
 Use weights to calculate Completeness
  Scores and to test for correlation between
  weights and success for larger sample
Failure Rates from 1500 OpenURL
          test sample
Author’sElement removed
         last name is least   Description              Failure Percentage
       important OpenURL
        from the
        ATitle                Article title                   .74%
 Date is AuLast
         surprisingly low     Author’s last name              .07%
        Date                  Date of publication             .4%
        ISSN                  ISSN (either online or         22.02%
                              print ISSN)
        Issue                 Issue number                   20.27%
      SPage
 Volume is most critical      Start page                     33.27%
        Title                 Journal Title (either           .61%
                              Title or Jtitle)
        Volume                Volume number                  74.14%
Calculated Element Weights
Element                    Description                          Weight*


ATitle                     Article title                           1.87
AuLast                     Author’s last name                      0.83
Date                       Date of publication                     1.61
ISSN                       ISSN (either online or                  3.34
                           print ISSN)

Issue                      Issue number                            3.31
SPage                      Start page                              3.52
Title                      Journal Title (either Title             1.78
                           or Jtitle)

Volume                     Volume number                           3.87

 *Element weight calculation: log10 (failure-rate-per-10,000 OpenURLs)
Results

1.2000
1.0000                                                                  Average of
0.8000                                                                  Completeness
0.6000                                                                  Score
0.4000
0.2000
                                                                        Average of
                                                                        Success Score
0.0000




                        Correlation Coefficient .80
          Tests conducted on sample of 15,000 OpenURLs randomly pulled from IOTA database
IOTA
INTERACTIVE ONLINE TOOL…
 23.3+ million OpenURLs processed
 Reporting interface
  ◦ Analyze data elements (metrics) across vendors or
    database (Source)
  ◦ Analyze (Source) for all data elements
Analysis of vendors by
  element (metric)
Analysis of elements
     by vendor
IOTA
HOW TO USE IT…
 ◦ The Technical Report provides suggestions for
   improving OpenURLs
 ◦ The interactive tool offers a means to pin-
   point irregularities in data provided on
   OpenURLs
 ◦ The Recommended Practice describes how to
   create a Completeness Index
 ◦ Completeness Index allows OpenURL quality
   problems to be quantified
IOTA
WHY YOU SHOULD USE IT…
 ◦ Link resolver vendors can implement the
   Completeness Index in their products to help
   identify problematic OpenURL sources
 ◦ Librarians can use suggestions and
   Completeness Index to more effectively
   communicate quality problems to content
   providers
 ◦ Content providers can use the online
   interactive tool to identify problems with the
   data they provide
IOTA
THE WORKING GROUP…
   Adam Chandler (Chair)
    Database Management and E-Resources Librarian, Cornell University Library
   Rafal Kasprowski
    Electronic Resources Librarian, Rice University
   Susan Marcin
    Licensed Electronic Resources Librarian, Continuing & Electronic Resources
    Management Division, Butler Library Columbia University
   Oliver Pesch
    Chief Strategist, E-Resource Access and Management Services, EBSCO Information
    Services
   Clara Ruttenberg
    Electronic Resources Librarian, University of Maryland
   Elizabeth Winter
    Electronic Resources Coordinator, Georgia Tech Library, Collection Acquisitions &
    Management Department
   Jim Wismer
    Manager, Software Engineering, Thomson Reuters
   Aron Wolf
    Data Program Analyst, Serials Solutions
IOTA
CURRENT STATUS…
 ◦ Technical Report in final draft
 ◦ Recommended Practice has been submitted
   to NISO
 ◦ Interactive Online Tool remains available
Active NISO Initiatives
   DAISY Standards
   Demand-Driven Acquisition (DDA) of Monographs
   Digital Bookmarking and Annotation
   E-book Special Interest Group (SIG)
   IOTA: OpenURL Quality Metrics
   I2 (Institutional Identifiers)
   ISO Project 25964
   JATS: Journal Article Tag Suite (Also known as Standardized Markup for Journal Articles)
   KBART (Knowledge Base and Related Tools) (NISO/UKSG)
   NCIP (NISO Circulation Interchange Protocol) Standing Committee
   Open Discovery Initiative
   PIE-J (Presentation & Identification of E-Journals)
   ResourceSync
   SERU Standing Committee
   Standard Interchange Protocol (SIP)
   Supplemental Journal Article Materials (NISO/NFAIS)
   SUSHI Standing Committee and SUSHI Servers
   Z39.7 (Data Dictionary) Standing Committee
References
 Active NISO Groups
  http://www.niso.org/workrooms/#active
 SUSHI Web Site
  http://www.niso.org/workrooms/sushi
 IOTA Web Site
  http://www.niso.org/workrooms/openurlquality
 SUSHI Server Registry
  https://sites.google.com/site/sushiserverregistry
Have an idea for a standard or
  recommended practice?

              Email…
             Nettie Lagace,
 Associate Director for Programs, NISO
           nlagace@niso.org



            THANK YOU!

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Meeting the Challenge / NISO update

  • 1. Meeting the Challenge: Successful Electronic Resources Management in the Absence of a Perfect System NISO Update on IOTA and SUSHI Oliver Pesch Chief Strategist, E-Resources, EBSCO Information Services
  • 2. Overview  SUSHI  IOTA  Other NISO Initiatives
  • 3. SUSHI Standardized Usage Statistics Harvesting Initiative
  • 4. SUSHI WHAT IT IS ...  An ANSI/NISO Standard (NISO Z39.93-2007)  Defines automated request and response model for harvesting e-resource usage data  Designed to work with COUNTER, the most frequently retrieved usage reports
  • 5. SUSHI HOW TO USE IT …  Works behind-the-scenes  It is a client-server technology used by usage consolidation solutions (e.g. ERM systems) and content providers  Content providers develop a SUSHI Server to deliver COUNTER statistics  Usage consolidation solutions include a SUSHI client to automatically retrieve usage on a scheduled basis or on demand
  • 6. SUSHI WHY YOU SHOULD USE IT …  It replaces the time-consuming user-mediated collection of usage data reports  The protocol is generalized and extensible, meaning it can be used to retrieve a variety of usage reports
  • 7. SUSHI CURRENT STATUS…  Many resources available on SUSHI web site: http://www.niso.org/workrooms/sushi  40+ content providers support SUSHI (SUSHI Server Registry: https://sites.google.com/site/sushiserverregistry)  Works with all COUNTER reports  Ready for COUNTER Release 4  SUSHI support is an enforced requirement for COUNTER compliance with Release 4
  • 8. SUSHI THE COMMITTEE…  Bob McQuillan, Innovative Interfaces Inc. (Co-chair)  Oliver Pesch, EBSCO Information Services (Co-chair)  Marie Kennedy, Loyola Marymount University  Chan Li, California Digital Library  John Milligan, ScholarlyIQ  Paul Needham, Cranfield University  James Van Mil, University of Cincinnati Libraries
  • 9. SUSHI CURRENT ACTIVITES… ◦ Continued education and awareness ◦ Renovating the web site ◦ Exploring “SUSHI Lite” – a protocol that would be based on JSON
  • 10. IOTA  Improving OpenURL Through Analytics
  • 11. IOTA WHAT IS IT… ◦ A working group focused on OpenURL quality… ◦ Using analytics to provide a quantitative measure of quality of OpenURLs provided by “Sources” ◦ Created the Completeness Index as a measure of quality ◦ Developed an interactive online tool to provide analysis and reporting on real OpenURL log file ◦ Producing a Technical Report and Recommended Practice related to OpenURL quality
  • 12. IOTA COMPLETENESS INDEX…  Based on premise that the success of a link can be affected by the data provided in the OpenURL  Identify the required metadata elements  Determine a “weight” for each element to reflect importance  Score an OpenURL by adding weights for all elements provided divided by the total if all elements appeared
  • 13. IOTA  Simple example assuming equal element weights Element Description Weight This OpenURL ATitle Article title 1 AuLast Author’s last name 1 Date Date of publication 1 ISSN ISSN 1 Issue Issue number 1 SPage Start page 1 Title Journal Title 1 Volume Volume number 1 TOTAL 8
  • 14. IOTA SAMPLE OPEN URL DATA ?date=2/4/2008 &issn=1083-3013  Simple example assuming equal element weights &volume=13 &issue=20 Completeness Score... &atitle=the+casualties+of+war Element Description Weight This OpenURL (Total for This OpenURL) Total Weights ATitle Article title 1 1 AuLast 5 / 8Author’s last name 1 Date 1 = .625 of publication Date 1 ISSN ISSN 1 1 Issue Issue number 1 1 SPage Start page 1 Title Journal Title 1 Volume Volume number 1 1 TOTAL 8 5
  • 15. IOTA RECOMMENDED PRACTICE…  Defines a technique for determining element weights  Tested with real link resolvers and real OpenURLs  Based on research which looked for a correlation with data elements on the OpenURL and “success” of the OpenURL
  • 16. A Statistical Approach to Determining Element Weights  Select a set of “perfect” OpenURLs ◦ include all key data elements and resolve to full text  Perform step-wise regression ◦ Test failure rates for each element by removing that element  Use failure rates as basis for weights  Use weights to calculate Completeness Scores and to test for correlation between weights and success for larger sample
  • 17. Failure Rates from 1500 OpenURL test sample Author’sElement removed last name is least Description Failure Percentage important OpenURL from the ATitle Article title .74% Date is AuLast surprisingly low Author’s last name .07% Date Date of publication .4% ISSN ISSN (either online or 22.02% print ISSN) Issue Issue number 20.27% SPage Volume is most critical Start page 33.27% Title Journal Title (either .61% Title or Jtitle) Volume Volume number 74.14%
  • 18. Calculated Element Weights Element Description Weight* ATitle Article title 1.87 AuLast Author’s last name 0.83 Date Date of publication 1.61 ISSN ISSN (either online or 3.34 print ISSN) Issue Issue number 3.31 SPage Start page 3.52 Title Journal Title (either Title 1.78 or Jtitle) Volume Volume number 3.87 *Element weight calculation: log10 (failure-rate-per-10,000 OpenURLs)
  • 19. Results 1.2000 1.0000 Average of 0.8000 Completeness 0.6000 Score 0.4000 0.2000 Average of Success Score 0.0000 Correlation Coefficient .80 Tests conducted on sample of 15,000 OpenURLs randomly pulled from IOTA database
  • 20. IOTA INTERACTIVE ONLINE TOOL…  23.3+ million OpenURLs processed  Reporting interface ◦ Analyze data elements (metrics) across vendors or database (Source) ◦ Analyze (Source) for all data elements
  • 21.
  • 22. Analysis of vendors by element (metric)
  • 23. Analysis of elements by vendor
  • 24. IOTA HOW TO USE IT… ◦ The Technical Report provides suggestions for improving OpenURLs ◦ The interactive tool offers a means to pin- point irregularities in data provided on OpenURLs ◦ The Recommended Practice describes how to create a Completeness Index ◦ Completeness Index allows OpenURL quality problems to be quantified
  • 25. IOTA WHY YOU SHOULD USE IT… ◦ Link resolver vendors can implement the Completeness Index in their products to help identify problematic OpenURL sources ◦ Librarians can use suggestions and Completeness Index to more effectively communicate quality problems to content providers ◦ Content providers can use the online interactive tool to identify problems with the data they provide
  • 26. IOTA THE WORKING GROUP…  Adam Chandler (Chair) Database Management and E-Resources Librarian, Cornell University Library  Rafal Kasprowski Electronic Resources Librarian, Rice University  Susan Marcin Licensed Electronic Resources Librarian, Continuing & Electronic Resources Management Division, Butler Library Columbia University  Oliver Pesch Chief Strategist, E-Resource Access and Management Services, EBSCO Information Services  Clara Ruttenberg Electronic Resources Librarian, University of Maryland  Elizabeth Winter Electronic Resources Coordinator, Georgia Tech Library, Collection Acquisitions & Management Department  Jim Wismer Manager, Software Engineering, Thomson Reuters  Aron Wolf Data Program Analyst, Serials Solutions
  • 27. IOTA CURRENT STATUS… ◦ Technical Report in final draft ◦ Recommended Practice has been submitted to NISO ◦ Interactive Online Tool remains available
  • 28. Active NISO Initiatives  DAISY Standards  Demand-Driven Acquisition (DDA) of Monographs  Digital Bookmarking and Annotation  E-book Special Interest Group (SIG)  IOTA: OpenURL Quality Metrics  I2 (Institutional Identifiers)  ISO Project 25964  JATS: Journal Article Tag Suite (Also known as Standardized Markup for Journal Articles)  KBART (Knowledge Base and Related Tools) (NISO/UKSG)  NCIP (NISO Circulation Interchange Protocol) Standing Committee  Open Discovery Initiative  PIE-J (Presentation & Identification of E-Journals)  ResourceSync  SERU Standing Committee  Standard Interchange Protocol (SIP)  Supplemental Journal Article Materials (NISO/NFAIS)  SUSHI Standing Committee and SUSHI Servers  Z39.7 (Data Dictionary) Standing Committee
  • 29. References  Active NISO Groups http://www.niso.org/workrooms/#active  SUSHI Web Site http://www.niso.org/workrooms/sushi  IOTA Web Site http://www.niso.org/workrooms/openurlquality  SUSHI Server Registry https://sites.google.com/site/sushiserverregistry
  • 30. Have an idea for a standard or recommended practice? Email… Nettie Lagace, Associate Director for Programs, NISO nlagace@niso.org THANK YOU!

Notas do Editor

  1. Lets run through a quick example. This table shows the core elements for an article link… and for the simplicity of this example we will assume all elements are equally important so each gets a weight of 1 – a perfect OpenURL will get the maximum score of 8.
  2. Now lets look at some OpenURL elements…. In this OpenURL we have…<CLICK>Date … so we add one point<CLICK>ISSN… add another point<CLICK>Volume… another point<CLICK>ISSUE… another<CLICK>And Article Title… and another point<CLICK>… the result is a total of 5 points.<CLICK>The calculation is Sum of the weights for this OpenURL divided by the total for all weights<CLICK>Which is five divided by 8<CLICK>Or .625
  3. We needed a better way of determining the element weights, so we sought help from Phil Davis – a researcher with some experience in statistical modeling. Phil’s suggestion was to perform stepwise regression to see the effect of individual elements on a sample of OpenURLs. And that is what we did…We started with a set of “perfect” OpenURLs – ones that not only included all core data elements, but that also resolved to match a full text target on both LinkSource and 360 Link… we used a set of 1500.<CLICK>We then ran several series of tests where we ran the OpenURL past the link resolver with a different element removed for each test series.<CLICK>We recorded the success (or rather failure rates) associated with each element. The elements with the higher failure rates are more important to the success of the OpenURL than the ones with lower failure rates.<CLICK>We then used the failure rates as a basis for weights.<CLICK>Then we used the weights and re-ran our 15,000 sample test.
  4. So how’d it turn out? Again, here are numbers for LinkSource.<Click>You can see Volume was a key element with 74% of OpenURLs failing when it was removed.<Click>Author last name was not very important with less than a 10th of a percent failure rate<Click>Date was surprising low too. This could be for a few reasons – the level of forgiveness in the holdings matching logic (e.g. treat no date as “any date”), the ability for the link resolver to discover the date by looking up the article citation in the knowledge base using volume/issue/start page coupled with the fact that a lot of full text providers don’t use date explicitly in the outbound links.
  5. We created article weights. <Click>Rather than use raw failure rates, we used logarithmic values of the failure rates – the number of failures per 10,000.
  6. Then we ran our 15,000 record sample again. You can see from the graph that average completeness score and average success score for the OpenURL providers align very closely, and the Correlation Coefficient of these two values across all 15,000 test OpenURLs is .80 – which indicates a strong correlation. Good news for the test.This tells us that the Completeness Index can be used as a predictor of OpenURL success from a particular content provider – a low Completeness Index is a good indicator there is a problem.