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COUNTER Point
Making the Most of Imperfect Data
cc: amphalon - https://www.flickr.com/photos/72427312@N00
Jeannie Gartensc...
Introduction
Who we are, What we do
Two Different eResource Perspectives
• Jeannie = Systems-Side
• Lindsay = Service-Side
Disclaimer:
I was studied international relations and studio art.
Photo by David Bygott - Creative Commons Attribution-NonCommercial-ShareAlike License https://www.flickr.com/photos/866660...
Statistical modeling is the application of a set of
assumptions to data, typically paired data.
Photo by Biblioteca General Antonio Machado - Creative Commons Attribution License https://www.flickr.com/photos/37667416@...
All COUNTER Reports are Time Series Data-Sets.
• Continuous time interval
• Successive measurements
• Equal spacing/time b...
Decomposition of Time Series
• Segments time series
• Estimates based on predictability
• Wold’s theorem/decomposition – e...
Exponential Smoothing
• Smooths time series data
• Eliminates frequency noise/outliers
About the Approach
• Plays to COUNTER’s strengths
• Addresses reporting weaknesses
• Relatively straight forward analysis
...
Context and Culture
cc: Misenus1 - https://www.flickr.com/photos/44075517@N00
Statistical Modeling in the Librarycc: Boston Public Library - https://www.flickr.com/photos/24029425@N06
Choosing Resources for Pilot
• Needed 4 year+ usage history for reverse
predictive analysis
• Larger numbers make analysis...
Getting Started
JR1/DB1 – 2010 to 2013
• 4 JR datasets (Elsevier, Wiley, Highwire, and
Cambridge)
• 4 DB datasets (Ebsco a...
Applications
• Excel – Data collection/clean-up
• R – Data analysis
• Tableau – Data visualization
Excel
R
Learn About R
Resources/Tutorials I like:
• R for Beginners: https://cran.r-project.org/doc/contrib/Paradis-
rdebuts_en.pd...
Tableau
Findings and Next Steps
Trends, Implications, and Plans
cc: DirectDish - https://www.flickr.com/photos/13800911@N08
Usage is consistent across vendor platforms.
Usage trends manifest across vendor platforms.
Usage can be predicted.
What is a good search to session ratio?
Moving Forward
• Going micro with big platforms
• Heuristic examination of databases with low
search to session ratios
• D...
Thank you!
cc: USFWS Pacific - https://www.flickr.com/photos/52133016@N08
Questions
cc: Maëlick - https://www.flickr.com/photos/113604805@N04
Keep in touch
cc: tasslehoff84 - https://www.flickr.com/photos/23284841@N00
Jeannie Gartenschlaeger-Castro
jmcastro10@uh.e...
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COUNTER Point: Making the Most of Imperfect Data

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Considers data modeling as a methodology to help make COUNTER report data more useful in assessing eresource value.

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COUNTER Point: Making the Most of Imperfect Data

  1. 1. COUNTER Point Making the Most of Imperfect Data cc: amphalon - https://www.flickr.com/photos/72427312@N00 Jeannie Gartenschlaeger-Castro Lindsay Cronk 4/4/2016
  2. 2. Introduction Who we are, What we do
  3. 3. Two Different eResource Perspectives • Jeannie = Systems-Side • Lindsay = Service-Side
  4. 4. Disclaimer: I was studied international relations and studio art.
  5. 5. Photo by David Bygott - Creative Commons Attribution-NonCommercial-ShareAlike License https://www.flickr.com/photos/86666094@N00 Created with Haiku Deck
  6. 6. Statistical modeling is the application of a set of assumptions to data, typically paired data.
  7. 7. Photo by Biblioteca General Antonio Machado - Creative Commons Attribution License https://www.flickr.com/photos/37667416@N04 Created with Haiku Deck
  8. 8. All COUNTER Reports are Time Series Data-Sets. • Continuous time interval • Successive measurements • Equal spacing/time between data points • Single measures within the report period
  9. 9. Decomposition of Time Series • Segments time series • Estimates based on predictability • Wold’s theorem/decomposition – every time series can be decomposed into a pair of uncorrelated processes, one deterministic/one time/average based – Imagine usage in two components, one trend oriented (COUNTER reporting periods) and one irregular (faculty recommendations/libguides/external drivers)
  10. 10. Exponential Smoothing • Smooths time series data • Eliminates frequency noise/outliers
  11. 11. About the Approach • Plays to COUNTER’s strengths • Addresses reporting weaknesses • Relatively straight forward analysis • Opportunity to test predictive analysis • Powerful visualizations
  12. 12. Context and Culture cc: Misenus1 - https://www.flickr.com/photos/44075517@N00
  13. 13. Statistical Modeling in the Librarycc: Boston Public Library - https://www.flickr.com/photos/24029425@N06
  14. 14. Choosing Resources for Pilot • Needed 4 year+ usage history for reverse predictive analysis • Larger numbers make analysis easier (went aggregate)
  15. 15. Getting Started JR1/DB1 – 2010 to 2013 • 4 JR datasets (Elsevier, Wiley, Highwire, and Cambridge) • 4 DB datasets (Ebsco and ProQuest, separate sets for sessions and searches)
  16. 16. Applications • Excel – Data collection/clean-up • R – Data analysis • Tableau – Data visualization
  17. 17. Excel
  18. 18. R
  19. 19. Learn About R Resources/Tutorials I like: • R for Beginners: https://cran.r-project.org/doc/contrib/Paradis- rdebuts_en.pdf • Quick R: http://www.statmethods.net/ • Using R for Time Series Analysis: http://a-little-book-of-r-for-time- series.readthedocs.org/en/latest/src/timeseries.html • R Time Series Quick Fix: http://www.stat.pitt.edu/stoffer/tsa3/R_toot.htm • Ryan Womack’s excellent video series: https://www.youtube.com/watch?v=QHsmAM6nktY
  20. 20. Tableau
  21. 21. Findings and Next Steps Trends, Implications, and Plans cc: DirectDish - https://www.flickr.com/photos/13800911@N08
  22. 22. Usage is consistent across vendor platforms.
  23. 23. Usage trends manifest across vendor platforms.
  24. 24. Usage can be predicted.
  25. 25. What is a good search to session ratio?
  26. 26. Moving Forward • Going micro with big platforms • Heuristic examination of databases with low search to session ratios • Developing trend reports for CMC/selectors
  27. 27. Thank you! cc: USFWS Pacific - https://www.flickr.com/photos/52133016@N08
  28. 28. Questions cc: Maëlick - https://www.flickr.com/photos/113604805@N04
  29. 29. Keep in touch cc: tasslehoff84 - https://www.flickr.com/photos/23284841@N00 Jeannie Gartenschlaeger-Castro jmcastro10@uh.edu 713-743-9346 Lindsay Cronk lacronk@uh.edu 713-743-0519 @linds_bot

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