Library and Scholarly Usage Data Conversation

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Development of a Usage Data Decision Framework

This wiki was created following the NISO Usage Data Forum, 1-2 November 2007, in Dallas, TX primarily to provide a place for folks who care about library and scholarly usage data to work together to develop a decision framework to help those organizations trying to figure out how to approach usage data.

Usage Data Decision Framework - This is the working draft that we can all continue to tweak

Contributing Frameworks - existing frameworks that might have something to offer (e.g., data evolution continuum, Technology 7 framework, 7 Deadly Sins of Performance Measurement and 4 Elements of Successful Strateges, Gartner Decision Support Framework)

Framework Discussion - thoughts and ideas about how to go about this or responses to people's suggestions or additions

Caryn Anderson's NISO Nov 2007 conference presentation

Understanding the Data Around Us: Gathering and Analyzing Usage Data - D-Lib Nov/Dec 2007 review 

Other Usage Data Conversations

While this wiki was primarily to help develop a Usage Data Decision Framework, it would be great to have other conversations about usage data as well. I've created a few pages (below). Please feel free to add a new page about any relevant topic.

General Discussion

Data Collection

Data Transfer and Manipulation

Data Incomparability

Data Integration - with ERMs, DSS (decision support), cost per use issues, etc.

Data Analysis and Presentation - includes full list of how data is used from all the presentations once they are available, analysis tools, how to communicate to administration, etc.

Usage Contexts - Ethnographic studies of users, purpose of uses (MINES)

User Behavior - how usage data supports discovery of information seeking behavior, scholarly behavior (MESUR)

Standards - COUNTER, SUSHI, discussion about what constitutes a use and whether we should be measuring at the item-level or part level and what to do about measuring non-text resources, etc.

Services - Scholarly Stats, repositories, etc.

Custom Usage Data Solutions - e.g. UPenn solutions

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