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Approximate Minimum Total CC Licensed Works as of July 2009: ~250 million

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The Metrics Portal is about gathering, processing and visualizing metrics about Creative Commons' related projects, with particular emphasis on the adoption and usage of Creative Commons licenses internationally. Join us!

The best place to communicate on this is through the cc-community mailing list for general discussion, cc-devel for technical discussion, and the #cc chat channel on If really deep into this, please consider joining into the commons-research community. Join in the fun!

CC Monitor Project

This is the home of the CC-Monitor online platform, which contains automatically collected data, graphs, research and collectively written commentary on the global adoption of Creative Commons licenses. It is our hope that this will become a valuable online resource for the Creative Commons community, for researchers, the press, and other third parties. We will invite many more experts on CC and all things 'open' to contribute to this resource in due time. Click on any of the links below to access statistical information, original research and commentary on the adoption of Creative Commons around the world.

See the Site

Research and Presentations

Juris-Ranking-Comparison WebVersion.jpg Chart of Global CC adoption and licensing permissiveness. Courtesy the Participatory Media Lab -- more visualizations available here and an explanation of this chart here.

Giorgos Cheliotis and the researchers at the Participatory Media Lab based at Singapore Management Univerity have been tracking and analyzing the development of Creative Commons worldwide. His 2007 TRPC paper "Taking Stock of the Creative Commons Experiment," is available here. The Lab's research wiki is a great resource for some of the latest research on CC adoption. Further slides:

Mike Linksvayer, VP of Creative Commons, has also given a few presentations in the past on the analysis and development of metrics for measuring the progress of CC licensing:

The First Interdisciplinary Research Workshop on Free Culture held in August, 2008 featured several metrics-related presentations.

Christian Grasse's analysis of Flickr data as of reaching 100m CC licensed images.

Aggregate web pages licensed

License statistics has basic information about linkback/page/search-engine-query-based license adoption statistics, as well as the code used to gather this data and dumps of the data itself.

Site-specific metrics

Content Directories lists licensed works counts for many sites that collect CC-licensed works, e.g., about 100 million at Flickr.

Counts for selected top sites over time may be found on the license statistics page.

Eventually code above should be expanded to collect this and finer-grained information (e.g., per site license breakdown) from these sites.

Other quantitative metrics

  • CC web server logs:
    • Historical data on license choices at the "License your work" CC license chooser
    • Indications based on referrers to our image icons to see if people change the license on web pages or other licensed documents
    • Indications based on image icon loading frequency as to which licenses are used by content widely seen by users
    • Analysis of logs to see what sorts of licenses and items people search for - and if that has changed over time
    • Analysis of license deeds to see if deed information affects choices in /license/
    • Geographic sub-analysis of the above
    • Code to reproducibly and consistently generate the above statistics.

Follow updates on ccLabs.

Qualitative metrics

  • Case Studies
  • Awards Received (grammys, oscars, etc)
  • "bestsellers" for some definition of best-seller from Books
  • Add ideas here...


Creative Commons Data

Other Datasets

  • Any other data sets? Add them here...


Numbers Explanation

The Approximate Minimum Total CC Licensed Works is based on licenses reported by Yahoo search queries and Flickr and is the minimum number of licensed works that would satisfy the distribution of license types across both of them. See the estimation code.

This uses the scaling algorithm programmed by Ankit Gugliani as part of his work with Giorgos Cheliotis.