Five years after their public launch, Creative Commons licenses have achieved impressive adoption across many different content types, users, and jurisdictions. However, this adoption has proven difficult to characterize, in part due to its decentralized nature. This talk will give a brief overview of what we know about quantitative and qualitative growth of CC license adoption, upcoming initiatives to increase this knowledge and to make raw data on CC license usage more available to researchers, and the role of CC technology efforts in facilitating adoption metrics, including reuse tracking.

1. ACIA 2008
2008-01-20
Toward Useful Creative Commons Adoption
Metrics
Mike Linksvayer
Vice President, Creative Commons
Original photo by tylerdurden1 1
Licensed under CC Attribution 2.0
http://flickr.com/photos/tylerdurden/880913951/

2. No New Graphs?
● See my 2007 Dubrovnik presentation
– http://www.slideshare.net/mlinksva/creative-commons-metrics/
● Giorgos has the best goods
– http://pml.wikidot.org
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3. Four pre-announcements
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4. 1: 90 million
● New estimate (taken 2006-12) of
minimum number of CC licensed works
● Using methodology similar to described
by Giorgos Cheliotis in June (finding
minimum 45-60m based on 2006-01
data)
● Number to satisfy distribution of licenses
at Flickr and Yahoo! search results
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5. 1: 90 million

6. 2: CC Metrics Portal
http://wiki.creativecommons.org/Metrics
(forthcoming)
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7. 3: Data Dump
All metrics collected by CC over the years
will be available for download as MySQL
and CSV dumps to encourage analysis.
Warning: the data is very messy.
(forthcoming)
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8. 4: ccREL
● Finer grained licensing
● Machine readable attribution
● Derivatives tracking
● Exposed on deed
● More and better metadata = easier and
more interesting metrics
● http://wiki.creativecommons.org/ccREL
(forthcoming)
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9. Some of the things we want to
know
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10. Quantitative
● Overall growth, causes
● Regional variation, causes
● Genre and type growth, causes
● Derivative use
● Plain republishing
● How is license use evolving? More
freedom?
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11. Qualitative
● High quality content
● Use cases, success stories
● Awards?
● Discovery
● Role of attention data (hey that’s
quantitative)
● How is open licensing changing culture?
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12. Some of the things you can do
to help
● Find good CC licensed stuff
● Document success stories as case studies
● Code for CC metrics projects
● Research
● Critiques of research
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13. License
– http://creativecommons.org/licenses/by/3.0/
Attribution
– Author: Mike Linksvayer
– Link: http://creativecommons.org
Questions?
– ml@creativecommons.org
Wiki
– http://meeting.creativecommons.org.tw/program:cc-adoption-metrics
Original photo by bopuc 13
Licensed under CC Attribution 2.0
http://flickr.com/photos/bopuc/360254332/