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The Future of Scientific Knowledge
Discovery in Open Networked
Environments:
Legal Considerations
Michael Madison
Professor of Law
Faculty Director, Innovation Practice Institute
University of Pittsburgh
[email protected]
Board on Research Data and Information
in collaboration with
Computer Science and Telecommunications Board
National Academy of Sciences
Washington, DC
March 10, 2011
Assume that access to the database/dataset is permitted in the first instance
Dataset # 2,
labeled “Public
domain/CC0”
Dataset # 1,
with no label
What legal
challenges
does the
researcher in
the middle
face?
Dataset # 3,
labeled
“All rights
reserved”
Dataset # 4, labeled
“Data Mining Not
Allowed”
Legal issues
1. Status of the data, coding, formats, and datasets:
copyright law basics
2. Making sense of contracts and licenses
3. Managing the results of data collection
Status of the data, coding, formats, and datasets:
copyright law default rules
1.
2.
3.
4.
5.
6.
A specific datum (observation, research result, nucleotide
sequence, and so on) is a noncopyrightable fact and is in the public
domain.
Datasets and other collections of facts are covered automatically by
copyright as “compilations” if their “selection, coordination, or
arrangement” demonstrates “minimal” (human) creativity.
Coding, formats, interpretations are likely covered by copyright.
Compilations arranged for ease of use, to comply with standard
taxonomies or disciplinary standards, or in other obvious, routine,
or mechanical ways cannot be protected by copyright.
Compilation copyrights are thin, meaning only verbatim copying is
prohibited.
In Europe, EU database rights may apply.
Fair use or other limitations protecting scientific research may
apply.
Making sense of contracts and licenses
1.
2.
3.
4.
5.
6.
In the absence of a contract, license, or notice, default copyright rules
apply. Data and datasets may be offered to the public domain. Or, the
compiler may dedicate the material to the public domain (e.g., CC0
licenses). A CC0 license irrevocably commits copyrighted content to
the PD. Noncopyrighted material may be labeled PD for clarity.
Licenses specifying scope of authorized access, use, datamining,
recombination may be bundled with contracts, or may be unilateral.
 No assent may be required. Notice of the terms may be limited.
Terms may be human readable but not machine readable. Or the
reverse.
License terms may be custom designed by the dataset provider /host
institution, leading to overlapping/inconsistent legal obligations.
License scope may enable some onward collaboration, sharing, or
redistribution of data -- but not all.
Enforceability of private unilateral notices / licenses is unclear.
Government-mandated data sharing /licensing provides consistency,
enforceability.
Managing the results of data collection
Forward-looking issues related to governing a data commons:
1. Data/dataset integrity.
2. Translation and interoperability of data from different sources, in
different formats: designing and enforcing standards; managing
and maintaining data consistency. (Ensuring PD status of data
may be inadequate to deal with this challenge.)
3. Who has access to the new collection of data, and for what
purposes?
4. What are participants’ duties and rights regarding standardization
and data consistency, and re-sharing, re-combining, re-using data?
5. How is compliance monitored and enforced?
6. When do those duties and rights pass to downstream parties who
did not obtain the data in the first place?
7. Compare the costs and benefits of government-sponsored
enforcement with those of private enforcement via licenses and
contracts, and with those of informal/community enforcement.
Summary
1.
2.
Difficulty of achieving
 Clarity
 Simplicity
 Flexibility
Even with sponsor support and the best of
intentions.
3.
The legal system is designed to promote securing
things, not sharing knowledge.
4.
We’re unlikely to find one-size-fits-all legal
solutions.