The DOI matches its Crossref record.
Governing Knowledge Commons
Abstract
Knowledge commons are the subject of enormous recent interest and enthusiasm with respect to policy making about innovation, creative production, and intellectual property. Taking that enthusiasm as its starting point, this book argues that policy making should be based on evidence and on deeper understanding of what makes commons institutions tick. Scholars of the natural environment have developed successful methods for studying commons arrangements systematically and in detail. The book borrows from them and proposes a framework for studying knowledge commons that is adapted to the unique attributes of knowledge and information. It describes the framework in detail and explains how to put it into practice, with contributed chapters that put the framework into context both with respect to commons research in general and with respect to innovation and information policy broadly. The book includes eleven detailed case studies that explore knowledge commons across a wide variety of scientific and cultural domains, including applications in contemporary medical research, astronomy, open source computer software, news reporting, development of military equipment, the origins of aircraft design, user entrepreneurship, and the emerging cultural phenomenon known as roller derby.
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“The construction follows the iterative logic of established taxonomy-development method (Nickerson et al., 2013), alternating between the conceptual derivation of dimensions from the Ostromian grammar and the empirical inspection of the institutions examined in Sections 6-10, and it adopts the interrogation structure of the Governing Knowledge Commons case-study method (Frischmann et al., 2014),”
From Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance (2026) · cites this paper as Frischmann et al., 2014
In the citing paper
“The Governing Knowledge Commons program of Frischmann et al. (2014) was built substantially on scientific cases, and the open-weight model collaboration of the model layer is, in its governance, an extension of scientific peer production to artifacts that were previously proprietary, as the BigScience workshop's BLOOM demonstrates (BigScience Workshop et al., 2022).”
From Commons-Governed Artificial Intelligence: A Taxonomy of Collective Governance (2026) · cites this paper as Frischmann et al. (2014)
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Metadata
- Venue
- Oxford University Press eBooks
- Publisher
- Oxford University Press
- Published
- 2014-09-02
- OpenAlex
- W592215310
- Cited by
- 304
- References
- 0
- Citations by year
- 2026: 33 · 2025: 36 · 2024: 16 · 2023: 36 · 2022: 24 · 2021: 31 · 2020: 30 · 2019: 24 · 2018: 13 · 2017: 28 · 2016: 19 · 2015: 13 · 2014: 1
- FWCI
- 30.14
- Type
- book
- Language
- pl
- Open access
- closed
- Locations
- Oxford University Press eBooks (publishedVersion)
- Topics
- Social Sciences › Law › Intellectual Property Rights and Media
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Research, Science, and Academia
- Social Sciences › Decision Sciences › Information Systems and Management › Knowledge Management and Sharing
- Keywords
- knowledge commons, commons governance, commons institutions, evidence-based policy, innovation policy, information policy, intellectual property, open source software, medical research, astronomy, media coverage, military technology development, aircraft design, user entrepreneurship, roller derby, cultural commons
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