Research Resource Commons workshop - Revision history

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← Older revision		Revision as of 20:33, 6 May 2012
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−	PDF version available [[Media:~~CC_Science_NSF_Workshop_report_2-3-2012~~.pdf#file\|here]].	+	PDF version available [[Media:CC_Science_NSF_Workshop_Final_Report_November_2011.pdf#file\|here]].

	= Workshop on Research and Resource Commons in Scientific Research: Final Report =		= Workshop on Research and Resource Commons in Scientific Research: Final Report =

@@ Line 160: / Line 160: @@
 == Conclusions ==
-There is increasing visibility of the Open Science movement world-wide<ref>As evidence, during the preparation of this report there were several articles published in the popular press on the subject, including this article in the NY Times: http://www.nytimes.com/2012/01/17/science/open-science- challenges-journal-tradition-with-web-collaboration.html?_r=1</ref> and that is an opportune time to accelerate progress towards a public commons of research resources. We offer the following observations and recommendations derived from the workshop:
+There is increasing visibility of the Open Science movement world-wide<ref>As evidence, during the preparation of this report there were several articles published in the popular press on the subject, including this article in the NY Times: http://www.nytimes.com/2012/01/17/science/open-science-challenges-journal-tradition-with-web-collaboration.html?_r=1</ref> and that is an opportune time to accelerate progress towards a public commons of research resources. We offer the following observations and recommendations derived from the workshop:
 * '''High-level government policies are key, and good examples exist to develop best practices'''
 ** A very high leverage activity is connected to the National Science Board data policy recommendations, as these policies will inform policy at NSF and elsewhere in the federal government, and have knock-on effects in other countries;

@@ Line 231: / Line 231: @@
 # Continued legal analysis of copyrightability of bibliographic data and the citing sentence (also fair use);
 # Defining best practices for standards (e.g. open, documented, IP-free)
 '''Additional recommendations'''

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-* Data management infrastructure will likely be characterized by a mix of centralized holding and distributed centers at universities
+* '''Data management infrastructure will likely be characterized by a mix of centralized holding and distributed centers at universities'''
 ** Funding and incentive models to support decentralized storage should be pursued;
 ** Creating certification for data management facilities (along the lines of LEED-certification for buildings) could be a practical incentive to create high-quality infrastructure, especially at universities.

@@ Line 231: / Line 231: @@
 # Continued legal analysis of copyrightability of bibliographic data and the citing sentence (also fair use);
 # Defining best practices for standards (e.g. open, documented, IP-free)
 <references />

@@ Line 165: / Line 165: @@
 ** Another high-level opportunity is working on Office of Science, Technology, and Policy’s open policy recommendations, as this is affects multiple funding agencies;
 ** Agencies that currently have policies related to openly sharing research results (primarily publications and data) include the NSF, NIH, National Statistics Bureau, Bureau of Justice Statistics, and the Census Bureau.
 * '''Policy for funder-mandated data management plans should require direction on open availability of results (publications and data) to the extent possible, clear terms of access and use, and timing of availability.'''
 ** Developing best practices should be a working document over time, incorporated experiences from the US, from Europe (Netherlands, Germany, etc.), from China, and elsewhere;
 ** Implementing automatic “decay times” for intellectual property rights accruing to research results may address concerns of researchers and grantees.
 * '''In addition to government and funder policy, focusing on a middle ground or bottom up support is also critical and can be supported through education and outreach, especially to researchers and students'''
@@ Line 175: / Line 177: @@
 ** Simpler, shared licenses (or waivers) for data rights and clearer definitions around attribution can also support increased commons.
 * Improving incentives for data sharing, demonstrating its value and removing barriers are also very important
 ** New incentives include providing better mechanisms for assigning credit (e.g., in tenure decisions), such as formal publication and attribution/citation tracking;
 ** Providing funding for data sharing is a key to reducing barriers.
 * '''Data sharing policy should address multiple levels of data that are useful for a variety of audiences, including scientists but also students and the general public'''
@@ Line 184: / Line 188: @@
 ** Data-focused efforts are generally distinct from publications, but the line is increasingly blurred so that policies need to address both;
 ** While there is growing agreement that research articles should be openly shared, open access to 100% of data is unlikely for a variety of regulatory and practical reasons.
 * '''Usefully shared data requires specific information about methodology, semantics, and other appropriate metadata, in standardized terms.'''
 **  Sharing metadata for research data supports its discovery, analysis and reuse, and standardization increases interdisciplinary research potential. As with the primary data, terms of access and use of metadata should be clear and open to the greatest extent possible.
 * Data management infrastructure will likely be characterized by a mix of centralized holding and distributed centers at universities
 ** Funding and incentive models to support decentralized storage should be pursued;
 ** Creating certification for data management facilities (along the lines of LEED-certification for buildings) could be a practical incentive to create high-quality infrastructure, especially at universities.
 * '''Creating exemplars on specific scientific research topics that use a commons approach will demonstrate value'''
 ** e.g. Antarctica, (see discussion in Section II, under Policy)
 === Key Opportunities ===
 <references />

← Older revision		Revision as of 23:35, 25 February 2012
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		+	== Conclusions ==
		+	There is increasing visibility of the Open Science movement world-wide<ref>As evidence, during the preparation of this report there were several articles published in the popular press on the subject, including this article in the NY Times: http://www.nytimes.com/2012/01/17/science/open-science- challenges-journal-tradition-with-web-collaboration.html?_r=1</ref> and that is an opportune time to accelerate progress towards a public commons of research resources. We offer the following observations and recommendations derived from the workshop:
		+	* '''High-level government policies are key, and good examples exist to develop best practices'''
		+	** A very high leverage activity is connected to the National Science Board data policy recommendations, as these policies will inform policy at NSF and elsewhere in the federal government, and have knock-on effects in other countries;
		+	** Another high-level opportunity is working on Office of Science, Technology, and Policy’s open policy recommendations, as this is affects multiple funding agencies;
		+	** Agencies that currently have policies related to openly sharing research results (primarily publications and data) include the NSF, NIH, National Statistics Bureau, Bureau of Justice Statistics, and the Census Bureau.
		+
		+	* '''Policy for funder-mandated data management plans should require direction on open availability of results (publications and data) to the extent possible, clear terms of access and use, and timing of availability.'''
		+	** Developing best practices should be a working document over time, incorporated experiences from the US, from Europe (Netherlands, Germany, etc.), from China, and elsewhere;
		+	** Implementing automatic “decay times” for intellectual property rights accruing to research results may address concerns of researchers and grantees.
		+
		+	* '''In addition to government and funder policy, focusing on a middle ground or bottom up support is also critical and can be supported through education and outreach, especially to researchers and students'''
		+	** Top-down policies alone won’t work. As China’s experience illustrates, top-down policies are good but getting researchers on board is equally necessary to insure success;
		+	** Education, outreach, and training are critical components to developing this bottom up support for the commons;
		+	** Simpler, shared licenses (or waivers) for data rights and clearer definitions around attribution can also support increased commons.
		+
		+	* Improving incentives for data sharing, demonstrating its value and removing barriers are also very important
		+	** New incentives include providing better mechanisms for assigning credit (e.g., in tenure decisions), such as formal publication and attribution/citation tracking;
		+	** Providing funding for data sharing is a key to reducing barriers.
		+
		+	* '''Data sharing policy should address multiple levels of data that are useful for a variety of audiences, including scientists but also students and the general public'''
		+	** The lowest level of unprocessed data (Level 0) is not often immediately useful, but the next level (Level 1) of cleaned data is very useful for research. Making this data openly available involving costs for data center management;
		+	** Higher levels (Level 2-5) of data, incorporating more metadata, analysis, and tools, are even more useful to students and the broader public;
		+	** Data-focused efforts are generally distinct from publications, but the line is increasingly blurred so that policies need to address both;
		+	** While there is growing agreement that research articles should be openly shared, open access to 100% of data is unlikely for a variety of regulatory and practical reasons.
		+
		+	* '''Usefully shared data requires specific information about methodology, semantics, and other appropriate metadata, in standardized terms.'''
		+	** Sharing metadata for research data supports its discovery, analysis and reuse, and standardization increases interdisciplinary research potential. As with the primary data, terms of access and use of metadata should be clear and open to the greatest extent possible.
		+
		+	* Data management infrastructure will likely be characterized by a mix of centralized holding and distributed centers at universities
		+	** Funding and incentive models to support decentralized storage should be pursued;
		+	** Creating certification for data management facilities (along the lines of LEED-certification for buildings) could be a practical incentive to create high-quality infrastructure, especially at universities.
		+
		+	* '''Creating exemplars on specific scientific research topics that use a commons approach will demonstrate value'''
		+	** e.g. Antarctica, (see discussion in Section II, under Policy)
		+
		+	=== Key Opportunities ===

	<references />		<references />

@@ Line 152: / Line 152: @@
 '''Opportunity''': work with universities, research institutions, individual researchers and government agencies on specific aspects of data management plans that lack clear guidelines, such as the means for sharing data, under what license or waiver and in what time frame, to best serve the funding agencies’ and the public’s expectations.
-'''Next Steps''': identify institutions for partnership opportunities to work on integrating policy into data management plan processes and infrastructure4.
+'''Next Steps''': identify institutions for partnership opportunities to work on integrating policy into data management plan processes and infrastructure<ref>The California Digital Library has a project underway to roll out the “DMP Tool” https://dmp.cdlib.org/ to help researchers create compliant plans for new grant proposals. Collaborating with this tool provider would allow a large number of researchers to immediately leverage open science tools like the CC licenses and waivers.</ref>.
 Opportunity: establish a certification process (inspired by LEED-certification in the Architecture, Engineering and Construction industry) as an incentive for using good infrastructure and complying with best practices.
 '''Next steps''': review how LEED certification was introduced and structured, and consider stakeholders in science who could serve as a certification body.

← Older revision		Revision as of 23:28, 25 February 2012
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	== Section III: Cultural and Organizational Issues ==		== Section III: Cultural and Organizational Issues ==
		+	The research enterprise involves multiple stakeholders whose interests must be balanced to achieve success and who respond differently to the prospect of a research commons. Stakeholders include individual researchers and students, their institutions (research universities and institutes), libraries and archives, funding agencies, scholarly societies and publishers, and the public as the ultimate beneficiaries of the research. The value of research resources differs across these stakeholders so each has different drivers and challenges for creating a research commons that must be simultaneously addressed.
		+
		+	Among the stakeholders’ concerns about a research commons are credit, cost, quality, responsibility, accountability, mission-fit, and control. Understanding the costs and benefits to each stakeholder of contributing to and participating in the commons is an important prerequisite to understanding which actors will set the policies that will advance or preclude the commons. Ultimately, the policies and decision-making around the commons will be distributed so that no single stakeholder’s interests dominate, so that the commons is less likely to rise or fall with the fate of that stakeholder over time.
		+
		+	A key component of a research resources commons is the infrastructure that supports it and which is provided by one or more of the organizational stakeholders. Large-scale infrastructure like a research commons must be a joint investment of several stakeholders, e.g., universities and funding agencies, as was the case with the Internet backbone. Also required of a successful commons infrastructure are standards: for data formats and transfer protocols, documentation and metadata, legal terms and conditions, software dependencies.
		+
		+	Discussion of science always comes back to the differences across disciplines. Furthermore, a robust and reliable digital research commons should be virtual/distributed, like the Internet, rather than centralized to mitigate the risk of sudden, total failure. Add these together and it might be more profitable to work towards creating a series of commons across science rather than a single, unified commons for all science. A distributed, disciplinary-oriented approach may not be ideal for the needs of interdisciplinary research, but it would likely be easier to build, and if architected correctly could be federated in the future.
		+
		+	The group observed that there are natural roles for the various stakeholder organizations in creating a research commons that can be exploited:
		+	* Funders can provide the “nudges” like the data management plan requirement, e.g., requesting dataset citations in addition to publications
		+	* Societies (of some kinds) can play the gatekeeper role for research data quality and reproducibility
		+	* Publishers can provide incentives to deposit data, software and related resources in trustworthy archives
		+	* Universities can help provide the infrastructure and policies to support increased sharing
		+	* Libraries need to help develop the collection policies for what should be archived, shared, how,
		+	and for how long (i.e., delineate the cost/benefit tradeoffs).
		+
		+
		+	But top-down and government- or university-led policies won’t succeed without simultaneously building understanding and support for the goals of open science and a commons of research resources. This will best be accomplished via outreach and education, especially of graduate students and young researchers who are already familiar with the affordances of the Web for many other activities.
		+
		+	'''Next steps''': develop basic online educational modules on open science, open access, and open data, with associated policy and technology choices, for distribution to institutional, society, publisher, and other stakeholder partners. Consider collaboration platforms as a means of injecting sharing policies and data curation into the workflow early.
		+
		+	'''Opportunity''': work with universities, research institutions, individual researchers and government agencies on specific aspects of data management plans that lack clear guidelines, such as the means for sharing data, under what license or waiver and in what time frame, to best serve the funding agencies’ and the public’s expectations.
		+
		+	'''Next Steps''': identify institutions for partnership opportunities to work on integrating policy into data management plan processes and infrastructure4.
		+	Opportunity: establish a certification process (inspired by LEED-certification in the Architecture, Engineering and Construction industry) as an incentive for using good infrastructure and complying with best practices.
		+
		+	'''Next steps''': review how LEED certification was introduced and structured, and consider stakeholders in science who could serve as a certification body.
		+


	<references />		<references />

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 * November 17-18, 2011
 * Michael Carroll, Professor of Law and Director, Program on Information Justice and Intellectual Property, Washington College of Law at American University, Washington, D.C.
 == Summary ==
 In November of 2011, the Washington College of Law at American University convened and hosted a two-day workshop in collaboration with the Creative Commons to develop a strategy for promoting a commons or scientific research and related resources. The workshop brought together interested stakeholders from across the scientific research enterprise: scientists, administrators, librarians, publishers, societies, technologists, lawyers, policy makers, students, funders, and Open Science advocates, including both U.S. and international representatives. This diverse group discussed the current state of policy and technology as it relates to a scientific research commons, and identified key opportunities and challenges, as well as next steps, for the scientific community in general and Creative Commons in particular. These opportunities will inform the next phase of the Science program at Creative Commons and include legal and policy issues, education and technology efforts, and partnerships that will better leverage our efforts going forward.
 == Introduction ==
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 Recognizing that putting research data in the public domain and making it openly accessible can be a very difficult proposal for many researchers, an interesting concept for data sharing in science is a “collaboration club” or “walled garden” in which members openly share data with each other but not outside the boundary of the local community. The locally-shared data has been sufficiently structured and documented to support its reuse, so it might be easier to broaden access after a defined time period, e.g. an embargo period, possibly automatically. Such an approach may hinder large-scale interoperability (as discussed previously) but offers a socially acceptable step towards sharing. Such an approach could also lend itself to standards and best practices for ad hoc collaborations, with sharing policies that can be quickly adopted without custom negotiation. Also built into this model is the concept of concentric circles of access (with necessary documentation) beginning with the data producer, broadening to close collaborators, a circle of peers, the larger discipline, the scientific community, and ultimately the general public. If a “commons kit” was developed to support this, and particularly if it included automatic decay of exclusivity, this would gradually lead to a research commons as a natural evolution.
 <references />