Open access to publicly funded data provides greater returns from the public investment in research, generates wealth through downstream commercialization of outputs, and provides decision-makers with facts needed to address problems. This article summarizes key findings of an international group that studied these issues on behalf of the Organisation for Economic Cooperation and Development.
Peter Arzberger* 1, Peter Schroeder 2, Anne Beaulieu 3, Geof Bowker 1, Kathleen Casey 1, Leif Laaksonen 4, David Moorman 5, Paul Uhlir 6 and Paul Wouters 3
- Author Affiliations
1. University of California, San Diego, La Jolla, CA 92093, USA.
2. Ministry of Education, Culture and Science, Zoetermeer, Netherlands.
3. Networked Research and Digital Information, Royal Netherlands Academy of Arts and Sciences, Amsterdam, Netherlands.
4. CSC-Scientific Computing Ltd., Espoo, Finland.
5. Social Sciences and Humanities Research Council, Ottawa, Canada.
6. National Research Council, Washington, DC 20418, USA.
*To whom correspondence should be addressed. E-mail: firstname.lastname@example.org
Recent national and multinational investments (1) in networking and continued gains in information technological capability (2) have given rise to a complex cyberinfrastructure that is rapidly increasing our ability to produce, manage, and use data (3). As research becomes increasingly global (4), data-intensive, and multifaceted (5, 6), it is imperative to address national and international data access and sharing issues systematically in a policy arena that transcends national jurisdictions. Open access to publicly funded data provides greater returns from the public investment in research, generates wealth through downstream commercialization of outputs, and provides decision-makers with facts needed to address complex, often transnational, problems. This article summarizes key findings of an international group that studied these issues on behalf of the Organisation for Economic Cooperation and Development (OECD) (7), which resulted in a ministerial-level declaration (8).
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Inter-disciplinary study and collaborative research with industry is changing
the way researchers interact, share data and manage intellectual properties.
With increasing commercial exploitation and ambitious international experiments, research data is becoming too expensive or even impossible to replace.
Shirley Crompton, Benjamin Aziz and Michael Wilson.
Inter-disciplinary study and collaborative research with industry is changing the way researchers interact, share data and manage intellectual properties.
With increasing commercial exploitation and ambitious international experiments tackling grand research challenges, research data is becoming too expensive or even impossible to replace. To promote a free flow of research data in
this complex environment, there is a need for a secure data sharing and dissemination framework that addresses issues such as context-aware usage and
obligations, data integrity, derived data, privacy and confidentiality.
As a pragmatic solution, stakeholders commonly use legally binding data
sharing agreements to control how their data is shared and disseminated. These
agreements contain policy statements on the access, usage conditions and obligations for specific sets of data as well as references to external data sharing
policies or protocols, like those of the funding agency and university hosts. Such
agreements are usually drafted by senior managers and lawyers to express what
can be decided in court should a breach occur. Enforcement is generally left
to the discretion of the data owners, publishers and providers. In the academic
domain, enforcement may range from simple mutual trust between individual
researchers on one end of the spectrum, with data consumers expected to voluntarily observe the ethical and legal obligations pertaining to the data; to a
complete lack of trust at the other end, with sensitive data secreted away on
private repositories accessible to the selected few. A system based on mutual
trust is simple to operate but not adequate to prove compliance as obligated by
many data sharing policies or regulatory legislation.
In this position paper, we outline typical use case sccenarios associated with
the scientific data sharing process and the challenges these scenarios raise.
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Michael Weiner, MD, Director of CIND at the San Francisco VA Medical Center, is among a prestigious group of 17 scientists named 2010 Rock Stars of Science by the Geoffrey Beene Foundation. The Rock Stars of Science campaign brings rock stars and “rock star” scientists together to help raise awareness about the important role of scientific research.
Michael Weiner, MD, Director of the Center for Imaging of Neurodegenerative Diseases (CIND) at the San Francisco VA Medical Center, is among a prestigious group of 17 scientists named 2010 Rock Stars of Science by the Geoffrey Beene Foundation.
Dr. Weiner, who is also a professor of Radiology, Medicine, Psychiatry, and Neurology at the University of California, San Francisco, is Principal Investigator of the Alzheimer’s Disease Neuroimaging Initiative (ADNI), a groundbreaking international study to detect biomarkers – changes in the brain and central nervous system – that may appear before overt symptoms of Alzheimer’s disease occur. Dr, Weiner is also Principal Investigator of the Neuroscience Center of Excellence, a research partnership between NCIRE-The Veterans Health Research Institute, SFVAMC, and the Department of Defense that focuses on traumatic brain injury, post-traumatic stress, and other neurological injuries and conditions among active military personnel and Veterans.
ADNI, the Neuroscience Center of Excellence, and other research projects by Dr. Weiner and his colleagues at CIND are supported through NCIRE.
The Rock Stars of Science campaign brings rock stars and “rock star” scientists together to help raise awareness about the important role of scientific research in our society. A special six-page Rock Stars of Science public service campaign is featured in GQ’s Men of the Year edition, which appeared on November 23, 2010.
Music stars from a wide range of genres – B.o.B, Brett Michaels, Debbie Harry, Ann and Nancy Wilson of Heart, Jay Sean, Keri Hilson, and Timbaland – teamed up with 17 scientists for the project, including Stephen B. Baylin, MD; Elizabeth A. Blackburn, PhD, of UCSF; retired Rear Adm. Susan J. Blumenthal, MD; Geraldine Dawson, PhD; Frank L. Douglas, MD, PhD; Bernard A. Harris, MD; Catronia Jamieson, MD, PhD; Emil Kakkis, MD; Frank M. Longo, PhD; Joan Massagué; Mehmet C. Oz, MD; Eric M. Reiman, MD; Charles L. Sawyers, MD; Phillip A. Sharp, PhD; Craig B. Thompson, MD; and Mehmet Toner, PhD.
“I’m thrilled to join my scientific colleagues and members of the music community in highlighting the significance of scientific research in our lives,” said Dr. Weiner. “Scientists must venture outside their comfort zones to show the public how cool – and how important – their work really is,” said Francis Collins, MD, PhD, director of the National Institutes of Health and one of the 2009 Rock Stars of Science.
The Rock Stars of Science campaign can be found on line at http://www.rockstarsofscience.org/index.htm .
NCIRE-The Veterans Health Research Institute is a self-funded private nonprofit research institute, established to administer health research at SFVAMC. It is the largest research institute associated with a VA medical center in the United States. NCIRE’s mission is to advance veterans health through research.
July 13-16, Vancouver – We aim in this workshop to gather speakers to discuss best practices for “reproducible research”: The idea that research contributions in the computational sciences involve not only publication of an article in an academic venue, but also release of sufficient components of the software and data such that the results claimed can be reproduced and extended by other scientists.
Date: July 13-16, Univ. British Columbia, Vancouver
Computation has become a vital component of research in the applied areas of mathematics, and through them all areas of science and engineering. Academic publications or industrially relevant mathematical results that do not involve some aspect of computational analysis are few and far between. Unfortunately, the software and data that drives this computation is too often developed and managed in a haphazard fashion prone to error and difficult to replicate or build upon.
We aim in this workshop to gather speakers to discuss best practices for “reproducible research”: The idea that research contributions in the computational sciences involve not only publication of an article in an academic venue, but also release of sufficient components of the software and data such that the results claimed in the publication can be reproduced and extended by other scientists.
The first step in reproducible research is to ensure that the developer can reproduce and easily build upon his or her own results. There are many well established tools and techniques available for software and data development and management, and the first day of the workshop will be an introduction to the most useful among them — a software development bootcamp if you will.
The next step is broader dissemination and long term management. The middle two days of the workshop will bring together experts in technical and non-technical aspects of scientific software development. In addition to talks covering specific topics, we will include case study talks: first person descriptions of successful (or perhaps not so successful) development and dissemination processes for both small-scale and large-scale academic and industrial computational science.
There is some evidence that reproducible research leads to direct benefits for individual researchers; however, we believe that even greater benefits will accrue with broad adoption. On the final day of the workshop we will focus on the benefits to the community of reproducible research, as well as strategies, policies and standards through which publishers and funders can encourage uptake of this approach to scientific computing. We believe that this aspect of the workshop is particularly important to applied and industrial mathematics because other fields — notably the biological sciences and the US National Institutes of Health — are moving quickly in this direction and the ICIAM community is in danger of being left behind.
After the workshop, the organizers plan to develop a single document, journal special issue or edited volume to summarize and/or provide more in-depth coverage of the best practices raised by the speakers.
This workshop is part of the conference “Applied Mathematics Perspectives” (AMP 2011) being held as a satellite conference to the International Congress on Industrial and Applied Mathematics – ICIAM 2011 (which takes place July 18-22 in Vancouver).
Traditional publication media cannot accommodate the multidimensionality, high resolution, and increasing volume of data produced by current imaging technology. A further barrier to sharing contemporary image data is the variety of proprietary file formats (PFFs) generated by an assortment of microscopes. To address these limitations, the JCB developed the DataViewer.
Friends, colleagues, authors, lend us your data
1Senior Editor, The Journal of Cell Biology, 2Executive Editor, The Journal of Cell Biology, 3Editor-in-Chief, The Journal of Cell Biology, and 4Executive Director, The Rockefeller University Press
Correspondence to Mike Rossner: email@example.com
- Aimee deCathelineau,
- Elizabeth H. Williams,
- Tom Misteli, and
- Mike Rossner
The JCB was founded by a group of scientists who needed a journal to showcase their micrographs with the highest quality reproduction. Our commitment to innovative presentation and sharing of image data continues today with the JCB DataViewer.
Traditional publication media cannot accommodate the multidimensionality, high resolution, and increasing volume of data produced by current imaging technology. A further barrier to sharing contemporary image data is the variety of proprietary file formats (PFFs) generated by an assortment of microscopes (Linkert et al., 2010). To address these limitations, the JCB developed the DataViewer, a browser-based application that makes original, multidimensional image data, and the associated metadata, from more than 75 different PFFs accessible to readers (Hill, 2008). The DataViewer allows the JCB to host the large amount of data required to accommodate images at the size and resolution at which they were acquired, as well as large image datasets that support quantitative microscopy studies and high-throughput image screens. No other journal has the ability to publish image data in this quantity, quality, or format.