This is Lesson 2 of the DataONE Data Management learning series. This lesson covers Data Management: Data Sharing

The topics covered in this lesson include: the role of data sharing within the lifecycle, the value of data sharing, concerns about data sharing, and methods for making data sharable.

After completing this lesson, you will be able to recognize the benefits of sharing scientific data, address concerns about sharing data, outline a process for making data sharable, and identify mechanisms for sharing data.

Data sharing should be addressed throughout the Data Life Cycle Guide to social science data preparation and archiving: Best practice throughout the data life cycle, 4th edition (ICPSR, 2009)

Effective data sharing requires careful thought during each stage of the data development process including:

• description and documentation of the data process, content, and character;
• deposition and storage of the data in a location from which it can be accessed or shared;
• preservation of the data using a format and media that enable long term reuse; and
• making the data discoverable by publishing information about the data in research publications, data clearinghouses and data distribution portals.

Why expend the extra effort to share data? Because it benefits the public, the research sponsor, the research community and, perhaps most importantly, the researcher.

How does the public benefit from shared research? The more informed the public the better they are able to understand and contribute toward effective public and personal decisions:

• environmental and economic planning
• federal, state and local policies
• social choices such as voting, use of tax dollars and education options
• personal lifestyles and health choices such as exercise, smoking, and nutrition

Australian Bureau of Statistics, National Statistical Service (2009) A good practice guide to sharing your data with others, Vers. 1. http://www.nss.gov.au/nss/home.nsf/NSS/E6C05AE57C80D737CA25761D002FD676?opendocument

Niu, J. (2006). Reward and Punishment Mechanisms for Research Data Sharing. IASSIST Quarterly, Winter 2006.

Why do research sponsors encourage data sharing? Because sponsors have an obligation to maximize the investment of research dollars.

Data sharing enhances the value of the research investment by enabling external reviewers to verify the project performance metrics and outcomes. This not only increases the credibility of the data but also spurs new research that can build upon the initial investment and advance the science rather than duplicate expenditures.

Guide to social science data preparation and archiving: Best practice throughout the data life cycle, 4th edition (ICPSR, 2009)

Piwowar, H.A. (2011). A new task for NSF reviewers:  Recognizing the value of data reuse. http://researchremix.wordpress.com/2011/05/28/dear-nsf-reviewers/

The scientific community as a whole also benefits from sharing among researchers. Data sharing allows researchers to build upon one another's work and to further, rather than duplicate, the science by exploring new findings or combining findings into meta analyses that cannot be performed with individual data. In sharing data, the scientific community expands both individual perspectives and the collective comprehension.

Guide to social science data preparation and archiving: Best practice throughout the data life cycle http://www.icpsr.umich.edu/files/ICPSR/access/dataprep.pdf, 4th edition (ICPSR, 2009)

Piwowar HA, Becich MJ, Bilofsky H, Crowley RS, on behalf of the caBIG Data Sharing and Intellectual Capital Workspace (2008) Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers. PLoS Med 5(9): e183. doi:10.1371/journal.pmed.0050183

Teeters, J.L., Harris, K.D., Millman, K.J., Olshausen, B.A., Sommer, F.T. (2008). Data Sharing for Computational Neuroscience. Neuroinform, DOI 10.1007s12021-008-9009-y

National Institute of Health (NIH) (2003). NIH Data Sharing Policy and Implementation Guidelines.

Borgman, C.L. Research Data: Who will share what, with whom, when, and why? In Proceedings of the China-North American Library Conference, Beijing , September 2010. (http://works.bepress.com/borgman/238/)

Access to related research enables members of the scientific community to better reproduce, compare and assess methods and results. Scientists are able to learn from one another and educate new researchers as to the most current and significant findings.

And finally, how does the independent researcher benefit from data sharing? When scientists share their data, they gain recognition as an authoritative source and respect as a wise investment for research dollars. When data are exposed, feedback from the broader community can be used to improve the quality and presentation of the data. Shared data also allows for greater opportunity for data exchange and networking opportunities with peers and potential collaborators.

• Piwowar HA, Becich MJ, Bilofsky H, Crowley RS, on behalf of the caBIG Data Sharing and Intellectual Capital Workspace (2008) Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers. PLoS Med 5(9): e183. doi:10.1371/journal.pmed.0050183
• Teeters, J.L., Harris, K.D., Millman, K.J., Olshausen, B.A., Sommer, F.T. (2008). Data Sharing for Computational Neuroscience. Neuroinform, DOI 10.1007s12021-008-9009-y
• Borgman, C.L. Research Data: Who will share what, with whom, when, and why? In Proceedings of the China-North American Library Conference, Beijing , September 2010. (http://works.bepress.com/borgman/238/)

Researchers may worry that the data will be taken out of context, misinterpreted or used inappropriately. They may also be concerned about maintaining the confidentiality and security of sensitive data. Business concerns may arise as well. Will data users give proper credit and acknowledgement to the scientist? Will the scientist lose a competitive advantage by sharing this valuable resource?

• Niu, J. (2006). Reward and Punishment Mechanisms for Research Data Sharing. IASSIST Quarterly, Winter 2006.
• Guide to social science data preparation and archiving: Best practice throughout the data life cycle, 4th edition (ICPSR, 2009)
• Borgman, C.L. Research Data: Who will share what, with whom, when, and why? In Proceedings of the China-North American Library Conference, Beijing , September 2010. (http://works.bepress.com/borgman/238/)

Each of these issues can, in great part, be addressed by providing rich data documentation known as ‘metadata’.

• Niu, J. (2006). Reward and Punishment Mechanisms for Research Data Sharing. IASSIST Quarterly, Winter 2006.
• Guide to social science data preparation and archiving: Best practice throughout the data life cycle, 4th edition (ICPSR, 2009)
• Borgman, C.L. Research Data: Who will share what, with whom, when, and why? In Proceedings of the China-North American Library Conference, Beijing , September 2010. (http://works.bepress.com/borgman/238/)

See this GREAT paper for more information about each of these important aspects of sharing data in a useful way.

See this GREAT paper for more information about each of these important aspects of sharing data in a useful way.

In 2003, a group of scientists from the National Institutes of Health, the Food and Drug Administration, drug and medical imaging industries, universities, and nonprofit groups joined in a collaborative effort to find the biological markers that show the progression of Alzheimer’s disease in the human brain.

The goal of this project was to do research on a massive scale that would involve sharing and making accessible all the data available to anyone in the world with a computer.

Dr. John Trojanowski, an Alzheimer’s researcher at the University of Pennsylvania, stated “It’s not science the way most of us have practiced it in our careers. But we all realized that we would never get biomarkers unless all of us parked our egos and intellectual-property noses outside the door and agreed that all of our data would be made public immediately.”

[Our “Data in Real Life” segment features a news report on this research. (?)]

In summary, data sharing adds value to the data. As such, it is the responsibility of the researcher to share their data. Metadata should be created for data resources to support data accountability, liability and usability. Research sponsors expect, and increasingly require, data to be shared.   THIS CONCLUDES Lesson 2.

To assess your learning on the content presented in this lesson, proceed to the next slide take the quiz.

More stuff:

• Inter-university Consortium for Political and Social Research (ICPSR), ICPSR Guide to Data Preparation and Archiving: Best Practice Throughout the Data Life Cycle (ICPSR, 2009; http://www.icpsr.umich.edu/files/ICPSR/access/dataprep.pdf). [4th Edition]
• Australian Bureau of Statistics - National Statistical Service (ABS-NSS), A good practice guide to sharing your data with others (ABS-NSS, 2009; http://www.nss.gov.au/nss/home.nsf/NSS/E6C05AE57C80D737CA25761D002FD676?opendocument). [Vers. 1]
• H.A. Piwowar, A new task for NSF reviewers:  Recognizing the value of data reuse. ResearchRemix vers. May 28, 2011 (http://researchremix.wordpress.com/2011/05/28/dear-nsf-reviewers/). [blog posting of draft]
• H.A. Piwowar, M.J. Becich, H. Bilofsky, R.S. Crowley, Towards a Data Sharing Culture: Recommendations for Leadership from Academic Health Centers. PLoS Med. 5(9), e183 (2008), doi:10.1371/journal.pmed.0050183. [on behalf of the caBIG Data Sharing and Intellectual Capital Workspace]
• National Institute of Health (NIH) “NIH Data Sharing Policy and Implementation Guidelines” (NIH, Washington D.C., 2003, http://grants.nih.gov/grants/policy/data_sharing/data_sharing_guidance.htm).
• J. Niu, “Reward and Punishment Mechanisms for Research Data Sharing”. IASSIST Quarterly, Winter (2006).
• C.L. Borgman, “Research Data: Who will share what, with whom, when, and why?” in Proceedings of the China-North American Library Conference, Beijing , September 2010 (http://works.bepress.com/borgman/238/)