General Data Management Plan Guidelines
for the University of the South
A few initial frequently asked questions:
What is a data management plan?
Simply put a data management plan (DMP) is a clear description of the kinds of data you expect to collect through your studies, a description of how you will make that data available to others (and under what conditions), and how you will archive that data to safeguard it for future users.
Why do I need a data management plan?
One could argue that thinking about the elements of a DMP are simply part of being a good scholar, research and/or scientist. Data should be freely available to the research community as a whole in the hopes that such open sharing will lead to significant new knowledge. On the other hand, a very practical, operational answer is that an increasing number of funding agencies are requiring you to file a DMP in one form or another as a required part of your application. For example, NIH has long expected researchers to document how the will disseminate their data and make it available to others as an integral part of a proposal. More recently, NSF has required all proposals (submitted after Jan 18, 2011) to include a two-page DMP as a required supplementary document in a proposal.
A guide to creating an NSF DMP:
As the NSF requirement for a data plan is new, the precise requirements are somewhat uncertain. Each directorate has issued guidelines (which can be found at http://www.nsf.gov/bfa/dias/policy/dmp.jsp). Example DMPs generated for recent NSF proposals submitted by Sewanee faculty can be found at YYY and ZZZ. It should be recognized that these DMPs are part of currently pending grants, and hence have not been vetted by NSF before. You are welcome to adopt any of the components of these plans, as practical. In particular, the information about re-use and archiving should be of relatively broad relevance. Some very helpful resources can be found at the following links:
http://www2.lib.virginia.edu/brown/data/
http://escience.washington.edu/blog/writing-nsf-data-management-plan
To create your DMP, it is recommended that you begin by answering the applicable questions from the sections below (which are based on the template available at Univ. of Virginia). Use each section header as a header in your DMP and the answers to the questions as the prose in that section (edited to make sense as paragraphs).
If you would like someone to review your DMP, please send it to Penny Cowan in the Library, Leigh Lentile in the Office of Sponsored Research or Rob Bachman, the Director of Undergraduate Research.
DMP Sections:
I. Types of Data—Samples, collections, images, numerical information, software or other materials produced as part of the project.
1. What data/data types will be generated in the research? Give a short description, including approximate quantities (if known) of the data you expect to accumulate. Examples might include experimental measurements, qualitative observational data, models, simulations, etc.
2. How will this data be captured, created and/or manipulated?
3. If you plan to use existing data, state the source of this data. Also note any relationship between the existing data you plan to use and any additional data you will collect.
II. Data and Metadata Standards—Standards to be used with regard to data and metadata.
1. Are there existing standards for the types of data you will collect? (Are there established databases with existing standards?) If the answer to this question is no, or the existing standards are inadequate, state this fact and document you proposed solutions.
2. What file formats will the data be stored in? Why?
3. What contextual details (metadata) are needed to make the data collected meaningful to others? How will you capture these details with the data?
4. What forms/formats will be used for the metadata?
5. Are there specific reasons for your choice of standards (accepted standards, widespread usage, digital staff advice)?
III. Policies for access and sharing along with provisions for privacy protection if applicable.
1. How will the data be made available? Are there specific resources needed to make this possible?
2. When will data be made available (at publication, etc)? Give any details related to embargo periods for commercial/patent/other reasons.
3. What process will others use to gain access to the data? Will access be chargeable?
4. What are the intellectual property protections, if any, on the data? Does the investigator/creator of the data retain the right to use the data prior to making it open to a wider group?
5. Are there any privacy/protection issues associated with the data? If yes, how will these be resolved? (Removal of identifying information, institutional ethical committee review, consent forms, etc).
6. Is the data “personal data” as defined by the Data Protection Act of 1998? If yes, an equivalent to the HIPAA requirement is needed.
7. If needed, how will you comply with any IRB protocol that was approved as part of the data collection process?
8. Will the data be covered by copyright? If so, who owns the intellectual property associated with the data? How will it be licensed (if applicable)?
IV. Policies for re-use/re-distribution
1. What groups will be interested in the data now and in the foreseeable future?
2. Will any restrictions need to be placed on access to the data? Are there any specific reasons not to share or re-use the data?
V. Archival Plans
1. What is the long-term strategy for maintaining, curating and archiving the data?
2. Where will the data be deposited?
3. Are any transformations needed to prepare the data for archiving? (Change of file formats, data cleaning, etc.)
4. What metadata/documentation will be submitted with the data or created on deposit to ensure that the data remains reusable into the future?
5. Will related information (references, reports, papers, original proposals, etc) be deposited with the data?
6. How long will the data be kept beyond the project period?
7. What procedures have been developed for long-term storage with respect to backup and preservation of information?
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