Data Management Plans
“A goal without a plan is just a wish." Antoine de Saint-Exupery (1900 -1944)
Earth Scientists spend considerable time collecting data for field studies and experiments. Because data have value for both the current project and for future researchers, a good data management plan enables data to retain their value. Sponsors recognize the importance of well-curated data products for future research and many are requiring data management plans to maximize the effectiveness of research funding beyond the lifetime of individual projects (NSF Notice).
A data management plan describes the data that will be authored and how the data will be managed and made accessible throughout its lifetime. The contents of the data management plan should include:
- the types of data to be authored;
- the standards that would be applied, for example format and metadata content;
- provisions for archiving and preservation;
- access policies and provisions; and
- plans for eventual transition or termination of the data collection in the long-term future.
The checklists and links at the bottom of this page contain additional information about these data management topics.
In January 2011 NSF added the requirement for a data management plan (DMP) to be included within proposals and have since provided guidelines for the structure of this plan. These guidelines are incorporated into the newly developed DMPTool (see below) of which DataONE is a founding organisation. Below are some example DMPs developed by participants of a DataONE Best Practices workshop, that conform to these guideline.
NSF General: Mauna Loa example
NSF General: Rio Grande example
NSF General: HDF Map example
NSF General: Nutrient Network example
NSF BIO: E. afffinis example
DMPTool
A collaboration of multiple institutions, including DataONE, have worked to develop the DMPTool to help you:
- Create ready-to-use data management plans for specific funding agencies
- Meet funder requirements for data management plans
- Get step-by-step instructions and guidance for your data management plan as you build it
- Learn about resources and services available at your institution to help fulfill the data management requirements of your grant
The DMPTool, released in October 2011, walks researchers through the steps neccesary to create a generic NSF DMP or a DMP targeted to one of six NSF Directorates. You can also save, preview and export your plans and future functionality will allow you to share DMPs with collaborators and other researchers.
Checklists
A group at the California Digital Library, including Patricia Cruse and John Kunze, both members of the DataONE Leadership Team and Valerie Enriquez (DataONE Summer Intern), has identified several data management checklists that are currently in use in the community. This group analyzed what each checklist included, what was common among checklists, and what was unique across checklists. The results of that analysis are summarized in the following table.
| COMPONENT |
MIT
|
DCC
|
ANDS
|
CESSDA
|
JPL
|
QUT
|
DAAC
|
Cornell |
|---|---|---|---|---|---|---|---|---|
| OBJECT CHARACTERISTICS | ||||||||
| Data type (raw, computational, observational) |
√
|
√
|
X
|
X
|
X
|
√
|
√
|
√
|
| Naming conventions |
√
|
X
|
√
|
√
|
X
|
√
|
√
|
X
|
| Format types |
√
|
√
|
√
|
X
|
√
|
√
|
√
|
√
|
| CONTEXTUAL INFORMATION | ||||||||
| Software (resilience, obsolescence) |
√
|
√
|
X
|
X
|
X
|
√
|
√
|
X
|
| Required and stored metadata |
√
|
√
|
√
|
X
|
X
|
√
|
√
|
√
|
| Documentation (may relate to metadata) |
√
|
√
|
√
|
√
|
√
|
√
|
√
|
√
|
| Intellectual control (copyright, ownership) |
√
|
√
|
√
|
√
|
X
|
√
|
√
|
X
|
| Transfer of Responsiblity |
?
|
?
|
?
|
?
|
?
|
?
|
?
|
√
|
| ENVIRONMENTAL / STORAGE FACTORS | ||||||||
| Data retention |
√
|
√
|
√
|
X
|
X
|
√
|
√
|
√
|
| Anticipated volume |
√
|
√
|
X
|
X
|
√
|
X
|
√
|
X
|
| Backup |
√
|
√
|
√
|
√
|
X
|
√
|
√
|
√
|
| USAGE | ||||||||
| Access restrictions |
√
|
√
|
√
|
X
|
X
|
√
|
X
|
√
|
| Privacy / anonymization |
√
|
√
|
√
|
√
|
X
|
√
|
√
|
√
|
| Security |
√
|
√
|
√
|
√
|
X
|
√
|
√
|
√
|
| Audience |
√
|
√
|
√
|
X
|
X
|
X
|
√
|
X
|
MIT: Massachusetts Institute of Technology
DCC: Digital Curation Centre
ANDS: Australian National Data Service
CESSDA : Council of European Soc. Sci. Data Archives
JPL: Jet Propulsion Laboratory
QUT: Queensland University of Technology
DAAC: ORNL Distributed Active Archive Center
Cornell Univesity
University of California Curation Center
Valerie Enriquez, DataONE summer intern