Data management plan
Encyclopedia
A data management plan is a formal document that outlines how you will handle your data both during your research, and after the project is completed . The goal of a data management plan is to consider the many aspects of data management
, metadata
generation, data preservation, and analysis before the project begins; this ensure that data are well-managed in the present, and prepared for preservation in the future.
Funding agencies are beginning to require data management plans as part of the proposal and evaluation process.
are the contextual details, including any information important for using data. This may include descriptions of temporal and spatial details, instruments, parameters, units, files, etc. Metadata is commonly referred to as “data about data”. Consider the following:
The data management plan should include how these costs will be paid.
must include a Data Management Plan that is no more than two pages . This is a supplement (not part of the 15 page proposal) and should describe how the proposal will conform to the Award and Administration Guide policy (see below). It may include the following:
Policy summarized from of the NSF
Award and Administration Guide, Section 4 (Dissemination and Sharing of Research Results):
Data management
Data management comprises all the disciplines related to managing data as a valuable resource.- Overview :The official definition provided by DAMA International, the professional organization for those in the data management profession, is: "Data Resource Management is the development and execution...
, metadata
Metadata
The term metadata is an ambiguous term which is used for two fundamentally different concepts . Although the expression "data about data" is often used, it does not apply to both in the same way. Structural metadata, the design and specification of data structures, cannot be about data, because at...
generation, data preservation, and analysis before the project begins; this ensure that data are well-managed in the present, and prepared for preservation in the future.
Importance
Preparing a data management plan before data are collected ensures that data are in the correct format, organized well, and better annotated. This saves time in the long term because there is no need to re-organize, re-format, or try to remember details about data. It also increases research efficiency since both the data collector and other researchers will be able to understand and use well-annotated data in the future. One component of a good data management plan is data archiving and preservation. By deciding on an archive ahead of time, the data collector can format data during collection to make its future submission to a database easier. If data are preserved, they are more relevant since they can be re-used by other researchers. It also allows the data collector to direct requests for data to the database, rather than address requests individually. Data that are preserved have the potential to lead to new, unanticipated discoveries, and they prevent duplication of scientific studies that have already been conducted. Data archiving also provides insurance against loss by the data collector.Funding agencies are beginning to require data management plans as part of the proposal and evaluation process.
Information about data & data format
- Include a description of data to be produced by the project. This might include (but is not limited to) data that are:
- Experimental
- Observational
- Raw or derived
- Physical collections
- Models
- Simulations
- Curriculum materials
- Software
- Images
- How will the data be acquired? When and where will they be acquired?
- After collection, how will the data be processed? Include information about
- Software used
- Algorithms
- Scientific workflowsWorkflowA workflow consists of a sequence of connected steps. It is a depiction of a sequence of operations, declared as work of a person, a group of persons, an organization of staff, or one or more simple or complex mechanisms. Workflow may be seen as any abstraction of real work...
- Describe the file formats that will be used, justify those formats, and describe the naming conventions used.
- Identify the quality assurance & quality control measures that will be taken during sample collection, analysis, and processing.
- If existing data are used, what are their origins? How will the data collected be combined with existing data? What is the relationship between the data collected and existing data?
- How will the data be managed in the short-term? Consider the following:
- Version control for files
- Backing up data and data products
- Security & protection of data and data products
- Who will be responsible for management
Metadata content and format
MetadataMetadata
The term metadata is an ambiguous term which is used for two fundamentally different concepts . Although the expression "data about data" is often used, it does not apply to both in the same way. Structural metadata, the design and specification of data structures, cannot be about data, because at...
are the contextual details, including any information important for using data. This may include descriptions of temporal and spatial details, instruments, parameters, units, files, etc. Metadata is commonly referred to as “data about data”. Consider the following:
- What metadata are needed? Include any details that make data meaningful.
- How will the metadata be created and/or captured? Examples include lab notebooks, GPS hand-held units, Auto-saved files on instruments, etc.
- What format will be used for the metadata? Consider the metadata standardsMetadata standardsMetadata standards are requirements which are intended to establish a common understanding of the meaning or semantics of the data, to ensure correct and proper use and interpretation of the data by its owners and users...
commonly used in the scientific discipline that contains your work. There should be justification for the format chosen.
Policies for access, sharing, and re-use
- Describe any obligations that exist for sharing data collected. These may include obligations from funding agencies, institutions, other professional organizations, and legal requirements.
- Include information about how data will be shared, including when the data will be accessible, how long the data will be available, how access can be gained, and any rights that the data collector reserves for using data.
- Address any ethical or privacy issues with data sharing
- Address intellectual propertyIntellectual propertyIntellectual property is a term referring to a number of distinct types of creations of the mind for which a set of exclusive rights are recognized—and the corresponding fields of law...
& copyrightCopyrightCopyright is a legal concept, enacted by most governments, giving the creator of an original work exclusive rights to it, usually for a limited time...
issues. Who owns the copyright? What are the institutional, publisher, and/or funding agency policies associated with intellectual property? Are there embargoes for political, commercial, or patent reasons? - Describe the intended future uses/users for the data
- Indicate how the data should be cited by others. How will the issue of persistent citation be addressed? For example, if the data will be deposited in a public archive, will the dataset have a digital object identifierDigital object identifierA digital object identifier is a character string used to uniquely identify an object such as an electronic document. Metadata about the object is stored in association with the DOI name and this metadata may include a location, such as a URL, where the object can be found...
(doi) assigned to it?
Long-term storage and data management
- Researchers should identify an appropriate archive for long-term preservation of their data. By identifying the archive early in the project, the data can be formatted, transformed, and documented appropriately to meet the requirements of the archive. Researchers should consult colleagues and professional societies in their discipline to determine the most appropriate database, and include a backup archive in their data management plan in case their first choice goes out of existence.
- Early in the project, the primary researcher should identify what data will be preserved in an archive. Usually, preserving the data in its most raw form is desirable, although data derivatives and products can also be preserved.
- An individual should be identified as the primary contact person for archived data, and ensure that contact information is always kept up-to-date in case there are requests for data or information about data.
Budget
Data management and preservation costs may be considerable, depending on the nature of the project. By anticipating costs ahead of time, researchers ensure that the data will be properly managed and archived. Potential expenses that should be considered are- Personnel time for data preparation, management, documentation, and preservation
- Hardware and/or software needed for data management, backing up, security, documentation, and preservation
- Costs associated with submitting the data to an archive
The data management plan should include how these costs will be paid.
NSF Data Management Plan
All grant proposals submitted to NSFNational Science Foundation
The National Science Foundation is a United States government agency that supports fundamental research and education in all the non-medical fields of science and engineering. Its medical counterpart is the National Institutes of Health...
must include a Data Management Plan that is no more than two pages . This is a supplement (not part of the 15 page proposal) and should describe how the proposal will conform to the Award and Administration Guide policy (see below). It may include the following:
- The types of data
- The standards to be used for data and metadata format and content
- Policies for access and sharing
- Policies and provisions for re-use
- Plans for archiving data
Policy summarized from of the NSF
National Science Foundation
The National Science Foundation is a United States government agency that supports fundamental research and education in all the non-medical fields of science and engineering. Its medical counterpart is the National Institutes of Health...
Award and Administration Guide, Section 4 (Dissemination and Sharing of Research Results):
- Promptly publish with appropriate authorship
- Share data, samples, physical collections, and supporting materials with others, within a reasonable time frame
- Share software and inventions
- Investigators can keep their legal rights over their intellectual property, but they still have to make their results, data, and collections available to others
- Policies will be implemented via
- Proposal review
- Award negotiations and conditions
- Support/incentives
External links
- DMPTool: Guidance and resources for data management plans
- California Digital Library, University of California Curation Center (UC3)
- DataONE
- University of Virginia Library
- Digital Curation Centre
- University of Michigan Library
- NSF Grant Proposal Guidelines
- Inter-University Consortium for Political and Social Research
- LTER Blog: How to write a data management plan