A reinterpretable representation of information in a formalized manner suitable for communication, interpretation, or processing. Examples of data include a sequence of bits, a table of numbers, the characters on a page, the recording of sounds made by a person speaking, or a moon rock specimen.
CCSDS Secretariat. (2012). Reference Model for an Open Archival Information System (OAIS). Retrieved from https://public.ccsds.org/pubs/650x0m2.pdf
National Library of Medicine's Strategic Plan involving Data
A data management plan should be developed during the Process and Methods stage of the Data Life Cycle. Creating a plan before collecting and analyzing data will save time later in the project.
Benefits of a data management plan:
A checklist of elements to be included in a solid Data Management Plan.
| Did you include... | Questions to consider |
|
Types of data to be collected or created |
What type, format and volume of data? Do your chosen formats and software enable sharing and long-term access to the data? Are there any existing data that you can reuse? |
|
Data collection method and organization |
What standards or methodologies will you use? How will you structure and name your folders and files? How will you handle versioning? What quality assurance processes will you adopt? |
|
Roles and responsibilities of project members |
Who is responsible for implementing the DMP, and ensuring it is reviewed and revised? Who will be responsible for each data management activity? How will responsibilities be split across partner sites in collaborative research projects? Will data ownership and responsibilities for RDM be part of any consortium agreement or contract agreed between partners? |
| Project resources | Is additional specialist expertise (or training for existing staff) required? Do you require hardware or software which is additional or exceptional to existing institutional provision? Will charges be applied by data repositories? |
| Metadata and documentation | What information is needed for the data to be to be read and interpreted in the future? How will you capture / create this documentation and metadata? What metadata standards will you use and why? |
|
Storage and backup of data |
Do you have sufficient storage or will you need to include charges for additional services? How will the data be backed up? Who will be responsible for backup and recovery? How will the data be recovered in the event of an incident? |
|
Access and privacy requirements |
What are the risks to data security and how will these be managed? How will you control access to keep the data secure? How will you ensure that collaborators can access your data securely? If creating or collecting data in the field how will you ensure its safe transfer into your main secured systems? |
| Data Sharing | How will potential users find out about your data? With whom will you share the data, and under what conditions? Will you share data via a repository, handle requests directly or use another mechanism? When will you make the data available? Will you pursue getting a persistent identifier for your data? How will the data be licensed for reuse? |
| Data Sharing Restrictions | What action will you take to overcome or minimize restrictions? For how long do you need exclusive use of the data and why? Will a data sharing agreement (or equivalent) be required?How will you protect the identity of participants if required? Are there any restrictions on the reuse of third-party data? Will data sharing be postponed / restricted e.g. to publish or seek patents? |
|
Archiving plans for project completion |
What data must be retained/destroyed for contractual, legal, or regulatory purposes? |
| Long-term preservation plans | Where e.g. in which repository or archive will the data be held? What costs if any will your selected data repository or archive charge? Have you costed in time and effort to prepare the data for sharing / preservation? How will sensitive data be handled to ensure it is stored and transferred securely? |
Adapted from DCC. (2013). Checklist for a Data Management Plan. v.4.0. Edinburgh: Digital Curation Centre. Available online: http://www.dcc.ac.uk/resources/data-management-plans
Contact your Liaison Librarian for assistance with the data cycle before starting your research project.
You will receive help on:
Adrienne Brodie, MLS
Liaison To ASHS & SOMA
abrodie@atsu.edu
480.219.6192
Hal Bright, MIRLS
Liaison to ASDOH
hbright@atsu.edu
480.219.6036
Susan Swogger, MLIS
Liaison to CGHS, KCOM & MOSDOH
susanswogger@atsu.edu
660.626.2340
