"The DMP should describe physical and cyber resources and facilities that will be used for the effective preservation and storage of research data. These can include third party facilities and repositories."
Please note that these DMP excerpts are copyrighted by their respective authors.
“As previously mentioned, data and codes developed during this research will be stored on both the PIs’ groups' local servers and on the campus servers. The campus servers are automatically backed up every day. Data generated at the University of Michigan will be stored in a repository called Deep Blue Data, while data generated at the University __________ will be stored in a repository called ______ providing 100Gb (expandable).”
Mentioning both short-term and long-term storage is good practice, and these are reliable storage options with automatic back-ups.
“All data will be available at request immediately after the scientific results are published and will be stored at least another five years on magnetic and optical storage devices (hard disks, CDs, DVDs). Optical storage devices will serve the purpose of the Disaster Recovery Plan.”
Optical storage media are not sufficiently reliable for long-term archival storage.
“Upon finalization, the calving histories we derive from satellite data will be submitted to the National Snow and Ice Data Center (NSDIC) for permanent archival, and will also be converted into .kmz files for display in Google Earth, as part of a broader effort to catalog our results and inform the public about coastal change in the region of Antarctica.”
This is an excellent example of choosing an appropriate disciplinary data repository.
“At the end of the project, original laboratory notebooks will be secured by the PI in his campus office, and computer files will be stored in the form of hard-drive storage as well as on the University of Michigan Canvas websites.”
“The original raw and processed data will remain on the lab computer under the account of the person that generated and analyzed the data. These are standard procedures in our lab.”
None of the three storage solutions listed here is appropriate for long-term archival storage.
“We use a mirrored CVS server to store the current as well as all earlier versions of the simulation software.... The CVS repositories are backed up regularly.... Our simulation software is checked out from the CVS server every night, and we run a large test suite on several machines. The results of these tests are sent back to a web site that we check every morning, so we can discover minor or major problems with the software or hardware within a day. The machines running the nightly tests are distributed in the department of AOSS, across the campus of the University of Michigan, and also include a machine in California.”
See DataONE Best Practices, Create and document a data backup policy and Ensure integrity and accessibility when making backups of data
“The data will include a README file with links to any reports or papers generated using it.”
Who will maintain the links when new papers are published?
Once data are ready to be archived and shared they will most likely need to be transferred to a repository or data center with a commitment to long-term curation. Consider both backup and archival strategies as part of your data management planning process.
Your first choice for long-term data preservation should be a disciplinary repository serving a relevant area of research. If no such repository exists, consider our institutional repository, Deep Blue Data. Perpetual archiving in a curated disciplinary or institutional repository is the preferred solution for long-term data preservation. If there are no applicable repositories, describe how you will keep the data accessible for its expected useful lifespan.
Two ways to approach finding a repository (please note that services mentioned are options for you to investigate further, not endorsements):