Interval and location recommendations for backing up your data
Consistent use of standard terminology for categorical data values and metadata descriptors facilitates the understanding, integration, discovery, and use of your data products.
Before data collection begins, a backup policy should be in place to help guide data users and identify roles and responsibilities of the users.
Recommends kinds of data and analysis products to consider preserving, and factors to use in decision-making.
Recommendations for the long-term storage of data and how to document the file formats so that others can readily assess the useability of the data and determine its potential for integration with other datasets
How to prepare virtual datasets for flexible retrieval
Methods to ensure the integrity of data backups
Good storage media monitoring and management practices will help ensure that access is maintained to both actively used and archived data.
Identify the specific content needed to describe your data for management, preservation, and discovery. Use this content to select the relevant metadata standard.
How to identify data sensitivity and make the appropriate security classification
A research project may generate many different datasets, as well as many iterations of the same dataset, requiring decisions about which data have significant long-term value and need to be kept.
Identify suitable repositories for the data early to help shape the data management plan so that it fits that repository’s requirements.
Information on what should be included in a Data Management Plan
Decision about how to manage and archive multimedia (images, video, sound) for access and preservation should be made before data are collected.
Preservation of raw data is critical for data reuse
Provide a dataset citation so that those who have collected, prepared, and archived the data can receive proper credit.
Standard, stable identifiers should be given to data products to ensure consistency
All individuals who claim ownership rights to the data should be identified and should receive recognition for their part in the creation of the data.
Recommendation and example of data storage and appropriate precision