• Assure data backup strategies that guard against any loss of irreplaceable data (e.g. Original or Synthesized Product data types that cannot be easily and economically regenerated).

  • Assure that when the data are migrated to new media or translated to another form (changing the original data format), no information is lost and recovery from errors is always possible.

  • Assure that information integrity and access are not compromised during software and technology evolution.

  • Assure that data management systems can support the growth of archived information that occurs during the data lifecycle. During a data lifecycle the archived information may be enhanced by reprocessing, error correction, and with the addition of supplemental data, quality control assessments, and other metadata derived from the scientific research and knowledge building processes.

  • Maintain close interactions with the scientific community and evolving user base to capture information about data use and limitations.

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