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Practical Policy Categorization

  • Creator
    Discussion
  • #138838

    Reagan Moore
    Member

     

    Practical Policy

     
     

    The Practical Policy working group of the Research Data Alliance is developing examples of policies that can be used to control data management applications. The policies are expressed as computer actionable rules. The rules can be used to enforce management policies, automate administrative functions, validate assessment criteria, and automate data analysis pipelines.

     

    Collection of policies

    Data Management

    Data management policies are intended to automate administrative tasks. Examples include managing access controls, managing storage caches, managing ingestion of files, and managing migration of files.

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    Preservation

    Preservation policies are used to enforce assertions about the records in an archive, including authenticity, chain of custody, integrity, and original arrangement.

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    Replication

    Replication policies are used to simplify disaster backup by managing distributed copies of each file. The replication policies may interact with policies for managing backups and policies for versioning of files.

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    Sharing

    Sharing policies are used to manage distribution of data between collaborators and time-dependent access controls.


    Federation

    Federation policies are used to manage interactions between independent data management systems, including automated synchronization of holdings, replication of data, and sharing of data.


    Description

    Description policies are used to automate extraction of descriptive metadata from files.

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    Trustworthiness

    Trustworthiness assessment criteria have been defined in the ISO 16363 standard, and include criteria for monitoring repository management functions.

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    Caching

    Caching policies are used for managing interactions with object stores and tape archives. A standard example is the use of a cache to aggregate files into a container before writing to tape.


    Processing

    Processing workflows are used to capture the knowledge needed to execute a research analysis. The workflow could include access to remote data repositories, transformation of the retrieved data, and execution of an analysis code.

     

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