Practices for Transparent Government (CATO Institute)

Government transparency is a widely agreed upon goal but progress on achieving it has been very limited. Real transparency would provide a burst of information that informs stromger public oversight of government.

Four key data practices that support government transparency are:

  1. authoritative sourcing
  2. availability
  3. machine-discoverability
  4. machine-readability

  1. Authorative sourcing

    means producing data as near to its origination as possible, and promptly so that the public uniformly comes to rely on the best sources of data.

    A practice that promotes authority is real-time or near-real-time publication.

    The authority required for transparency is earned through prompt publication of data in useful open standards - authority through being awesome

  2. Availability

    is another set of practices that ensure consistency and confidence in data.

    Permanency is an important part of availability. A thing is not truly available unless it existsa for good.

    Data should be stable and consistent and should always be found in the same location. Trying data excavations in shifting sands is not worth the effort.

    Data is available when it is complete. A partial reord is unreliable and it cannot be used to tell stories that full data records can, so it does not foster transparency.

    Data is fully available when it is structured using standards that are unencumbered by intellectual property claims. If a string of text in a database is copyrightted, that datum is not fully available. It is encumbered by legal claims that limits its use.

  3. Machine discoverability

    occurs when information is arranged so that a computer can discover the data and follow links within the data. Machine discoverability is produced when data is presented consistent with a host of customs about how data is identified and referenced, the naming of documents and files, the protocols for communicating data and the organization of data withing files.

    Machine discoverability is enhanced thru the use of web standards such as HTTP and HTML. A consistent URL structure is an important way of making data available.

    Discoverbility is a function of how hard it is for machines to locate data.

  4. Machine readability

    is the heart of transparency because it allows the many meanings of data to be discovered. Machine readable data is logically structured so that computers can generate the myriad stories that the data has to tell and put it to the hundreds of uses the public would make of it in government oversight.

    Data's value depends not only on its subject, but also on the format in which the information is stored, Format determines the value of the resource and the extent to which the public can exploit it for analysis and reuse.

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