SCAPE: creating machine understandable policy from human readable policy

SCAPE: creating machine understandable policy from human readable policy

 

In Policy Representation we have been looking at the different levels of policy that an organisation should consider

We have identified three levels:

  • Guidance policy: Very high level statements which apply to the whole organisation
  • Preservation Procedure policy:  Natural language human readable policy which may encompass the whole organisation or may be focused on a particular collection or material type depending on the needs of the particular organisation
  • Control level policy:  These are statements derived from the Preservation Level, which are in both a human readable and machine-readable form and relate to a specific collection or material type.

The first two levels are written by humans to be read by humans, the third level will be available in both human and readable forms.  If one intends to use the SCAPE watch and planning tools, such as SCOUT and PLATO, then machine readable policy statements will be needed to inform the operation of the tools and can be used in both tools without further modifications.

Getting from policy which is aimed at humans to policy which a machine can evaluate is not a straightforward process.  We are developing some guidance and trying the process out with policy from SCAPE partners.

The control policy model will be described in further blogs, but to summarise:  for a given content set and user community, there will be a preservation case which has a series of measurable objectives, which together define machine understandable policy which applies in this case.  Examples of objectives might include permittable file formats or the  presence of documentation.

Steps in the process
 Steps Description

Stage 1: Whole policy activities

1. Identify the content set the policy addresses
2. Identify the user communities/roles required by the policy
3. Map policy statements to high level concepts.

This stage has activities which apply equally to all parts of the written policy.

As a result of the steps in this stage the content,  users and topics addressed will  be identified

Stage 2: Policy statements within the whole policy

1. Clarification of implicit meaning
2 .Identification of control policy preservation case
3. Identification of objectives
4. Generate control statements

Taking each policy statement in turn.

The steps in this stage of process are designed to ensure that all the information a machine will need to have is explicitly stated and the the parameters to be measured are chosen

Stage 3: Review the Preservation Cases and identify any rationalisation required Finally, the final stage is an opportunity to review the complete set of control policies and to make any adjustments required.

 Points to note 

This is work in progress, but from the work we have done so far, we have reached these conclusions:
  • Having explicit policy in natural language is important
  • Expressing policy in machine testable ways is more complex but can bring benefit through use of tools
  • Natural language preservation procedure policy defines acceptable states in statements but control level defines measurable attributes in questions
  • Written policy is at a fairly abstract level and practicalities may be addressed in implementation plan/job procedure document or one-off project plan
  • Implicit information understood by human audience will need explicitly expressing for computers

 

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