Use Case Info Flow Progress
From Decision XG
The Measuring Info Flow use case requires tracking the user's progress (transitions) through a series of relevant decision states. This requirement was similar to the generic Transition pattern already well designed and available in the ontologydesignpatterns.org repository of content patterns. The goal then is to follow the eXtreme design methodology and the Neon Toolkit to import and specialize the pattern as needed, then create instances useful for testing and finally create a sparql query as a unit test to ensure the ontology includes what we need for this use case.
The Neon Toolkit was used to import the Transition pattern. The pattern already included classes representing transitions which included states, time intervals, and triggering events. The pattern was specialized by subclassing states to create decisionStates and then further to create states relevant to Information Flow, such as info gathering, info analysis, making a decision product (an information output), sharing the decision (time spent communicating the decision to others), waiting, and gathering feedback.
Instances of the pattern were created for testing. The specific decision concept instantiated is shown in the conceptual diagram below, which shows the time intervals at the bottom, the states, the transitions and the triggering events.
A sample SPARQL unit test was then created showing that we can recover the start and end times of all of the decision states. A screendump of the Neon toolkit below shows the SPARQL query being executed and the returned results.
This state and time information is key to determining amount of time spent in each state which can then be used to determine how much time is spent in states gathering, digesting and communicating as compared with actual analysis and decision-making. If the right information were available quickly to the right person at the right time, a greater amount of time could be spent analyzing and decision-making. An information format which can represent this information can help with the instrumentation of tools for collection to support a metric for measuring decision flow.