Description: This problem originates from the work of the W3C Decision Incubator group. However, the problem could be applicable to other areas than decision-making.
The problem concerns how to model metrics that can be applied in decision-making situations. A metric is a way to assess options, to make a decision. If a metric is formally described, it can be better understood, reused, and in some cases applied automatically. We would also like to be able to detect possible metrics automatically, i.e., given a dataset we would like to be able to determine what metrics could be applied to it.
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|Competency Questions||What metrics can be applied to this dataset? Can this metric be reused for this new dataset? What metric was applied to make this decision?|
|Scenarios||Given a dataset with information about earthquakes, the data could be assessed using metrics such as the magnitude of the earthquake, the distance from some given location, the number of injured. If the dataset uses some datatype properties, this could be seen as an indication of a possible metric, e.g., a float property representing the magnitude indicates that metrics applicable to float numbers could be applicable.|
|Proposed Solutions (OWL files)|
|Submission to event|