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Visual analytics tools integrate provenance recording to externalize analytic processes or user insights. Provenance can be captured on varying levels of detail, and in turn activities can be characterized from different granularities. However, current approaches do not support inferring activities that can only be characterized across multiple levels of provenance. We propose a task abstraction framework that consists of a three stage approach, composed of (1) initializing a provenance task hierarchy, (2) parsing the provenance hierarchy by using an abstraction mapping mechanism, and (3) leveraging the task hierarchy in an analytical tool. Furthermore, we identify implications to accommodate iterative refinement, context, variability, and uncertainty during all stages of the framework. A use case describes exemplifies our abstraction framework, demonstrating how context can influence the provenance hierarchy to support analysis. The paper concludes with an agenda, raising and discussing challenges that need to be considered for successfully implementing such a framework.
This article was published in the following journal.
Name: IEEE computer graphics and applications
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The observation and analysis of movements in a task with an emphasis on the amount of time required to perform the task.
The study of ancient inscriptions and modes of writing. It includes the deciphering of manuscripts and other forms to determine their date, provenance, etc. (Webster's 1st ed)
The construction or arrangement of a task so that it may be done with the greatest possible efficiency.
Simultaneous task performance, or switching between tasks in a concentrated period of time.
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.