A Provenance Task Abstraction Framework
A Provenance Task Abstraction Framework
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起源任务抽象框架
DOI:
10.1109/mcg.2019.2945720
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发表时间:
2019
影响因子:
1.8
通讯作者:
Laramee, Robert S.
中科院分区:
文献类型:
--
作者:
Bors, Christian;Wenskovitch, John;Dowling, Michelle;Attfield, Simon;Battle, Leilani;Endert, Alex;Kulyk, Olga;Laramee, Robert S.
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. We describe a use case which exemplifies our abstraction framework, demonstrating how context can influence the provenance hierarchy to support analysis. The article concludes with an agenda, raising and discussing challenges that need to be considered for successfully implementing such a framework.
DOI:
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发表时间:
1994
期刊:
Int. J. Hum. Comput. Stud.
影响因子:
--
作者:
A. Bisantz;K. J. Vicente
通讯作者:
K. J. Vicente
DOI:
--
发表时间:
2007
期刊:
影响因子:
--
作者:
作田絵里;Islam Saiful;山内清語;喜多村昇;作田 絵里;作田 絵里;作田 絵里;作田 絵里
通讯作者:
作田 絵里