Authors:
Alexander Paulus
;
Andreas Burgdorf
;
Lars Puleikis
;
Tristan Langer
;
André Pomp
and
Tobias Meisen
Affiliation:
Chair of Technologies and Management of Digital Transformation, University of Wuppertal, Wuppertal, Germany
Keyword(s):
Semantic Modeling, Semantic Refinement, Semantic Data Management, PLASMA.
Abstract:
In recent years, the impact and usability of semantic data management has increased continuously. Still, one limiting factor is the need to create a semantic mapping in the form of a semantic model between data and a used conceptualization. Creating this mapping manually is a time-consuming process, which especially requires to know the used conceptualization in detail. Thus, the majority of recent approaches in this research field focus on a fully automated semantic modeling approach, but reliable results cannot be achieved in all use cases, i.e., a human must step in. The needed subsequent manual adjustment of automatically created models has already been mentioned in previous works, but has, in our opinion, received too little attention so far. In this paper, we treat the involvement of a human as an explicit phase of the semantic model creation process, called semantic refinement. Semantic refinement comprises the manual improvement of semantic models generated by automated appro
aches. In order to additionally enable dedicated research in this direction in the future, we also present PLASMA, a platform to utilize existing and future modeling approaches in a consistent and extendable environment. PLASMA aims to support the development of new semantic refinement approaches by providing necessary supplementary functionalities.
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