2 research outputs found

    Unveiling Relations in the Industry 4.0 Standards Landscape based on Knowledge Graph Embeddings

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    Industry~4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of \emph{empowering interoperability} in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans^* family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.Comment: 15 pages, 7 figures, DEXA2020 Conferenc

    Towards Vocabulary Development by Convention

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    A major bottleneck for a wider deployment and use of ontologies and knowledge engineering techniques is the lack of established conventions along with cumbersome and inefficient support for vocabulary and ontology authoring. We argue, that the pragmatic development by convention paradigm well-accepted within software engineering, can be successfully applied for ontology engineering, too. However, the definition of a valid set of conventions requires broadly-accepted best-practices. In this regard, we empirically analyzed a number of popular vocabularies and ontology development efforts with respect to their use of guidelines and common practices. Based on this analysis, we identified the following main aspects of common practices: documentation, internationalization, naming, structure, reuse, validation and authoring. In this paper, these aspects are presented and discussed in detail. We propose a set of practices for each aspect and evaluate their relevance in a study with vocabulary developers. The overall goal is to pave the way for a new paradigm of vocabulary development similar to Software Development by Convention, which we name Vocabulary Development by Convention
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