Alligator: A Deductive Approach for the Integration of Industry 4.0 Standards

Grangel-González, Irlán; Collarana, Diego; Halilaj, Lavdim; Lohmann, Steffen; Lange, Christoph; Vidal, María-Esther; Auer, Sören

doi:10.1007/978-3-319-49004-5_18

Cited by 10 publications

(4 citation statements)

References 13 publications

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“…The landscape is also described in terms of standards organizations as well as types of standards acting in each of the three dimensions. Recent works for semantically integrating I40 related standards are presented by us in [9] and [10]. The first approach, Alligator, combines the power of Datalog and ontologies to semantically integrate KGs while solving semantic interoperability conflicts between I40 related standards.…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, this article provides a methodological foundation for identifying existing semantic interoperability conflicts between standards and standardization frameworks and include them as a part of the I40KG. Second, the rest of the approaches only target the integration between the information models of the standards, e.g., [12,9,10]. Conversely, the I40KG targets to resolve semantic interoperability conflicts not only between standards but also between standards and standardization frameworks.…”

Section: Related Workmentioning

confidence: 99%

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Analyzing a Knowledge Graph of Industry4.0 Standards

Grangel-Gonzalez,

Vidal

2021

Preprint

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Realizing smart factories according to the Industry 4.0 vision requires intelligent human-to-machine and machine-to-machine communication.To achieve this goal, components such as actuators, sensors, and cyber-physical systems along with their data, need to be described; moreover, interoperability conflicts arisen from various semantic representations of these components demand also solutions. To empowering communication in smart factories, a variety of standards and standardization frameworks have been proposed. These standards enable the description of the main properties of components, systems, and processes, as well as interactions between them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Various standardization frameworks have been proposed all over the world by industrial communities, e.g., RAMI4.0 or IICF. While being expressive to categorize existing standards, standardization frameworks may present divergent classifications of the same standard. Mismatches between standard classifications generate semantic interoperability conflicts that negatively impact the effectiveness of communication in smart factories. In this article, we tackle the problem of standard interoperability across different standardization frameworks, and devise a knowledge-driven approach that allows for the description of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The STO ontology represents properties of standards and standardization frameworks, as well as relationships among them. The I40KG integrates more than 200 standards and four standardization frameworks. To populate the I40KG, the landscape of standards has been analyzed from a semantic perspective and the resulting I40KG represents knowledge expressed in more than 200 industrial related documents including technical reports, research articles, and white papers. Additionally, the I40KG has been linked to existing knowledge graphs and an automated reasoning has been implemented to reveal implicit relations between standards as well as mappings 1

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Analyzing a Knowledge Graph of Industry4.0 Standards

Grangel-Gonzalez,

Vidal

2021

Preprint

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“…The research would be applying the deductive approach for the development strategies. Since the approach is based on pre-existing hypotheses, therefore, effective solutions would be deduced by applying the mentioned strategy [6] . The advantage of applying this research approach instead of the inductive approach is that the conclusions are derived at a very short time and therefore the applicability of the solutions to mitigate pedestrian issues would be eventually evaluated.…”

Section: Research Approachmentioning

confidence: 99%

Evaluating Various Approaches to Improve Road Infrastructure and Controlling Pedestrian Crossings in India

Durga¹,

Srivastava²,

Shanmuganathan³

2020

International Journal of Civil Engineering and Technology (Ijciet)

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The study projects the various aspects of development of pedestrian crossings such that the people of India would be able to facilitate a safety measure during a crossing of congested roads. The study also provides relevant measures that are to be adopted by the government of India to develop the mentioned proposal. Dealing with the various development mechanisms, it could be stated that applying time scheduled signal posts at every crossing would eventually enhance the traffic handling ability of the governing bodies as well as provide an estimation of the controlling of pedestrian publics while crossing the roads. The study also draws conclusions based on the evaluation of the methods and technologies along with the projection of the futuristic benefits of the application.

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“…Ontology-based approaches have also contributed to create a shared understanding of the domain [16], and specifically Kovalenko and Euzenat [15] have equipped data integration with diverse methods for ontology alignment. Furthermore, Lin et al [18] identify interoperability conflicts across domain specific standards (e.g., RAMI4.0 model and the IICF architecture), while works by Grangel-Gonzalez et al [10,11,12] show the relevant role that Descriptive Logic, Datalog, and Probabilistic Soft Logic play in liaising I4.0 standards. Certainly, the extensive literature in data integration provides the foundations for enabling the semantic description and alignment of "similar" things in a smart factory.…”

Section: Introductionmentioning

confidence: 99%

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

Rivas¹,

Grangel-González²,

Collarana³

et al. 2020

Preprint

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Industry 4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of 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.

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Alligator: A Deductive Approach for the Integration of Industry 4.0 Standards

Cited by 10 publications

References 13 publications

Analyzing a Knowledge Graph of Industry4.0 Standards

Analyzing a Knowledge Graph of Industry4.0 Standards

Evaluating Various Approaches to Improve Road Infrastructure and Controlling Pedestrian Crossings in India

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

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