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Open AccessArticle

tribAIn—Towards an Explicit Specification of Shared Tribological Understanding

Engineering Design, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Martensstr. 9, 91058 Erlangen, Germany
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Appl. Sci. 2020, 10(13), 4421; https://doi.org/10.3390/app10134421
Received: 30 May 2020 / Revised: 19 June 2020 / Accepted: 24 June 2020 / Published: 27 June 2020
(This article belongs to the Special Issue Knowledge Retrieval and Reuse)
Within the domain of tribology, the science and technology for understanding and controlling friction, lubrication, and wear of relatively moving interacting surfaces, countless experiments are carried out and their results are published worldwide. Due to the variety of test procedures and a lack of consistency in the terminology as well as the practice of publishing results in the natural language, accessing and reusing tribological knowledge is time-consuming and experiments are hardly comparable. However, for the selection of potential tribological pairings according to given requirements and to enable comparative evaluations of the behavior of different tribological systems or testing conditions, a shared understanding is essential. Therefore, we present a novel ontology tribAIn (derived from the ancient Greek word “tribein” (= rubbing) and the acronym “AI” (= artificial intelligence)), designed to provide a formal and explicit specification of knowledge in the domain of tribology to enable semantic annotation and the search of experimental setups and results. For generalization, tribAIn is linked to the intermediate-level ontology EXPO (ontology of scientific experiments), supplemented with subject-specific concepts meeting the needs of the domain of tribology. The formalization of tribAIn is expressed in the W3C standard OWL DL. Demonstrating the ability of tribAIn covering tribological experience from experiments, it is applied to a use case with heterogeneous data sources containing natural language texts and tabular data. View Full-Text
Keywords: ontology; tribology; tribological testing; formalization; knowledge reuse; knowledge representation ontology; tribology; tribological testing; formalization; knowledge reuse; knowledge representation
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MDPI and ACS Style

Kügler, P.; Marian, M.; Schleich, B.; Tremmel, S.; Wartzack, S. tribAIn—Towards an Explicit Specification of Shared Tribological Understanding. Appl. Sci. 2020, 10, 4421. https://doi.org/10.3390/app10134421

AMA Style

Kügler P, Marian M, Schleich B, Tremmel S, Wartzack S. tribAIn—Towards an Explicit Specification of Shared Tribological Understanding. Applied Sciences. 2020; 10(13):4421. https://doi.org/10.3390/app10134421

Chicago/Turabian Style

Kügler, Patricia; Marian, Max; Schleich, Benjamin; Tremmel, Stephan; Wartzack, Sandro. 2020. "tribAIn—Towards an Explicit Specification of Shared Tribological Understanding" Appl. Sci. 10, no. 13: 4421. https://doi.org/10.3390/app10134421

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