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An Ontology Model for Interoperability and Multi-organization Data Exchange

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Artificial Intelligence and Bioinspired Computational Methods (CSOC 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1225))

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Abstract

Progress in the uptake and use of technologies such as Artificial Intelligence and the Internet of Things seems to be stalled by the colossal fragmentation of information and data standards. This complexity is compounded by issues of inter-organisational differences, hindering effective collaboration. There is a growing demand for cross-organizational integrations in regulated but decentralized environments. This paper introduces an ontology architecture where information is sliced into independent semantic layers, each focusing on a specific aspect of the data. By dissolving traditional monolithic data structures into layered, light semantic components, the necessity to maintain contextual metadata is diminished. The model proposes an ontology structure based on decentralized technologies to ensure an open environment and to avoid the flaws of centralized systems.

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Acknowledgement

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870148 - “DIY4U”.

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Authors and Affiliations

  1. Effective Decisions, 16 Iosif Veleceanu, 550057, Sibiu, Romania

    Andrei Tara & Alex Butean

  2. Lucian Blaga University of Sibiu, 10 Victoriei, 550024, Sibiu, Romania

    Alex Butean & Constantin Zamfirescu

  3. Digital Catapult, 101 Euston Road, London, NW1 2RA, UK

    Robert Learney

Authors
  1. Andrei Tara
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  2. Alex Butean
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  3. Constantin Zamfirescu
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  4. Robert Learney
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Corresponding author

Correspondence to Alex Butean .

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Editors and Affiliations

  1. Tomas Bata University, Zlín, Czech Republic

    Radek Silhavy

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Tara, A., Butean, A., Zamfirescu, C., Learney, R. (2020). An Ontology Model for Interoperability and Multi-organization Data Exchange. In: Silhavy, R. (eds) Artificial Intelligence and Bioinspired Computational Methods. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1225. Springer, Cham. https://doi.org/10.1007/978-3-030-51971-1_23

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