Abstract
The interoperability of critical infrastructures, such as ports, has become a primary concern of EU in recent years. Information systems that have the control of these infrastructures are continuously evolving and handle heterogeneous collections of data, processes, and people. Moreover, cross-infrastructure dependencies may give rise to cascading and escalating data model discrepancies across interconnected systems. In this article, we present a data model -following the newest technology standards- that tries to consolidate APIs and services of highly complex infrastructures. Port environments are a characteristic example of them, since massive amount of data and services from different sources are processed and used. We adopt a bottom-up approach, considering every service interconnection as an independent entity, which must be aligned with the proposed common vocabulary and data model. The strict guidelines that are injected into the lifecycle of a service/component development, lead to explicitly enforce interoperability between each one service that lives inside the ecosystem of the port. That is -and should be- a step towards “the cognitive port of the future”, where developers, SMEs and huge vendors can exchange and reuse data from a shared repository. Consequently, ports will play key role in the new information system model, as in-house marketplaces will be developed, for companies to disseminate and exploit their data and services.
Supported by DataPorts EU Project – 871493.
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Acknowledgement
The research leading to these results has received funding from the European Commission under the H2020 Programme’s project DataPorts (grant agreement No. 871493).
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Marinakis, A. et al. (2022). Efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652. Springer, Cham. https://doi.org/10.1007/978-3-031-08341-9_10
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