Efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases

Marinakis, Achilleas; Segui, Matilde Julian; Pellicer, Andreu Belsa; Palau, Carlos E.; Gizelis, Christos-Antonios; Nikolakopoulos, Anastasios; Misargopoulos, Antonis M.; Nikolopoulos-Gkamatsis, Filippos; Kefalogiannis, Michalis; Varvarigou, Theodora; Nestorakis, Konstantinos; Moulos, Vrettos

doi:10.1007/978-3-031-08341-9_10

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…Performance results in both the Data Interoperability and the Data Processing and Virtualization layers, tested in the port of Valencia (using real Customs datasets) and the metropolitan area of Thessaloniki (using anonymized cellular network Mobility data), prove that both models, and therefore BigDaM as a whole, can be evaluated in additional real-world scenarios. Since this current journal is a continuation of an existing work [10], as mentioned at the beginning of Section 2, it is safe to assume that it has achieved its goal of further expanding and exploring BigDaM's potential as a big data management framework for critical infrastructures.…”

Section: Discussionmentioning

confidence: 99%

“…BigDaM aims to relieve CIs from the time-consuming task of properly and wholly managing the data generated. Its development and implementation is the continuation of a previous work published as a paper in 2022 by the same authoring team [10]. The model proposed was based on the use case of smart ports (and therefore the CI transportation sector, in which ports belong to), studied within the context of DataPorts European Research Project [11].…”

Section: Data Management Proposalmentioning

confidence: 99%

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BigDaM: Efficient Big Data Management and Interoperability Middleware for Seaports as Critical Infrastructures

Nikolakopoulos,

Julian Segui,

Pellicer

et al. 2023

Computers

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Over the last few years, the European Union (EU) has placed significant emphasis on the interoperability of critical infrastructures (CIs). One of the main CI transportation infrastructures are ports. The control systems managing such infrastructures are constantly evolving and handle diverse sets of people, data, and processes. Additionally, interdependencies among different infrastructures can lead to discrepancies in data models that propagate and intensify across interconnected systems. This article introduces “BigDaM”, a Big Data Management framework for critical infrastructures. It is a cutting-edge data model that adheres to the latest technological standards and aims to consolidate APIs and services within highly complex CI infrastructures. Our approach takes a bottom-up perspective, treating each service interconnection as an autonomous entity that must align with the proposed common vocabulary and data model. By injecting strict guidelines into the service/component development’s lifecycle, we explicitly promote interoperability among the services within critical infrastructure ecosystems. This approach facilitates the exchange and reuse of data from a shared repository among developers, small and medium-sized enterprises (SMEs), and large vendors. Business challenges have also been taken into account, in order to link the generated data assets of CIs with the business world. The complete framework has been tested in the main EU ports, part of the transportation sector of CIs. Performance evaluation and the aforementioned testing is also being analyzed, highlighting the capabilities of the proposed approach.

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Section: Discussionmentioning

confidence: 99%

Section: Data Management Proposalmentioning

confidence: 99%

BigDaM: Efficient Big Data Management and Interoperability Middleware for Seaports as Critical Infrastructures

Nikolakopoulos,

Julian Segui,

Pellicer

et al. 2023

Computers

Self Cite

View full text Add to dashboard Cite

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Scalable Data Profiling for Quality Analytics Extraction

Nikolakopoulos,

Chondrogiannis,

Karanastasis

et al. 2024

IFIP Advances in Information and Communication Technology

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Operational efficiency and sustainability in smart ports: a comprehensive review

Alzate,

Isaza,

Toro

et al. 2024

Mar Syst Ocean Technol

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The challenges of optimizing logistics operations in all links of the supply chain have led to the development of new dynamics around the revolution 4.0 and the response of operational efficiency linked to environmental sustainability. Smart ports are born as a strategy to meet customer needs from a technological evolution that generates quality logistical and operational responses. The objective of this review is to identify and to analyze the research perspectives related to smart ports. The implemented methodology considered a scientific mapping to determine the most relevant publications in terms of authors, journals, and countries with the greatest scientific participation in the subject and a network analysis based on the implementation of the tree metaphor of the graph theory. The R-studio software and the Bibliometrix plugin were used to process the information. The review considered 204 documents from the Scopus and Web of Science databases, identifying a growing trend in the number of enhanced publications as of 2019, with China being the country with the largest number of papers. In relation to research trends, the adaptation of ports to industry 4.0, maritime ports and technological security, and green and smart ports are the perspectives on the subject of study. Finally, an agenda for future research is presented.

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Efficient Data Management and Interoperability Middleware in Business-Oriented Smart Port Use Cases

Cited by 3 publications

References 9 publications

BigDaM: Efficient Big Data Management and Interoperability Middleware for Seaports as Critical Infrastructures

BigDaM: Efficient Big Data Management and Interoperability Middleware for Seaports as Critical Infrastructures

Scalable Data Profiling for Quality Analytics Extraction

Operational efficiency and sustainability in smart ports: a comprehensive review

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