Semantic Interoperability and Knowledge  Building

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Systems".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 11638

Special Issue Editors


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Guest Editor
INP-ENIT, University of Toulouse, 65016 Tarbes, France
Interests: interoperability; ontology engineering; semantic web; distributed systems; cyber-physical-social systems

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Guest Editor
Institut National des Sciences Appliquées de Lyon, 69100 Villeurbanne, France
Interests: ontology-based engineering; knowledge representation; semantic interoperability; decision support systems; cyber-physical-social systems

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Guest Editor
INP-ENIT, University of Toulouse, 65016 Tarbes, France
Interests: artificial intelligence; computer integrated manufacturing; ontology; multi-agent systems; genetic algorithm

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Guest Editor
ENEA-Centro Ricerche Casaccia, Via Anguillarese 301, 00123 Rome, Italy
Interests: Artificial Intelligence; computational creativity; linked data; ontology; ontology engineering; crisis management; resilience; risk assessment; smart city
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Special Issue Information

Dear Colleagues,

In an increasingly connected world, information systems are becoming more and more complex, and the mass of real-time data that is stored and processed is growing exponentially. This amount of data, mostly heterogeneous from a semantic point of view, must be leveraged to take full advantage of it. Indeed, the diversity of the information systems and the generated data makes the notion of interoperability essential. Interoperability is considered as the key component that empowers information sharing. To tackle the interoperability challenge, ontologies are increasingly used for their semantic explicitness and knowledge discovery in order to enable semantic inference and reasoning for more intelligent systems, as well as to promote semantic interoperability among heterogeneous information systems.

This invited Special Issue intends to provide an opportunity for researchers to introduce their recent achievements related to semantic interoperability and knowledge building. Topics of interest include. but are not limited to, the following:

  • Semantics-driven design of information system;
  • Ontologies and knowledge-graph-based systems;
  • Semantic interoperability of heterogeneous systems;
  • Semantic provenance and knowledge acquisition;
  • Semantic interoperability and systems alignment;
  • Knowledge-based decision making;
  • Knowledge discovery and reasoning;
  • Semantics-driven Cyber-Physical Systems (CPS);
  • Semantic Artificial Intelligence (AI);
  • Semantic reasoning and machine learning processes.

Prof. Dr. Mohamed Hedi Karray
Dr. Linda Elmhadhbi
Dr. Arkopaul Sarkar
Dr. Antonio De Nicola
Guest Editors

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Keywords

  • semantic interoperability
  • ontology
  • knowledge graph
  • semantic ai
  • knowledge formalization
  • knowledge reasoning

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Published Papers (3 papers)

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Research

24 pages, 1251 KiB  
Article
Interoperability-Enhanced Knowledge Management in Law Enforcement: An Integrated Data-Driven Forensic Ontological Approach to Crime Scene Analysis
by Alexandros Z. Spyropoulos, Charalampos Bratsas, Georgios C. Makris, Emmanouel Garoufallou and Vassilis Tsiantos
Information 2023, 14(11), 607; https://doi.org/10.3390/info14110607 - 9 Nov 2023
Cited by 7 | Viewed by 4493
Abstract
Nowadays, more and more sciences are involved in strengthening the work of law enforcement authorities. Scientific documentation is evidence highly respected by the courts in administering justice. As the involvement of science in solving crimes increases, so does human subjectivism, [...] Read more.
Nowadays, more and more sciences are involved in strengthening the work of law enforcement authorities. Scientific documentation is evidence highly respected by the courts in administering justice. As the involvement of science in solving crimes increases, so does human subjectivism, which often leads to wrong conclusions and, consequently, to bad judgments. From the above arises the need to create a single information system that will be fed with scientific evidence such as fingerprints, genetic material, digital data, forensic photographs, information from the forensic report, etc., and also investigative data such as information from witnesses’ statements, the apology of the accused, etc., from various crime scenes that will be able, through formal reasoning procedure, to conclude possible perpetrators. The present study examines a proposal for developing an information system that can be a basis for creating a forensic ontologya semantic representation of the crime scene—through descriptive logic in the owl semantic language. The Interoperability-Enhanced information system to be developed could assist law enforcement authorities in solving crimes. At the same time, it would promote closer cooperation between academia, civil society, and state institutions by fostering a culture of engagement for the common good. Full article
(This article belongs to the Special Issue Semantic Interoperability and Knowledge  Building)
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18 pages, 2828 KiB  
Article
Automatic Construction of Educational Knowledge Graphs: A Word Embedding-Based Approach
by Qurat Ul Ain, Mohamed Amine Chatti, Komlan Gluck Charles Bakar, Shoeb Joarder and Rawaa Alatrash
Information 2023, 14(10), 526; https://doi.org/10.3390/info14100526 - 27 Sep 2023
Cited by 10 | Viewed by 4157
Abstract
Knowledge graphs (KGs) are widely used in the education domain to offer learners a semantic representation of domain concepts from educational content and their relations, termed as educational knowledge graphs (EduKGs). Previous studies on EduKGs have incorporated concept extraction and weighting modules. However, [...] Read more.
Knowledge graphs (KGs) are widely used in the education domain to offer learners a semantic representation of domain concepts from educational content and their relations, termed as educational knowledge graphs (EduKGs). Previous studies on EduKGs have incorporated concept extraction and weighting modules. However, these studies face limitations in terms of accuracy and performance. To address these challenges, this work aims to improve the concept extraction and weighting mechanisms by leveraging state-of-the-art word and sentence embedding techniques. Concretely, we enhance the SIFRank keyphrase extraction method by using SqueezeBERT and we propose a concept-weighting strategy based on SBERT. Furthermore, we conduct extensive experiments on different datasets, demonstrating significant improvements over several state-of-the-art keyphrase extraction and concept-weighting techniques. Full article
(This article belongs to the Special Issue Semantic Interoperability and Knowledge  Building)
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17 pages, 611 KiB  
Article
Ontology-Driven Knowledge Sharing in Alzheimer’s Disease Research
by Sophia Lazarova, Dessislava Petrova-Antonova and Todor Kunchev
Information 2023, 14(3), 188; https://doi.org/10.3390/info14030188 - 16 Mar 2023
Cited by 2 | Viewed by 2027
Abstract
Alzheimer’s disease is a debilitating neurodegenerative condition which is known to be the most common cause of dementia. Despite its rapidly growing prevalence, medicine still lacks a comprehensive definition of the disease. As a result, Alzheimer’s disease remains neither preventable nor curable. In [...] Read more.
Alzheimer’s disease is a debilitating neurodegenerative condition which is known to be the most common cause of dementia. Despite its rapidly growing prevalence, medicine still lacks a comprehensive definition of the disease. As a result, Alzheimer’s disease remains neither preventable nor curable. In recent years, broad interdisciplinary collaborations in Alzheimer’s disease research are becoming more common. Furthermore, such collaborations have already demonstrated their superiority in addressing the complexity of the disease in innovative ways. However, establishing effective communication and optimal knowledge distribution between researchers and specialists with different expertise and background is not a straightforward task. To address this challenge, we propose the Alzheimer’s disease Ontology for Diagnosis and Preclinical Classification (AD-DPC) as a tool for effective knowledge sharing in interdisciplinary/multidisciplinary teams working on Alzheimer’s disease. It covers six major conceptual groups, namely Alzheimer’s disease pathology, Alzheimer’s disease spectrum, Diagnostic process, Symptoms, Assessments, and Relevant clinical findings. All concepts were annotated with definitions or elucidations and in some cases enriched with synonyms and additional resources. The potential of AD-DPC to support non-medical experts is demonstrated through an evaluation of its usability, applicability and correctness. The results show that the participants in the evaluation process who lack prior medical knowledge can successfully answer Alzheimer’s disease-related questions by interacting with AD-DPC. Furthermore, their perceived level of knowledge in the field increased leading to effective communication with medical experts. Full article
(This article belongs to the Special Issue Semantic Interoperability and Knowledge  Building)
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