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Konstantinos Kotis (https://orcid.org/0000-0001-7838-9691) owns a B.Sc. in Computation from University of Manchester (UMIST), UK and a Ph.D. in Information Management (Knowledge Representation/Ontology Engineering) from the University of the Aegean, Greece. He has worked as a post-doc researcher and adjunct lecturer at the AI Lab of the University of the Aegean (2005-2010), as an ERCIM “Allain Bensoussan” (Marie Curie) post-doc fellow at VTT Technical Research Centre of Finland (2011-2012), and as a post-doc researcher at the University of Piraeus, Dept. of Digital Systems, AI Lab (2013-2018). He is currently an assistant professor at the University of the Aegean, Dept. of Cultural Informatics and Communication, and a research associate at the University of Piraeus, Dept. of Digital Systems, AI Lab. His research interests include but not limited to: Knowledge/Ontology Engineering, Semantic Web technologies, Semantic Data Management, the Semantic Internet/Web of Things, and Knowledge Graphs-based Chatbots. He has published more than 70 papers (Google Scholar’s h-index 17, citations > 1300) in peer-reviewed international journals and conferences and served as a reviewer and PC member in several journals and conference events. He has also contributed in several national and European projects from different roles/positions (in FP7, H2020, Interreg, and national programs).
In this paper, an ontology related to energy-efficient cultural spaces is presented. Specifically, this research work concerns ongoing efforts towards engineering the Museum Energy-Saving Ontology (MESO) towards meeting the following objectives: a) to represent knowledge related to the trustworthy IoT entities that are deployed in a museum i.e., things (e.g., exhibits, spaces), sensors, actuators, people, data, applications; b) to deal with entities’ heterogeneity via semantic interoperability and integration, especially for ’smart’ museum applications and generated data; c) to represent knowledge related to saving energy e.g., lights, air-conditioning; d) to represent knowledge related to museum visits and visitors towards enhancing visiting experience while preserving comfort; e) to represent knowledge related to environmental conditions towards protecting and preserving museum artwork via continuous monitoring. The human-centered collaborative, agile and iterative methodology is followed, namely HCOME, towards the development of an evolved, ‘live’ and modular ontology, while SWRL rules and SPARQL queries are used for its preliminary evaluation.
Konstantina Zachila; Konstantinos Kotis; Asimina Dimara; Stamatia Ladikou; Christos-Nikolaos Anagnostopoulos. Semantic Modeling of Trustworthy IoT Entities in Energy-Efficient Cultural Spaces. Collaboration in a Hyperconnected World 2021, 364 -376.
AMA StyleKonstantina Zachila, Konstantinos Kotis, Asimina Dimara, Stamatia Ladikou, Christos-Nikolaos Anagnostopoulos. Semantic Modeling of Trustworthy IoT Entities in Energy-Efficient Cultural Spaces. Collaboration in a Hyperconnected World. 2021; ():364-376.
Chicago/Turabian StyleKonstantina Zachila; Konstantinos Kotis; Asimina Dimara; Stamatia Ladikou; Christos-Nikolaos Anagnostopoulos. 2021. "Semantic Modeling of Trustworthy IoT Entities in Energy-Efficient Cultural Spaces." Collaboration in a Hyperconnected World , no. : 364-376.
The Semantic Web emerged as an extension to the traditional Web, adding meaning (semantics) to a distributed Web of structured and linked information. At its core, the concept of ontology provides the means to semantically describe and structure information, and expose it to software and human agents in a machine and human-readable form. For software agents to be realized, it is crucial to develop powerful artificial intelligence and machine-learning techniques, able to extract knowledge from information sources, and represent it in the underlying ontology. This survey aims to provide insight into key aspects of ontology-based knowledge extraction from various sources such as text, databases, and human expertise, realized in the realm of feature selection. First, common classification and feature selection algorithms are presented. Then, selected approaches, which utilize ontologies to represent features and perform feature selection and classification, are described. The selective and representative approaches span diverse application domains, such as document classification, opinion mining, manufacturing, recommendation systems, urban management, information security systems, and demonstrate the feasibility and applicability of such methods. This survey, in addition to the criteria-based presentation of related works, contributes a number of open issues and challenges related to this still active research topic.
Konstantinos Sikelis; George Tsekouras; Konstantinos Kotis. Ontology-Based Feature Selection: A Survey. Future Internet 2021, 13, 158 .
AMA StyleKonstantinos Sikelis, George Tsekouras, Konstantinos Kotis. Ontology-Based Feature Selection: A Survey. Future Internet. 2021; 13 (6):158.
Chicago/Turabian StyleKonstantinos Sikelis; George Tsekouras; Konstantinos Kotis. 2021. "Ontology-Based Feature Selection: A Survey." Future Internet 13, no. 6: 158.
In this paper, a novel method to modify color images for the protanopia and deuteranopia color vision deficiencies is proposed. The method admits certain criteria, such as preserving image naturalness and color contrast enhancement. Four modules are employed in the process. First, fuzzy clustering-based color segmentation extracts key colors (which are the cluster centers) of the input image. Second, the key colors are mapped onto the CIE 1931 chromaticity diagram. Then, using the concept of confusion line (i.e., loci of colors confused by the color-blind), a sophisticated mechanism translates (i.e., removes) key colors lying on the same confusion line to different confusion lines so that they can be discriminated by the color-blind. In the third module, the key colors are further adapted by optimizing a regularized objective function that combines the aforementioned criteria. Fourth, the recolored image is obtained by color transfer that involves the adapted key colors and the associated fuzzy clusters. Three related methods are compared with the proposed one, using two performance indices, and evaluated by several experiments over 195 natural images and six digitized art paintings. The main outcomes of the comparative analysis are as follows. (a) Quantitative evaluation based on nonparametric statistical analysis is conducted by comparing the proposed method to each one of the other three methods for protanopia and deuteranopia, and for each index. In most of the comparisons, the Bonferroni adjusted p-values are <0.015, favoring the superiority of the proposed method. (b) Qualitative evaluation verifies the aesthetic appearance of the recolored images. (c) Subjective evaluation supports the above results.
George Tsekouras; Anastasios Rigos; Stamatis Chatzistamatis; John Tsimikas; Konstantinos Kotis; George Caridakis; Christos-Nikolaos Anagnostopoulos. A Novel Approach to Image Recoloring for Color Vision Deficiency. Sensors 2021, 21, 2740 .
AMA StyleGeorge Tsekouras, Anastasios Rigos, Stamatis Chatzistamatis, John Tsimikas, Konstantinos Kotis, George Caridakis, Christos-Nikolaos Anagnostopoulos. A Novel Approach to Image Recoloring for Color Vision Deficiency. Sensors. 2021; 21 (8):2740.
Chicago/Turabian StyleGeorge Tsekouras; Anastasios Rigos; Stamatis Chatzistamatis; John Tsimikas; Konstantinos Kotis; George Caridakis; Christos-Nikolaos Anagnostopoulos. 2021. "A Novel Approach to Image Recoloring for Color Vision Deficiency." Sensors 21, no. 8: 2740.
Remarkable progress in research has shown the efficiency of Knowledge Graphs (KGs) in extracting valuable external knowledge in various domains. A Knowledge Graph (KG) can illustrate high-order relations that connect two objects with one or multiple related attributes. The emerging Graph Neural Networks (GNN) can extract both object characteristics and relations from KGs. This paper presents how Machine Learning (ML) meets the Semantic Web and how KGs are related to Neural Networks and Deep Learning. The paper also highlights important aspects of this area of research, discussing open issues such as the bias hidden in KGs at different levels of graph representation.
Konstantinos Ilias Kotis; Konstantina Zachila; Evaggelos Paparidis. Machine Learning Meets the Semantic Web. Artificial Intelligence Advances 2021, 3, 1 .
AMA StyleKonstantinos Ilias Kotis, Konstantina Zachila, Evaggelos Paparidis. Machine Learning Meets the Semantic Web. Artificial Intelligence Advances. 2021; 3 (1):1.
Chicago/Turabian StyleKonstantinos Ilias Kotis; Konstantina Zachila; Evaggelos Paparidis. 2021. "Machine Learning Meets the Semantic Web." Artificial Intelligence Advances 3, no. 1: 1.
The work presented in this paper is engaging with and contributes to the implementation and evaluation of Semantic Web applications in the cultural Linked Open Data (LOD) domain. The main goal is the semantic integration, enrichment and interlinking of data that are generated through the documentation process of artworks and cultural heritage objects. This is accomplished by using state-of-the-art technologies and current standards of the Semantic Web (RDF, OWL, SPARQL), as well as widely accepted models and vocabularies relevant to the cultural domain (Dublin Core, SKOS, Europeana Data Model). A set of specialized tools such as KARMA and OpenRefine/RDF-extension is being used and evaluated in order to achieve the semantic integration of museum data from heterogeneous sources. Interlinking is achieved using tools such as Silk and OpenRefine/RDF-extension, discovering links (at the back-end) between disparate datasets and other external data sources such as DBpedia and Wikidata that enrich the source data. Finally, a front-end Web application is developed in order to exploit the semantically integrated and enriched museum data, and further interlink (and enrich) them (at application run-time), with the data sources of DBpedia and Europeana. The paper discusses engineering choices made for the evaluation of the proposed framework/pipeline.
Sotirios Angelis; Konstantinos Kotis. Generating and Exploiting Semantically Enriched, Integrated, Linked and Open Museum Data. Communications in Computer and Information Science 2021, 1355, 367 -379.
AMA StyleSotirios Angelis, Konstantinos Kotis. Generating and Exploiting Semantically Enriched, Integrated, Linked and Open Museum Data. Communications in Computer and Information Science. 2021; 1355 ():367-379.
Chicago/Turabian StyleSotirios Angelis; Konstantinos Kotis. 2021. "Generating and Exploiting Semantically Enriched, Integrated, Linked and Open Museum Data." Communications in Computer and Information Science 1355, no. : 367-379.
The paper presents recent work on the design and development of AI chatbots for museums using Knowledge Graphs (KGs). The utilization of KGs as a key technology for implementing chatbots raises not only issues related to the representation and structuring of exhibits’ knowledge in suitable formalism and models, but also issues related to the translation of natural language dialogues to and from the selected technology for the formal representation and structuring of information and knowledge. Moreover, such a translation must be as transparent as possible to visitors, towards a realistic human-like question-answering process. The paper reviews and evaluates a number of recent approaches for the use of KGs in developing AI chatbots, as well as key tools that provide solutions for natural language translation and the querying of Knowledge Bases and Linked Open Data sources. This evaluation aims to provide answers to issues that are identified within the proposed MuBot approach for designing and implementing AI chatbots for museums. The paper also presents Cretan MuBot, the first experimental KG/Ontology-based AI chatbot of the MuBot Platform, which is under development in the Heracleum Archaeological Museum.
Savvas Varitimiadis; Konstantinos Kotis; Dimitris Spiliotopoulos; Costas Vassilakis; Dionisis Margaris. “Talking” Triples to Museum Chatbots. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 281 -299.
AMA StyleSavvas Varitimiadis, Konstantinos Kotis, Dimitris Spiliotopoulos, Costas Vassilakis, Dionisis Margaris. “Talking” Triples to Museum Chatbots. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():281-299.
Chicago/Turabian StyleSavvas Varitimiadis; Konstantinos Kotis; Dimitris Spiliotopoulos; Costas Vassilakis; Dionisis Margaris. 2020. "“Talking” Triples to Museum Chatbots." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 281-299.
This work addresses the challenges of creating usable and personalized conversational interfaces for broad, yet applicable, domains that require user engagement and learning, such as museum chatbots. Whether the chatbots are standalone or coupled with virtual agents or real-life robots, the functional requirements for interaction that targets specific learning aspects would be expected to be more or less similar. This work reports on experimental semantics-driven conversational interface design for chatbots in museum settings, targeting visitors to converse about exhibits and learn information about their style, the artists, the era, and other aspects related to them. Depending on the semantics (presentation, learning, exploration), chatbot scenarios were designed and evaluated by participants in a formative evaluation. The evaluation show that user requirement perception manifests in expectations on the semantic level, instead of just the technical level. The results between the scenarios are compared to see how the semantics considered for the design transferred to the implementation and to the user perception.
Dimitris Spiliotopoulos; Konstantinos Kotis; Costas Vassilakis; Dionisis Margaris. Semantics-Driven Conversational Interfaces for Museum Chatbots. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 255 -266.
AMA StyleDimitris Spiliotopoulos, Konstantinos Kotis, Costas Vassilakis, Dionisis Margaris. Semantics-Driven Conversational Interfaces for Museum Chatbots. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():255-266.
Chicago/Turabian StyleDimitris Spiliotopoulos; Konstantinos Kotis; Costas Vassilakis; Dionisis Margaris. 2020. "Semantics-Driven Conversational Interfaces for Museum Chatbots." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 255-266.
In this paper, we present a framework that aims to support the active participation and collaboration of knowledge workers and engineers in the co-authoring of place-based, cross-cultural and media-rich memories, experiences, stories and narration. To achieve this, the framework proposes a novel approach for facilitating such a participation and collaboration through the semantic integration of data/information and integrated tools that will be both accessible via an open, user-friendly, mobile and knowledge-based platform, emphasizing a low-effort participative and guided co-authoring approach. The presented collaborative and participative approach is expected to foster social cohesion in heterogeneous communities of interest and practice. For the realization of the framework, we propose the implementation of a proof-of-concept system and its evaluation in the socio-cultural group of immigrants and refugees within the context of creating and sharing knowledge related to the physical and digital artifacts of a modern art museum. Our vision for the proposed framework is to introduce new technology for the collaborative authoring of cultural experiences with low effort using an intelligent assistant. Additionally, we envision a Shared Experiences Ecosystem (SEE) that aims to provide media-rich content and tools that will eventually foster the inclusive access of heterogeneous socio-cultural groups to shared experiences, increasing social cohesion in resilient local environments.
Konstantinos Kotis; Dimitris Spiliotopoulos; Andreas Papasalouros. Intelligent Collaborative Authoring of Place-Based, Cross-Cultural and Media-Rich Experiences. Challenges 2020, 11, 10 .
AMA StyleKonstantinos Kotis, Dimitris Spiliotopoulos, Andreas Papasalouros. Intelligent Collaborative Authoring of Place-Based, Cross-Cultural and Media-Rich Experiences. Challenges. 2020; 11 (1):10.
Chicago/Turabian StyleKonstantinos Kotis; Dimitris Spiliotopoulos; Andreas Papasalouros. 2020. "Intelligent Collaborative Authoring of Place-Based, Cross-Cultural and Media-Rich Experiences." Challenges 11, no. 1: 10.
This paper presents SemMR, a semantic framework for modelling interactions between human and non-human entities and managing reusable and optimized cultural experiences, towards a shared cultural experience ecosystem that might seamlessly accommodate mixed reality experiences. The SemMR framework synthesizes and integrates interaction data into semantically rich reusable structures and facilitates the interaction between different types of entities in a symbiotic way, within a large, virtual, and fully experiential open world, promoting experience sharing at the user level, as well as data/application interoperability and low-effort implementation at the software engineering level. The proposed semantic framework introduces methods for low-effort implementation and the deployment of open and reusable cultural content, applications, and tools, around the concept of cultural experience as a semantic trajectory or simply, experience as a trajectory (eX-trajectory). The methods facilitate the collection and analysis of data regarding the behaviour of users and their interaction with other users and the environment, towards optimizing eX-trajectories via reconfiguration. The SemMR framework supports the synthesis, enhancement, and recommendation of highly complex reconfigurable eX-trajectories, while using semantically integrated disparate and heterogeneous related data. Overall, this work aims to semantically manage interactions and experiences through the eX-trajectory concept, towards delivering enriched cultural experiences.
Costas Vassilakis; Konstantinos Kotis; Dimitris Spiliotopoulos; Dionisis Margaris; Vlasios Kasapakis; Christos-Nikolaos Anagnostopoulos; Georgios Santipantakis; George A. Vouros; Theodore Kotsilieris; Volha Petukhova; Andrei Malchanau; Ioanna Lykourentzou; Kaj Michael Helin; Artem Revenko; Nenad Gligoric; Boris Pokric. A Semantic Mixed Reality Framework for Shared Cultural Experiences Ecosystems. Big Data and Cognitive Computing 2020, 4, 6 .
AMA StyleCostas Vassilakis, Konstantinos Kotis, Dimitris Spiliotopoulos, Dionisis Margaris, Vlasios Kasapakis, Christos-Nikolaos Anagnostopoulos, Georgios Santipantakis, George A. Vouros, Theodore Kotsilieris, Volha Petukhova, Andrei Malchanau, Ioanna Lykourentzou, Kaj Michael Helin, Artem Revenko, Nenad Gligoric, Boris Pokric. A Semantic Mixed Reality Framework for Shared Cultural Experiences Ecosystems. Big Data and Cognitive Computing. 2020; 4 (2):6.
Chicago/Turabian StyleCostas Vassilakis; Konstantinos Kotis; Dimitris Spiliotopoulos; Dionisis Margaris; Vlasios Kasapakis; Christos-Nikolaos Anagnostopoulos; Georgios Santipantakis; George A. Vouros; Theodore Kotsilieris; Volha Petukhova; Andrei Malchanau; Ioanna Lykourentzou; Kaj Michael Helin; Artem Revenko; Nenad Gligoric; Boris Pokric. 2020. "A Semantic Mixed Reality Framework for Shared Cultural Experiences Ecosystems." Big Data and Cognitive Computing 4, no. 2: 6.
The aim of this critical review paper is threefold: (a) to provide an insight on the impact of ontology engineering methodologies (OEMs) to the evolution of living and reused ontologies, (b) to update the ontology engineering (OE) community on the status and trends in OEMs and of their use in practice and (c) to propose a set of recommendations for working ontologists to consider during the life cycle of living, evolved and reused ontologies. The work outlined in this critical review paper has been motivated by the need to address critical issues on keeping ontologies alive and evolving while these are shared in wide communities. It is argued that the engineering of ontologies must follow a well-defined methodology, addressing practical aspects that would allow (sometimes wide) communities of experts and ontologists to reach consensus on developments and keep the evolution of ontologies ‘in track’. In doing so, specific collaborative and iterative tool-supported tasks and phases within a complete and evaluated ontology life cycle are necessary. This way the engineered ontologies can be considered ‘shared, commonly agreed and continuously evolved “live” conceptualizations’ of domains of discourse. Today, in the era of Linked Data and Knowledge Graphs, it is more necessary than ever not to neglect to consider the recommendations that OEMs explicitly and implicitly introduce and their implications to the evolution of living ontologies. This paper reports on the status of OEMs, identifies trends and provides recommendations based on the findings of an analysis that concerns the impact of OEMs to the status of well-known, widely used and representative ontologies.
Konstantinos I. Kotis; George A. Vouros; Dimitris Spiliotopoulos. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review 2020, 35, 1 .
AMA StyleKonstantinos I. Kotis, George A. Vouros, Dimitris Spiliotopoulos. Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations. The Knowledge Engineering Review. 2020; 35 ():1.
Chicago/Turabian StyleKonstantinos I. Kotis; George A. Vouros; Dimitris Spiliotopoulos. 2020. "Ontology engineering methodologies for the evolution of living and reused ontologies: status, trends, findings and recommendations." The Knowledge Engineering Review 35, no. : 1.
Dimitris Spiliotopoulos; Dionisis Margaris; Costas Vassilakis; Volha Petukhova; Konstantinos Kotis. A Mixed-reality Interaction-driven Game-based Learning Framework. Proceedings of the 11th International Conference on Management of Digital EcoSystems 2019, 1 .
AMA StyleDimitris Spiliotopoulos, Dionisis Margaris, Costas Vassilakis, Volha Petukhova, Konstantinos Kotis. A Mixed-reality Interaction-driven Game-based Learning Framework. Proceedings of the 11th International Conference on Management of Digital EcoSystems. 2019; ():1.
Chicago/Turabian StyleDimitris Spiliotopoulos; Dionisis Margaris; Costas Vassilakis; Volha Petukhova; Konstantinos Kotis. 2019. "A Mixed-reality Interaction-driven Game-based Learning Framework." Proceedings of the 11th International Conference on Management of Digital EcoSystems , no. : 1.
ARTIST is a research approach introducing novel methods for real-time multi-entity interaction between human and non-human entities, to create reusable and optimized Mixed Reality (MR) experiences with low-effort, towards a Shared MR Experiences Ecosystem (SMRE2). As a result, ARTIST delivers high quality MR experiences, facilitating the interaction between a variety of entities which interact in a virtual and symbiotic way within a mega, virtual and fully-experiential world. Specifically, ARTIST aims to develop novel methods for low-effort (code-free) implementation and deployment of open and reusable MR content, applications and tools, introducing the novel concept of an Experience as a Trajectory (EaaT). In addition, ARTIST will provide tools for the tracking, monitoring and analysis of user behaviour and their interaction with the environment and with other users, towards optimizing MR experiences by recommending their reconfiguration, dynamically (at run-time) or statically (at development time). Finally, it will provide tools for synthesizing experiences into new mega and still reconfigurable EaaTs, enhancing them at the same time using semantically integrated related data/information available in disparate and heterogeneous resources.
Konstantinos Kotis. ARTIST - a reAl-time low-effoRt mulTi-entity Interaction System for creaTing reusable and optimized MR experiences. Research Ideas and Outcomes 2019, 5, e36464 .
AMA StyleKonstantinos Kotis. ARTIST - a reAl-time low-effoRt mulTi-entity Interaction System for creaTing reusable and optimized MR experiences. Research Ideas and Outcomes. 2019; 5 ():e36464.
Chicago/Turabian StyleKonstantinos Kotis. 2019. "ARTIST - a reAl-time low-effoRt mulTi-entity Interaction System for creaTing reusable and optimized MR experiences." Research Ideas and Outcomes 5, no. : e36464.
ARTIST is a research approach introducing novel methods for real-time multi-entity interaction between human and non-human entities, to create reusable and optimized Mixed Reality (MR) experiences with low-effort, towards a Shared MR Experiences Ecosystem (SMRE2). As a result, ARTIST delivers high quality MR experiences, facilitating the interaction between a variety of entities which interact in a virtual and symbiotic way within a mega, virtual and fully-experiential world. Specifically, ARTIST aims to develop novel methods for low-effort (code-free) implementation and deployment of open and reusable MR content, applications and tools, introducing the novel concept of an Experience as a Trajectory (EaaT). In addition, ARTIST will provide tools for the tracking, monitoring and analysis of user behaviour and their interaction with the environment and with other users, towards optimizing MR experiences by recommending their reconfiguration, dynamically (at run-time) or statically (at development time). Finally, it will provide tools for synthesizing experiences into new mega and still reconfigurable EaaTs, enhancing them at the same time using semantically integrated related data/information available in disparate and heterogeneous resources.
Konstantinos Kotis. A reAl-time low-effoRt mulTi-entity Interaction System for creaTing reusable and optimized MR experiences. Research Ideas and Outcomes 2019, 5, e36128 .
AMA StyleKonstantinos Kotis. A reAl-time low-effoRt mulTi-entity Interaction System for creaTing reusable and optimized MR experiences. Research Ideas and Outcomes. 2019; 5 ():e36128.
Chicago/Turabian StyleKonstantinos Kotis. 2019. "A reAl-time low-effoRt mulTi-entity Interaction System for creaTing reusable and optimized MR experiences." Research Ideas and Outcomes 5, no. : e36128.
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Iraklis Athanasakis; George A. Vouros; Konstantinos Kotis. Semantically enabling IoT trust to ensure and secure deployment of IoT entities. International Journal of Internet of Things and Cyber-Assurance 2018, 1, 1 .
AMA StyleIraklis Athanasakis, George A. Vouros, Konstantinos Kotis. Semantically enabling IoT trust to ensure and secure deployment of IoT entities. International Journal of Internet of Things and Cyber-Assurance. 2018; 1 (1):1.
Chicago/Turabian StyleIraklis Athanasakis; George A. Vouros; Konstantinos Kotis. 2018. "Semantically enabling IoT trust to ensure and secure deployment of IoT entities." International Journal of Internet of Things and Cyber-Assurance 1, no. 1: 1.
Konstantinos Kotis; Iraklis Athanasakis; George A. Vouros. Semantically enabling IoT trust to ensure and secure deployment of IoT entities. International Journal of Internet of Things and Cyber-Assurance 2018, 1, 3 .
AMA StyleKonstantinos Kotis, Iraklis Athanasakis, George A. Vouros. Semantically enabling IoT trust to ensure and secure deployment of IoT entities. International Journal of Internet of Things and Cyber-Assurance. 2018; 1 (1):3.
Chicago/Turabian StyleKonstantinos Kotis; Iraklis Athanasakis; George A. Vouros. 2018. "Semantically enabling IoT trust to ensure and secure deployment of IoT entities." International Journal of Internet of Things and Cyber-Assurance 1, no. 1: 3.
Georgios M. Santipantakis; Konstantinos Kotis; George A. Vouros; Christos Doulkeridis. RDF-Gen. Proceedings of the 8th International Conference on Digital Arts 2018, 28 .
AMA StyleGeorgios M. Santipantakis, Konstantinos Kotis, George A. Vouros, Christos Doulkeridis. RDF-Gen. Proceedings of the 8th International Conference on Digital Arts. 2018; ():28.
Chicago/Turabian StyleGeorgios M. Santipantakis; Konstantinos Kotis; George A. Vouros; Christos Doulkeridis. 2018. "RDF-Gen." Proceedings of the 8th International Conference on Digital Arts , no. : 28.
Georgios Santipantakis; Konstantinos Kotis; George A. Vouros. OBDAIR: Ontology-Based Distributed framework for Accessing, Integrating and Reasoning with data in disparate data sources. Expert Systems with Applications 2017, 90, 464 -483.
AMA StyleGeorgios Santipantakis, Konstantinos Kotis, George A. Vouros. OBDAIR: Ontology-Based Distributed framework for Accessing, Integrating and Reasoning with data in disparate data sources. Expert Systems with Applications. 2017; 90 ():464-483.
Chicago/Turabian StyleGeorgios Santipantakis; Konstantinos Kotis; George A. Vouros. 2017. "OBDAIR: Ontology-Based Distributed framework for Accessing, Integrating and Reasoning with data in disparate data sources." Expert Systems with Applications 90, no. : 464-483.
This paper proposes a distributed framework for accessing, integrating and reasoning with data from heterogeneous, disparate data sources. The proposed solution combines the E -- SHIQ modular ontology representation framework with the Ontop ontology-based data access (OBDA) technology. Distribution of knowledge allows the treatment of data from disparate sources in an autonomous manner, parallelization of operations, while it allows more efficient reasoning with the data.
Georgios M. Santipantakis; Konstantinos Kotis; George A. Vouros. Accessing and reasoning with data from disparate data sources using modular ontologies and OBDA. Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication 2015, 1 .
AMA StyleGeorgios M. Santipantakis, Konstantinos Kotis, George A. Vouros. Accessing and reasoning with data from disparate data sources using modular ontologies and OBDA. Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication. 2015; ():1.
Chicago/Turabian StyleGeorgios M. Santipantakis; Konstantinos Kotis; George A. Vouros. 2015. "Accessing and reasoning with data from disparate data sources using modular ontologies and OBDA." Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication , no. : 1.
Recent environmental disasters at sea have highlighted the need for efficient maritime surveillance and incident management. Currently, maritime navigation technology automatically provides real time data from vessels, which together with historical data, can be processed in an integrated way to detect complex events and support decision making. Ontology-Based Data Access (OBDA) frameworks, can be employed to access data towards this effort. However the heterogeneity of data in disparate sources make data integration a challenging task. In this paper we report on our efforts to implement a scalable system for integrating data from disparate data sources by means of existing OBDA frameworks and distributed E -- SHIQ knowledge bases, towards supporting complex event recognition. We present two versions of the implemented system, and the lessons learned from this effort.
Georgios M. Santipantakis; Konstantinos Kotis; George A. Vouros. Ontology-Based Data Integration for Event Recognition in the Maritime Domain. Proceedings of the 5th International Conference on Mobile Software Engineering and Systems 2015, 1 .
AMA StyleGeorgios M. Santipantakis, Konstantinos Kotis, George A. Vouros. Ontology-Based Data Integration for Event Recognition in the Maritime Domain. Proceedings of the 5th International Conference on Mobile Software Engineering and Systems. 2015; ():1.
Chicago/Turabian StyleGeorgios M. Santipantakis; Konstantinos Kotis; George A. Vouros. 2015. "Ontology-Based Data Integration for Event Recognition in the Maritime Domain." Proceedings of the 5th International Conference on Mobile Software Engineering and Systems , no. : 1.
Recent environmental disasters in the sea, have highlighted the need for efficient maritime surveillance. Currently, maritime navigation technology automatically provides real time data from vessels, that together with other historical data can be processed in an integrated way to detect complex events and support decision making. Ontology-Based Data Access (OBDA) frameworks can be employed to access data towards this effort. Integration of data is critical, but the heterogeneity and the large amount of data make this a difficult task. In this paper we present two systems that we have implemented using different OBDA frameworks, emphasizing on the semantic integration of data from disparate sources to support complex event recognition. We discuss the features of each system separately and the lessons learned from this effort.
Georgios Santipantakis; Konstantinos I. Kotis; George A. Vouros. Ontology-based data sources' integration for maritime event recognition. 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA) 2015, 1 -6.
AMA StyleGeorgios Santipantakis, Konstantinos I. Kotis, George A. Vouros. Ontology-based data sources' integration for maritime event recognition. 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA). 2015; ():1-6.
Chicago/Turabian StyleGeorgios Santipantakis; Konstantinos I. Kotis; George A. Vouros. 2015. "Ontology-based data sources' integration for maritime event recognition." 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA) , no. : 1-6.