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Journal articles on the topic 'Ontological Data Model'
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Castro, Alfonso, Victor A. Villagra, Paula Garcia, Diego Rivera, and David Toledo. "An Ontological-Based Model to Data Governance for Big Data." IEEE Access 9 (2021): 109943–59. http://dx.doi.org/10.1109/access.2021.3101938.
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Rivero, Carlos R., Inma Hernández, David Ruiz, and Rafael Cochuelo. "Discovering and Analysing Ontological Models From Big RDF Data." Journal of Database Management 26, no. 2 (2015): 48–61. http://dx.doi.org/10.4018/jdm.2015040104.
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We are witnessing an increasing popularity of the Web of Data, which exposes a large variety of web sources that provide their data using RDF. Ontological models are used as the schema to organize this data. These models are usually shared by several communities and, to devise them, there is usually an agreement amongst those communities. As a result, it is common to have more than one ontological model to understand some RDF data; therefore, there might be a gap between the ontological models and the RDF data, which is not negligible in practice. In this article, the authors present a technique to automatically discover ontological models from raw RDF data. It is based on the intensive usage of a set of SPARQL 1.1 structural queries that are generic and independent from the RDF data. The final result of the authors' technique is an ontological model that is derived from the RDF data, and includes types and properties, subtypes, domains and ranges of properties and subproperties. The authors have conducted experiments with millions of triples that prove that their technique is suitable to deal with Big RDF Data. As far as they know, this is the first technique to discover such ontological models in the context of RDF data and the Web of Data.
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Vaganov, Danila, Egor Shikov, Anton Lysenko, and Polina Andreeva. "Ontological model identification based on data from heterogeneous sources." Procedia Computer Science 229 (2023): 305–14. http://dx.doi.org/10.1016/j.procs.2023.12.032.
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Nasim, Khozouie, Fotouhi-Ghazvini Faranak, and Minaei-Bidgoli Behrouz. "Ontological MobiHealth System." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 1 (2018): 309–19. https://doi.org/10.11591/ijeecs.v10.i1.pp309-319.
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MobiHealth systems are tele-monitoring systems based on BAN (Body Area Network) and mobile health care (m-health) service platform utilizing next generation public wireless networks. Smart phone applications have selfmonitoring and sensing capabilities and are used in health interventions and disease prevention. In this study, a prototype mobile sensing platform was introduced for m-Health and telemedicine applications, which medical sensors on patient body reports biological signals and environmental sensors send environment raw data to base station (smart phone). Then raw data were preprocessed and necessary features (situations) were extracted. In order to context computation and respond with adaptability, we have used ontologybased model.
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Globa, Larysa, Nataliia Gvozdetska, and Rina Novogrudska. "Ontological model for data processing organization in information and communication networks." System research and information technologies, no. 1 (July 11, 2021): 47–60. http://dx.doi.org/10.20535/srit.2308-8893.2021.1.04.
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The functioning of modern information and communication networks is impossible without data processing. With the emergence of new network services, the amount of information that needs to be processed increases, while the requirements to the data processing quality become more and more stringent. Therefore, the problem of designing and maintaining a scalable data processing system with a flexible quality of service management is becoming more and more important for a network operator. Such data processing systems have a complex internal structure with many interrelated parameters, which makes them difficult to analyze, manage, and expand. This study proposes to use an ontological model to store, represent, and manipulate the information in the operator’s data processing system. The ontological model allows to structure and systematize the data of an information processing system, and transparently reflects the relationships between the parameters of the system to simplify its analysis and scaling. The proposed ontology of a data processing system consists of three related subsystems. The paper describes the proposed ontological model and additionally analyzes the sources of information that needs to be processed in the information and communication network.
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Mahmood, Nadeem, S. M. Aqil Burney, and Kamran Ahsan. "Generic Temporal and Fuzzy Ontological Framework (GTFOF) for Developing Temporal-Fuzzy Database Model for Managing Patient's Data." JUCS - Journal of Universal Computer Science 18, no. (2) (2012): 177–93. https://doi.org/10.3217/jucs-018-02-0177.
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A generic temporal and fuzzy ontological framework (GTFOF) is presented, specific to the task of designing temporal and fuzzy database system. The framework includes both time and fuzzy dimension in deigning patient information system in a hospital environment. The proposed framework is essential for developing knowledge management systems (KMS) in healthcare environments. The importance of ontological models in the development of patient information system is well established and it provides the logical and formal mechanism for building KMS. Healthcare information systems may include complex data such as time stamped data and fuzzy data about patients. This paper highlights the importance of identifying the key concepts for building an ontological framework to manage both temporal and fuzzy information content. The proposed generic framework is capable of integrating and mapping the proposed ontological model into an effective database design for implementation.
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García-Castro, Raúl, Oscar Corcho, and Chris Hill. "A Core Ontological Model for Semantic Sensor Web Infrastructures." International Journal on Semantic Web and Information Systems 8, no. 1 (2012): 22–42. http://dx.doi.org/10.4018/jswis.2012010102.
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Semantic Sensor Web infrastructures use ontology-based models to represent the data that they manage; however, up to now, these ontological models do not allow representing all the characteristics of distributed, heterogeneous, and web-accessible sensor data. This paper describes a core ontological model for Semantic Sensor Web infrastructures that covers these characteristics and that has been built with a focus on reusability. This ontological model is composed of different modules that deal, on the one hand, with infrastructure data and, on the other hand, with data from a specific domain, that is, the coastal flood emergency planning domain. The paper also presents a set of guidelines, followed during the ontological model development, to satisfy a common set of requirements related to modelling domain-specific features of interest and properties. In addition, the paper includes the results obtained after an exhaustive evaluation of the developed ontologies along different aspects (i.e., vocabulary, syntax, structure, semantics, representation, and context).
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Vlasenko, Lidiia, Nataliia Lutska, Tetiana Savchenko, and Oleksandr Bohdanov. "ONTOLOGICAL MODELING OF INFORMATION DATA OF DIGITAL CRIMINAL CRIME." Cybersecurity: Education, Science, Technique 1, no. 21 (2023): 211–22. http://dx.doi.org/10.28925/2663-4023.2023.21.211222.
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In the article, an ontological model of information data of a digital criminal offense is formed and researched. Ontological modeling made it possible to conceptualize knowledge and effectively overcome the problems of insufficient structure, ambiguity and inconsistency of data and knowledge in the field of digital forensics. On the basis of the conducted classification, five main classes (Digital Crime, Digital Traces, Types of Crimes, Criminal and Criminal Liability) were identified, which include multiple user and non-user instances, including relevant articles of the Criminal Code of Ukraine and international law. The user creates instances of three classes: Digital Crime, Digital Traces, and Criminal. They contain personal information about digital crime and are the main data of the user part of the ontological model as a knowledge base. The Crime Types and Criminal Liability classes are non-user and can only be modified by model support specialists. The ontology model is implemented in Protege in the OWL language, which is an informal standard for creating and sharing ontologies. Of the selected seven relationships between entities, only three are entered into the ontology by the user, the others are formed automatically based on the developed SWRL rules. Using the SPARQL query language, real-time information search, filtering, and analysis patterns are provided to help discover complex relationships between objects and generate new ontological knowledge. The results of the study highlight the importance of ontology modeling in the field of digital forensics and how SPARQL queries can be used to improve data processing, analysis and understanding of knowledge in this field.
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Khozouie, Nasim, Faranak Fotouhi-Ghazvini, and Behrouz Minaei-Bidgoli. "Ontological MobiHealth System." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 1 (2018): 309. http://dx.doi.org/10.11591/ijeecs.v10.i1.pp309-319.
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<p>MobiHealth systems are tele-monitoring systems based on BAN (Body Area Network) and mobile health care (m-health) service platform utilizing next generation public wireless networks. Smart phone applications have self-monitoring and sensing capabilities and are used in health interventions and disease prevention. In this study, a prototype mobile sensing platform was introduced for m-Health and telemedicine applications, which medical sensors on patient body reports biological signals and environmental sensors send environment raw data to base station (smart phone). Then raw data were preprocessed and necessary features (situations) were extracted. In order to context computation and respond with adaptability, we have used ontology-based model. </p>
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Porshnev, Sergey, Andrey Borodin, Olga Ponomareva, Sergey Mirvoda, and Olga Chernova. "The Development of a Heterogeneous MP Data Model Based on the Ontological Approach." Symmetry 13, no. 5 (2021): 813. http://dx.doi.org/10.3390/sym13050813.
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The article discusses the approaches providing symmetric access of all industrial production services to the data of business processes of the enterprise by building a single warehouse of heterogeneous data of a metallurgical production. The warehouse is a part of an automated statistic quality control system for the products of a metallurgical enterprise. The article describes an ontological storage model of data coming from various sources of information in the production process. The concept of “a unit of production of metallurgical production” is introduced that is the connecting component of the entire production life cycle of a metallurgical production. The authors propose an ontological model of the production process, in terms of information flows which are formed in an enterprise at each stage of production. Based on the constructed ontological model, the structure of recording an array of information in the heterogeneous data warehouse is justified and formed. Heterogeneous data warehouse forms a single information space of the enterprise, which serves as the basis for analytical analysis throughout the production and decision—making process. For example, timely response to the deviation reasons from the given physical and chemical properties of the finished product.
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Suleimenova, L. R., S. K. Kumargazhanova, A. S. Tlebaldinova, Zh T. Konurbayeva, S. S. Smailova, and A. M. Urkumbayeva. "APPLICATION OF ONTOLOGICAL MODELING IN THE PROBLEMS OF KNOWLEDGE MANAGEMENT IN A MODERN UNIVERSITY." Bulletin D. Serikbayev of EKTU, no. 1 (December 2023): 335–42. http://dx.doi.org/10.51885/1561-4212_2023_4_335.
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The article provides a brief description of the stages of building an ontological model of the subject area. The results of building an ontological model of university knowledge, namely scientific knowledge, which allows integrating data on the results of scientific activity from scientometric databases, are presented. The proposed model is built by reengineering the SWRC and BiDO ontological model.
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Igor, Bibichkov, Sokol Vadym, and Shevchenko Oleksandr. "ONTOLOGICAL APPROACH TO DEVELOPMENT OF WEB-CONTENT GENERATION METHOD." Technology audit and production reserves 5, no. 2 (49) (2019): 4–10. https://doi.org/10.15587/2312-8372.2019.183201.
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<em>The object of research is the process of automated creation of web content based on information presented in an ontological form. One of the most problematic places in web development is the process of creating a user interface. This is due to the fact that this process is complex and requires more time and money than other development stages.</em> <em>During the study, there was applied a software development model, which is, based on the development of an ontology, and then a software application for its processing. This approach is called «Ontology-driven development» (or the software development process controlled by the ontology).</em> <em>An intellectual model is obtained for representing the elements of web resources, which is represented in the form of an ontology, as well as the software core of the system for generating web pages, based on information stored in the ontology. This is due to the process, which is need to obtain a set of finite elements of the user interface (HTML, CSS, JS elements) from which web pages are formed.</em> <em>Setting addressing between pages of a web resource has a number of features. In particular, an appropriate approach was proposed for linking the address of the final web page with the controller, which is responsible for generating its content. These functions are similarly to the so-called «router», which is used in classical web-based systems (e. g. JSP for Java). A distinctive feature of this approach is in the set of information from which the web page is formed. This information, as well as its address is stored and loaded from the ontology.</em> <em>Due to the presented approach, the process of designing and developing of the user interface is simplified in comparison with classical ones. This approach is effective for web projects and, in the perspective, for other applications (desktop, mobile, etc.). Also, the proposed method will increase the possibility of reusing already developed elements of the user interface, as well as ensure the creation of a base of ready-made solutions for the developers in the form of corporate memory.</em>
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Kovartsev, A. N., V. S. Smirnov, and S. V. Smirnov. "Intelligent Design of Class Structure Model based on Ontological Data Analysis." Proceedings of the Institute for System Programming of the RAS, no. 3 (2015): 73–86. http://dx.doi.org/10.15514/ispras-2015-27(3)-5.
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Fedorov, Oleg D., and Nadezhda R. Yashchuk. "The ontological model of mentoring young teachers." Yaroslavl Pedagogical Bulletin 5, no. 122 (2021): 38–49. http://dx.doi.org/10.20323/1813-145x-2021-5-122-38-49.
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The problem of mentoring is relevant not only for the pedagogical community, but also for the entire system of training personnel for many sectors of the economy. It is likely that many of the processes that occur in the mentor – mentee relationship are repeated regardless of the field of activity. The authors of this article have made an attempt to explore the real practice of mentoring in general education organizations to identify and define these key processes, considering the situation of formation in the profession of a young teacher. The model formed as a result of the generalization of the collected data includes key processes, objects and their relationships, and allows you to model mentoring programs taking into account a comprehensive understanding of actors and their interests. The study and its results can be useful for designing comprehensive mentoring programs in schools, municipalities, and regions, as well as for optimizing the work of individual teacher mentors. Questionnaire surveys (332 respondents) and in – depth semi-structured interviews (34 respondents) were conducted, which allowed us to establish several phases that a young teacher goes through from employment to consolidation in the profession-adaptation, integration, individualization. Within the framework of the study, the ratio of various types of difficulties and leading types of activities in the process of professional development is determined. The collected data and materials allowed us to build an ontological model of mentoring a young teacher, which includes the most important social and pedagogical contexts of his development, as well as the main objects and relationships that arise during the first years of work. The ontological model of mentoring of a young teacher, used as a tool for analyzing mentoring practices in school, allowed us to identify the deficits of mentoring activities, which lie mainly in the plane of personal improvement and spiritual growth of a young teacher, generated not only by the pace and speed of the processes occurring in the first years of his career, but also by the lack of andragogical competencies of the mentor. The obtained results and the constructed model allowed us to conclude that the regulation of mentoring activities can occur through the transformation of the regional context and state policy in the field of teacher education, an important role in the process of professional formation is played by a variety of formal organizations and associations, a set of public expectations from specific schools and teachers, however, the interaction between the mentor and the mentee around the subject content of education and teaching methods is decisive.
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Yarushkina, N., A. Romanov, A. Filippov, A. Dolganovskaya, and M. Grigoricheva. "Using ontology merging for the integration of information systems and the production capacity planning system." Information Technology and Nanotechnology, no. 2416 (2019): 401–8. http://dx.doi.org/10.18287/1613-0073-2019-2416-401-408.
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This article describes the method of integrating information systems of an aircraft factory with the production capacity planning system based on the ontology merging. The ontological representation is formed for each relational database (RDB) of integrated information systems. The ontological representation is formed in the process of analyzing the structure of the relational database of the information system (IS). Based on the ontological representations merging the integrating data model is formed. The integrating data model is a mechanism for semantic integration of data sources.
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Fomin, Igor N. "Application of an ontological approach to the problems of energy consumption data exchange." Journal Of Applied Informatics 19, no. 4 (2024): 4–17. http://dx.doi.org/10.37791/2687-0649-2024-19-4-4-17.
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The article describes the technical concept of organizing data exchange between a specialized settlement center that carries out billing of consumed heat energy, and an energy sales company that supplies heat energy to industrial enterprises, government agencies and the population. The article describes the features of the technical problem of data exchange, which determine the parameters of mathematical models for calculating the volumes and costs of consumed energy resources, and then reviews approaches to solving this class of problems. To solve the technical problem, the features of the data preparation stage for the initial data exchange were formalized and schemes for organizing a regular data flow based on an ontological data model were proposed. The originality of the proposed approach was expressed in the definition of classes and their properties for concepts reflecting sets of information about the parameters of energy supply facilities, parameters for calculating volumes, prices and costs of energy resources, which made it possible, using an ontology editor, to form graphically formalized semantics, which became the basis for the formation of rules data processing for information exchange. The concepts of the ontological model were related to each other by sets of classified predicates, the use of which was illustrated by examples of descriptive logic queries. The implemented data exchange process based on the ontological model is illustrated with a data flow diagram. The ontological approach to solving the described problem made it possible to organize an end-to-end connection between the formalized reflection of the calculation models required for billing and the exchange data model, which made it possible to balance and comply with management and information technology requirements for this procedure.
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Razdyakonov, D. S., and D. I. Muromcev. "Application of an Agent-Based Model to Develop Ontological Data Visual Management Tool." Scientific Visualization 15, no. 5 (2023): 73–88. http://dx.doi.org/10.26583/sv.15.5.07.
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The paper presents an agent-based model of interactive visualization and proposes a method for its application in the development of the ontological data visual management tool. The process of user interaction with the visualization is represented as a state graph, where each node is a separate visualization. The initial state is known, and the final state is formed in the process of user interaction with the ontological data visual management tool. Each intermediate visualization from the state graph is transferred into the multidimensional Euclidean data space formed on the basis of the visualized ontology, which allows to calculate weighting coefficients on the state graph edges and to search the graph using known algorithms. Application of the model allows for a reduction in the labor intensity of executing user scripts due to the reduction of step-by-step visualization creation to the task of searching in the state space.
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Globa, Larysa, and Anton Kartashov. "OPTIMIZING DISTRIBUTED DATA STORAGE IN MULTI-CLOUD ENVIRONMENTS: ALGORITHMIC APPROACH." Information and Telecommunication Sciences, no. 2 (December 23, 2024): 4–12. https://doi.org/10.20535/2411-2976.22024.4-12.
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Background. Multi-cloud environments present complex challenges in optimal resource allocation and provider selection. Previous research has established a comprehensive ontological model and evaluation criteria for distributed data storage, however efficient provider selection remains a significant challenge due to the dynamic nature of cloud services and the multitude of interdependent factors affecting performance and cost-effectiveness. Objective. The purpose of the paper is to develop and validate a sophisticated optimization function for cloud provider selection in multi-cloud environments, incorporating both Reinforcement Learning (RL) and Multi-Objective Evolutionary Algorithms (MOEAs) to address the complexity of provider selection while considering multiple competing objectives and constraints. Methods. The research employs an ontological approach to formalize domain concepts, relationships, and properties in multi-cloud environments. Additionally, an optimization function is developed incorporating multiple weighted criteria derived from the established ontological model. The study focuses on the implementation of the RL algorithm to adapt to dynamic changes in cloud provider characteristics and integration of MOEAs to handle multiple competing objectives as well as providing a comparative analysis with traditional selection methods and alternative optimization approaches for multi-cloud storage settings. Results. The proposed ontological model successfully formalizes the domain's concepts, relationships, and properties in multi-cloud environments. The optimization function demonstrates effectiveness in selecting the most suitable public cloud provider based on the proposed features, enhancing data management practices automation and decision-making processes. Conclusions. The developed optimization function and suggested methodology significantly advance the state-of-the-art in distributed multi-cloud data storage. The integration of RL and MOEAs provides a robust framework for addressing the complexity of multi-cloud environments while offering superior performance compared to existing approaches. The methodology successfully balances multiple objectives while adapting to dynamic changes in cloud provider characteristics.
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Dyvak, Mykola, Andriy Melnyk, Artur Rot, Marcin Hernes, and Andriy Pukas. "Ontology of Mathematical Modeling Based on Interval Data." Complexity 2022 (July 19, 2022): 1–19. http://dx.doi.org/10.1155/2022/8062969.
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An ontological approach as a tool for managing the processes of constructing mathematical models based on interval data and further use of these models for solving applied problems is proposed in this article. Mathematical models built using interval data analysis are quite effective in many applications, as they have “guaranteed” predictive properties, which are determined by the accuracy of experimental data. However, the application of mathematical modeling methods is complicated by the lack of software tools for the implementation of procedures for constructing this type of mathematical models, creating an ontological model that operates by the categories of the subject area of mathematical modeling, regardless of the modeling object proposed in this article. This approach has made it possible to generate tools for mathematical modeling of various objects based on the interval data analysis for any software development environment selected by the user. The technology of creating the software on the basis of the developed ontological superstructure for mathematical modeling using the interval data for different objects, as well as various forms of user interface implementation, is presented in this article. A number of schemes, which illustrate the technology of using the ontological approach of mathematical modeling based on interval data, are presented, and the features of its interpretation when solving environmental monitoring problems are described.
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Mamedova, Natalia. "Towards Digitalization of Business Processes: Building a Business Domain Ontology for Project Management." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 17 (September 16, 2022): 379–91. http://dx.doi.org/10.37394/23203.2022.17.42.
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The article presents an ontological model of the subject area. It was designed to improve the efficiency of the software development process and reduce development costs. This ontological model is recommended to be used in the formation of the company’s software architecture. The article contains data on the process and results of developing an ontological model of the selected subject area. The theoretical justification of the application of the ontological approach is presented. The business domain of relations between IT directors during the implementation of the digitalization project of the company’s business process is defined as a subject area. The sources of the metadata of the ontological model were the standards for the organization of collective activity – ISO 21500:2012 and PRINCE2. The ontological model was developed in accordance with the basic characteristics of the modeling process and the mathematical apparatus that established the relationship of concepts and the order of inheritance of attributes. The project topics became layers of the ontological model, the responsibility for the consistent implementation of which is borne by IT directors, as well as the functional tasks and functional roles of IT management distributed among them. The order and direction of interaction of the IT management in the project is shown by the relationships between the entities of the model. The chosen form of visualization - semantic network - allows you to demonstrate the result of the development of an ontological model and can be considered as a ready-made product to support the semantics of end-user requests in the company.
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Silagin, Silagin, and V. O. Denysiuk. "ONTOLOGICAL MODELLING OF THE KNOWLEDGE BASE OF THE TRAVEL ORGANIZATION." Ukrainian Journal of Information Technology 4, no. 1 (2022): 44–52. http://dx.doi.org/10.23939/ujit2022.01.044.
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In modern conditions of society development, increasing degree and pace of integration of information technology achievements in the field of human life, traditional approaches to building information systems become too cumbersome or cease to be effective. One of the ways to solve this problem is to develop knowledge-based systems. The work is devoted to ontological modeling of a new subject area "travel organization". The ontology is considered in the context of knowledge exchange. The created travel ontology is quite modern and relevant today. The developed ontological model of the knowledge base in this area can be implemented on thematic web resources and greatly facilitate the semantic search for information within the subject area in comparison with existing ones. A terminological dictionary from this subject area is defined using the concept of terminological system. An analysis of the possibilities of the Protege ontology development environment for modeling a specific subject area of "travel". The basic principle of ontology modeling in the form of a semantic network is chosen. The proposed network has the opportunity to expand and deepen knowledge about the subject area of "travel". The use of the Protege environment to implement the ontological model of the knowledge base allowed to use the advantages and features of the created model of "travel organization", such as: functionality, transitivity, reflectivity, structuring, completeness, reliability and consistency of information. The criterion for assessing the correctness of the ontological model of the knowledge base is chosen. Testing of the developed ontological knowledge base was carried out and a rather high level of its correctness in the process of information retrieval was confirmed. The average metric on the SUM metric for all users is equal to 82.95%, which is an acceptable indicator of the ontological knowledge base. When using the classical relational model of database organization to implement the "travel" database, the average SUM metric for 10 users is 73.68%. An example of the developed ontology in Protege is considered, a graphic representation of the basic graph of the ontological mode "travel" is given, the model includes 10 classes and subclasses, for each class and subclass 2 properties-relations and from 2 to 10 properties-data are defined, an example is given classes of the ontological model of "travel", an example of "properties-relations" of the ontological model of "travel" is given, an example of "properties-data" of the ontological model of "travel" is given. Possible directions of further development of the ontological model "travel organization" are formulated.
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Espinoza-Arias, Paola, María Poveda-Villalón, Raúl García-Castro, and Oscar Corcho. "Ontological Representation of Smart City Data: From Devices to Cities." Applied Sciences 9, no. 1 (2018): 32. http://dx.doi.org/10.3390/app9010032.
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Existing smart city ontologies allow representing different types of city-related data from cities. They have been developed according to different ontological commitments and hence do not share a minimum core model that would facilitate interoperability among smart city information systems. In this work, a survey has been carried out in order to study available smart city ontologies and to identify the domains they are representing. Taking into account the findings of the survey and a set of ontological requirements for smart city data, a list of ontology design patterns is proposed. These patterns aim to be easily replicated and provide a minimum set of core concepts in order to guide the development of smart city ontologies.
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Foudeh, Pouya, and Naomie Salim. "ONTOLOGICAL, FULLY PROBABILISTIC KNOWLEDGE MODEL FOR HUMAN ACTIVITY RECOGNITION." Jurnal Teknologi 85, no. 2 (2023): 183–99. http://dx.doi.org/10.11113/jurnalteknologi.v85.18942.
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Efficiency and scalability are obstacles that have not yet received a viable response from the human activity recognition research community. This paper proposes an activity recognition method. The knowledge model is in the form of ontology, the state-of-the-art in knowledge representation and reasoning. The ontology starts with probabilistic information about subjects’ low-level activities and location and then is populated with the assertion axioms learned from data or defined by the user. Unlike methods that choose only the most probable candidate from sensor readings, the proposed method keeps multiple candidates with the known degree of confidence for each one and involves them in decision making. Using this method, the system is more flexible to deal with unreliable data, readings from sensors, and the final recognition rate is improved. Besides, to resolve the scalability problem, a system is designed and implemented to do reasoning and storing in a relational database management system. Numerical evaluations and conceptual benchmarking prove the proposed system feasibility.
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Kartashov, Anton, and Larysa Globa. "TOWARDS SEAMLEES MULTI-CLOUD INTEGRATION: STRATEGIC APPROACH." Системи управління, навігації та зв’язку. Збірник наукових праць 4, no. 78 (2024): 79–83. https://doi.org/10.26906/sunz.2024.4.079.
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Background. Cloud computing has transformed the IT landscape, offering scalable and cost-efficient solutions for data storage and access. The emergence of multi-cloud environments as a strategic approach to leverage various cloud service providers' strengths has introduced new challenges and opportunities. Existing multi-cloud frameworks and approaches lack versatility in addressing key concepts such as data security, scalability, cost optimization, and resource management. Objective. Designing and developing an ontological model and optimization function to enhance data management practices and decision-making in multi-cloud environments. Methods. The research employs an ontological approach to formalize domain concepts, relationships, and properties in multi-cloud environments. Additionally, an optimization function is proposed for selecting the best public cloud provider based on specific features. The study focuses on designing distributed storage techniques, optimizing data access latency, and developing security frameworks for multicloud settings. Results. The proposed ontological model successfully formalizes the domain's concepts, relationships, and properties in multi-cloud environments. The optimization function demonstrates effectiveness in selecting the most suitable public cloud provider based on the proposed features, enhancing data management practices automation and decision-making processes. Conclusions. This work addresses the critical challenge of improving data management and decision-making in multi-cloud environments through the development of an ontological model and optimization function. The research contributes to enhancing data security, scalability, cost optimization, and resource management in multi-cloud settings. Future work should focus on further refining the ontological model and optimization function, as well as exploring their application in various industry sectors.
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Nieto Sánchez, Zulmary Carolina, and Antonio José Bravo Valero. "Exploring computational methods in the statistical analysis of imprecise medical data: between epistemology and ontology." Salud, Ciencia y Tecnología 4 (July 31, 2024): 1341. http://dx.doi.org/10.56294/saludcyt20241341.
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The accuracy of the results is essential to evaluate the effectiveness of statistical methods in the analysis of medical data with uncertainty. Indicators such as margin of error, percent agreement and coefficient of determination quantified accuracy under epistemic and ontological uncertainty. The stability of the methods was assessed by variation in trend analysis, sensitivity to small variations and model robustness. Data reliability focused on the selection of methods that effectively handle epistemic uncertainty, recording assumptions, sensitivity analysis and internal consistency. Ontological imprecision was quantified using the fuzzy membership degree and the overlap coefficient. The exploration of computational methods underlined the importance of accuracy and the handling of epistemic and ontological uncertainty, ensuring reliable results. The geometric mean filter, with a score of 0,7790, stood out as the best for its accuracy and ability to effectively handle uncertainty
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MELNYK, Andriy. "SOFTWARE ARCHITECTURE FOR MATHEMATICAL MODELING BASED ON INTERVAL AND ONTOLOGICAL APPROACH." Herald of Khmelnytskyi National University. Technical sciences 311, no. 4 (2022): 141–49. http://dx.doi.org/10.31891/2307-5732-2022-311-4-141-149.
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The paper substantiates the use of the ontological approach as an effective tool for managing the processes of building mathematical models based on interval data and using these models for applied problems. The use of the ontological model made it possible to formalize the process of obtaining, storing and using knowledge obtained in the process of mathematical modeling. The article also presents the features of building a software architecture for mathematical modeling based on interval analysis and an ontological approach. The technology for creating software based on the developed ontological add-on for mathematical modeling using interval data for various objects, as well as various forms of user interface implementation, is described. A number of diagrams illustrating the peculiarities of using the ontological approach based on interval data are presented and the peculiarities of its interpretation in applied fields, in particular, in the tasks of environmental monitoring, are described.
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Aresti, Andreas, Penelope Markellou, Ioanna Mousourouli, Spiros Sirmakessis, and Athanasios Tsakalidis. "A Movie E-shop Recommendation Model Based on Web Usage and Ontological Data." Journal of Electronic Commerce in Organizations 5, no. 3 (2007): 17–34. http://dx.doi.org/10.4018/jeco.2007070102.
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Zawadzka, Teresa, Wojciech Waloszek, Aleksandra Karpus, Sara Zapalowska, and Michal R. Wrobel. "Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis." IEEE Access 9 (2021): 166674–94. http://dx.doi.org/10.1109/access.2021.3132728.
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Bendik, Nadezhda V., and Marina N. Polkovskaya. "Ontological data model for assessing the repeatability of failures of electrical network elements." Информационные и математические технологии в науке и управлении, no. 4 (2022): 170–80. http://dx.doi.org/10.38028/esi.2022.28.4.013.
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Zayakin, V. S., L. N. Lyadova, and E. A. Rabchevskiy. "An Ontological Approach to Information Integration in Data Intensive Domains." Informacionnye Tehnologii 28, no. 10 (2022): 529–38. http://dx.doi.org/10.17587/it.28.529-538.
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The development and support of knowledge-based systems for experts in the field of social network analysis (SNA) is complicated because of the problems of viability maintenance that inevitably emerge in data intensive domains. Largely this is the case due to the properties of semi-structured objects and processes that are analyzed by data specialists using data mining techniques and others automated analytical tools. Firstly, new sources (e. g. online social networks, published databases) constantly become available for gathering, analyzing, and interpreting data. Thus, new sources should be modelled and embedded in existing data structures maintaining logical consistency. Secondly, new techniques and underlying algorithms are also constantly being developed. Therefore, analysis results should be integrated with source data, and metamodels that describe the integration should be adaptable and extensible. Thirdly, the dynamism of semi-structured objects entails constant changes in knowledge models produced by domain experts and knowledge engineers. Considering that the same data could be used by different domain experts it is crucial not only to support traceability of changes in models but also to ensure independence of expert interpretation of these models. The analysis of existing approaches to information integration shows lack of solutions implementing traceability of changes. This paper introduces a novel approach to information integration based on ontological and production knowledge models to fill this gap. A conceptual description of the approach and an underlying set-theoretical model are given. The main difference of the given approach from the existing ones is the uniformity to the integration of different kinds of ontologies as well as different versions of ontologies using rule-based model of ontological mappings, which is demonstrated by the example of solving the special case of the problem of identifying key users (so-called bridges) in social networks.
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Mukanova, Assel, Marek Milosz, Assem Dauletkaliyeva, et al. "LLM-Powered Natural Language Text Processing for Ontology Enrichment." Applied Sciences 14, no. 13 (2024): 5860. http://dx.doi.org/10.3390/app14135860.
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This paper describes a method and technology for processing natural language texts and extracting data from the text that correspond to the semantics of an ontological model. The proposed method is distinguished by the use of a Large Language Model algorithm for text analysis. The extracted data are stored in an intermediate format, after which individuals and properties that reflect the specified semantics are programmatically created in the ontology. The proposed technology is implemented using the example of an ontological model that describes the geographical configuration and administrative–territorial division of Kazakhstan. The proposed method and technology can be applied in any subject areas for which ontological models have been developed. The results of the study can significantly improve the efficiency of using knowledge bases based on semantic networks by converting texts in natural languages into semantically linked data.
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Okemwa, Joshua, Patrick Oduor Owoche, and Samuel Mungai Mbuguah. "A Fuzzy Ontological Model for Semantic Interoperability in Distributed Healthcare Information Systems." International Journal of Research and Innovation in Applied Science IX, no. XII (2025): 478–83. https://doi.org/10.51584/ijrias.2024.912043.
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The exchange of patient or care data across heterogeneous health systems is crucial in the modern healthcare ecosystem yet remains daunting. Integration and interoperability in siloed health applications require robust health information exchange (HIE) and a pragmatic ontological model to be successful. This paper details a prototype development endeavor and systematic review of literature that has pioneered the development of a robust, practical, and tested fuzzy ontological model to enhance semantic interoperability in siloed, distributed health systems. Leveraging the tenets, standards, LOINC codes, and developed model from this study will enable robust and flexible data mapping and sharing health data in an environment marred with ambiguities and uncertainties but requiring the sophistry of interoperability.
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Sanfilippo, Emilio M., Walter Terkaj, and Stefano Borgo. "Ontological modeling of manufacturing resources." Applied Ontology 16, no. 1 (2021): 87–109. http://dx.doi.org/10.3233/ao-210242.
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Standards and ontologies for manufacturing understand resources differently. Because of this heterogeneity, misunderstandings arise concerning the basic features that characterize them. The purpose of the paper is to investigate how to ontologically model resources with the goal of facilitating the development of knowledge representation models for manufacturing. By reviewing the literature, we discuss and compare three approaches for the representation of resources depending on whether they are conceived in connection to either processes, plans or goals. By addressing the advantages and shortcomings of each view, we present a unifying perspective to enable the modeling of resources in an integrated manner. In this way, the intended meanings of the used notions are harmonized and, as a result, one can facilitate multiple experts to interact e.g., via data sharing and/or data integration procedures. Differently, by keeping three separated views, there is no guarantee that data coming from different parties will share common meanings even if the same terms are used. By the end of the paper, we present a case study to show the application of our approach and to compare it with an existing ontology for manufacturing.
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Shapovalov, V. B. "USING THE ONTOLOGICAL MODEL OF THE STEM–CENTER IN THE EDUCATIONAL PROCESS." Scientific Notes of Junior Academy of Sciences of Ukraine, no. 1(20) (2021): 102–16. http://dx.doi.org/10.51707/2618-0529-2021-20-11.
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The article is devoted to the practical aspects of using the ontological model of the STEM Center, which is built on the basis of cognitive information technology “Polyhedron”, in educational and research processes. Tools created using Microsoft and Google Spreadsheets are described. The application of the system of virtual museum Laboratories, a database of microorganisms, an ontological STEM classifier, a virtual laboratory of scientific publications, ontological virtual laboratories of expeditions, and a cognitive system for selecting research papers is analyzed. All tools of the CIT “Polyhedron” can be represented as a taxonomy, object-oriented, or prism. Approaches to data processing using ranking and auditing, which are elements of the CIT “Polyhedron”, have been developed. This approach is used in the selection of data by teachers and students, as well as in the processing of ontological knowledge bases, which is shown on the example of the microbial selection system. The database of a centralized information web-oriented educational environment consists of various types of educational programs. The ontologized program differs from the classical approaches to the interpretation of educational programs by a higher level of structured material and interactivity. Students and teachers can interact with structured curricula. Internal and external search tools are used to search for contexts based on the program’s terminology field. The ontological system of virtual museum laboratories provides a high level of structuring of information about objects and their virtualization. This allows you to use Museum ontologies during sightseeing classes. The database of microorganisms in the CIT “Polyhedron” system provided systematization of research knowledge in the educational process. CIT “Polyhedron” made it possible to identify the characteristics of research papers and systematize their processing in accordance with the user’s request.
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Greenberg, Jane, Angela Murillo, and John A. Kunze. "Ontological Empowerment: Sustainability via Ownership." Advances in Classification Research Online 23, no. 1 (2013): 47. http://dx.doi.org/10.7152/acro.v23i1.14258.
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<p>Positive impacts associated with urban housing/home ownership programs motivate us to study this topic in relation to ontologies. This paper reviews ontological dependence and presents early work underway in the DataONE Preservation and Metadata Working Group (PAMWG) to collectively leverage existing metadata schemes and ontologies. The paper introduces a high-level set of functional requirements and the stackoverflow model that may be used detect highly rated metadata or ontological properties to from a loose cannon for describing scientific data. The long term goal is to establish community identity and rhythm supporting a sustainable ontology/metadata driven workflow.</p>
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Zelinska, Dariia, Vladyslav Girdvainis, and Olexiy Silagin. "IMPLEMENTATION OF THE APPROACH TO ONTOLOGICAL MODELING OF THE MUSICAL SUPERGENRE “METAL”." Information and Telecommunication Sciences, no. 2 (December 21, 2021): 58–63. http://dx.doi.org/10.20535/2411-2976.22021.58-63.
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Background. The relevance of the article is due to the development of modern ontological methods of structuring information and the need to systematize data in many new specific subject areas. Such subject areas include the musical art of the "metal" variety, which is quite common today, but insufficiently studied within the terminology. The subject of the article are ontological models and tools for creating ontological knowledge bases.
 Objective. The purpose of the paper is to increase the correctness of the semantic search in the knowledge base of the musical supergenre "metal". The scientific problem is the need to improve the terminology in this subject area and build an ontological knowledge model that increases the accuracy of information retrieval for the target audience, compared to the existing relational model implemented on one of the known web resources. 
 Methods. Classification method, generalization method, software optimization methods, analytical method. The way to solve the problem: selection based on the comparative characteristics of the best web resource of the subject area and identifying the shortcomings of its model of knowledge representation, designing an ontological knowledge model and testing its effectiveness. 
 Results. The average SUM for all users is 83.85%, which is a good indicator for ontological knowledge bases. At the same time, a similar method of checking the database of the supergenre "metal" on the basis of the site "Encyclopedia Metallum", which used the classical relational model of database organization, showed much lower results. Thus, the average SUM for 10 users was 75.32%, respectively. 
 Conclusions. The scientific novelty of the obtained results is as follows: For the first time an ontological model (ontology) of the subject area was created: musical supergenre "metal", which showed much higher efficiency of semantic search than the best relational model of this subject area, implemented as a web resource. The developed structure can be used to create ontologies of related musical supergenres with similar terminology. Future research also plans to integrate this ontological knowledge model with applied web-based and desktop applications.
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Shynkarenko, Viktor, Larysa Zhuchyi, and Oleksandr Ivanov. "Ontology-Based Semantic Checking of Data in Railway Infrastructure Information Systems." Foundations of Computing and Decision Sciences 47, no. 3 (2022): 291–319. http://dx.doi.org/10.2478/fcds-2022-0016.
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Abstract Semantic checking of railway infrastructure information support data is one of the ways to improve the consistency of information system data and, as a result, increase the safety of train traffic. Existing ontological developments have demonstrated the applicability of description logic for modelling railway transport, but have not paid enough attention to the data resources structure and the railway regulatory support. In this work, the formalization of the tabular presentation of data and the rules of railway transport regulations is carried out using the example of a connection track passport and temporary speed restrictions using ontological means, data wrangling and extraction tools. Ontologies of the various formats data resources and railway station infrastructure, tools for converting and extracting data have been developed. The semantic checking of the compliance of railway information system data with regulatory documents in terms of the connection track passport is carried out on the basis of a multi-level concretization model and integration of ontologies. The mechanisms for implementing the constituent ontologies and their integration are demonstrated by an example. Further research includes ontological checking of natural language normative documents of railway transport.
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Villazón-Terrazas, Boris Carmen, Mari Suárez-Figueroa, and Asunción Gómez-Pérez. "A Pattern-Based Method for Re-Engineering Non-Ontological Resources into Ontologies." International Journal on Semantic Web and Information Systems 6, no. 4 (2010): 27–63. http://dx.doi.org/10.4018/jswis.2010100102.
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To speed up the ontology development process, ontology developers are reusing all available ontological and non-ontological resources, such as classification schemes, thesauri, lexicons, and so forth, that have already reached some consensus. Non-ontological resources are highly heterogeneous in their data model and storage system (or implementation). The reuse of these non-ontological resources involves their re-engineering into ontologies. This paper presents a method for re-engineering non-ontological resources into ontologies. The method is based on so-called re-engineering patterns, which define a procedure that transforms the non-ontological resource components into ontology representational primitives using WordNet for making explicit the relations among the non-ontological resource terms. The paper also provides the description of NOR2O, a software library that implements the transformations suggested by the patterns. Finally, it depicts an evaluation of the method, patterns, and software library proposed.
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CHANG, SHI-KUO, FRANCESCO COLACE, LEI ZHAO, and YAO SUN. "PROCESSING CONTINUOUS QUERIES ON SENSOR-BASED MULTIMEDIA DATA STREAMS BY MULTIMEDIA DEPENDENCY ANALYSIS AND ONTOLOGICAL FILTERING." International Journal of Software Engineering and Knowledge Engineering 21, no. 08 (2011): 1169–208. http://dx.doi.org/10.1142/s0218194011005669.
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We present a mathematical model of multimedia data streams and a framework for multimedia functional dependency analysis. The dual objectives are to effectively design multimedia data streams schema and to efficiently process continuous queries on sensor-based multimedia data streams. To further improve query processing, we introduce the concept of ontological filtering. A software tool to add multimedia functional dependencies to ontology is developed. Based upon multimedia functional dependency analysis and ontological filtering, query processing algorithms, illustrative examples and experimental results for sensor-based multimedia data streams continuous querying are presented to demonstrate the practical applications of our approach.
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Kannengiesser, Udo, and John S. Gero. "What distinguishes a model of systems engineering from other models of designing? An ontological, data-driven analysis." Research in Engineering Design 33, no. 2 (2022): 129–59. http://dx.doi.org/10.1007/s00163-021-00382-9.
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AbstractThis paper investigates how the core technical processes of the INCOSE model of systems engineering differ from other models of designing used in the domains of mechanical engineering, software engineering and service design. The study is based on fine-grained datasets produced using mappings of the different models onto the function-behaviour-structure (FBS) ontology. By representing every model uniformly, the same statistical analyses can be carried out independently of the domain of the model. Results of correspondence analysis, cumulative occurrence analysis and Markov model analysis show that the INCOSE model differs from the other models in its increased emphasis on requirements and on behaviours derived from structure, in the uniqueness of its verification and validation phases, and in some patterns related to the temporal development and frequency distributions of FBS design issues.
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Fedasyuk, Dmytro, and Illia Lutsyk. "Adaptive Software System Based on Ontological Approach for People With Cognitive Impairments." Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì 9 (June 10, 2021): 61–74. http://dx.doi.org/10.23939/sisn2021.09.061.
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The paper presents a method of creating an adaptive software system to help people with cognitive impairments, based on the use of an ontological model of the subject area. The specifics of creating software tools to help people with cognitive impairments are analysed. The features of using the ontological approach for the formation of adaptive functionality and graphical interface are revealed and their advantages over traditional methods are analysed. It was found that when using this method, there is no need to recompile and fully deploy the software system in the event of a change in business logic. An ontological model of the subject area has been designed, which will make it possible to customize the system for the needs of a particular user. The architecture of a software system based on an ontological model of the subject area is proposed, which takes into account the possibility of personalizing the components of the system and the user interface without the need to re-deploy the system. The process of adaptation of a mobile application based on data about health disorders of the user using an ontological model of the subject area is disclosed. The result of the research is the development of a software system that implements the proposed adaptation process and allows to modify a mobile application for the needs of a specific user, using an ontological model of the subject area.
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Eremin, I. E., E. B. Korobiy, A. V. Natsvin, V. I. Trukhin, and A. Iu Lokhov. "HIGH-TECH MODEL OF ALBAZINSKY FORT." Informatika i sistemy upravleniya, no. 3 (2021): 3–24. http://dx.doi.org/10.22250/isu.2021.69.3-24.
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The methodology of using computer technologies for scientific and metric modeling of lost wooden structures dating back to medieval period in Russian history is reviewed. The most accurate recon-struction of the Albazinsky Fort exterior as of 1685, implemented within the framework of ontological coordination of initial data maximum sampling, is presented.
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Mugizi, Wilson. "Constructing a Conceptual Framework for Quantitative Data Analysis in Social Science Research." INTERDISCIPLINARY JOURNAL OF EDUCATION (IJE) 2, no. 1 (2019): 74–88. http://dx.doi.org/10.53449/ije.v2i1.77.
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The article proposes how to construct a conceptual framework in social science research using the quantitative paradigm. The purpose of the paper is to provide a guideline for drawing a conceptual framework to students writing proposals based on scientific justification for data analysis. The paper explains how constructs are interlinked to develop a conceptual framework. The article argues that a conceptual framework is not a fixed network of variables but possesses ontological, epistemological, and methodological assumptions and each concept within a conceptual framework plays an ontological or epistemological role. The ontological assumptions explain how knowledge is or what knowledge is, the epistemological assumptions relate to how things really are done and how things certainly work in an assumed reality, and the methodological assumptions relate to the process of building the conceptual framework and assessing what it can tell us about the real world. Therefore, the conceptual frame shows how variables are interlinked, how analysis will be carried out and how the subsequent model will look like. In conclusion, the conceptual framework is not a form of fixed diagram but portrays the kind of analysis that will be or has been carried out in a study.
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Loginovskiy, O. V., and V. A. Beliakova. "DIGITAL TWIN-BASED MANAGEMENT MODEL FOR HIGH-TECH PRODUCTION." Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & Radioelectronics 25, no. 2 (2025): 95–106. https://doi.org/10.14529/ctcr250209.
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A management model for high-tech production based on digital twin technology is presented, combining the architecture of a data lake and the principles of ontological engineering and an agent-based service approach. The study examines the problems of managing complex production environments in the context of Industry 4.0, and suggests a hybrid approach combining the principles of a “smart factory” with lean manufacturing methodologies. The model includes a multi-level architecture covering strategic, tactical and operational levels, supported by an agent-service structure for system integration. The aim of the work is to develop an integrated management model for high-tech production based on the integration of digital twin technology, an ontological approach, and an agent-service architecture using a data lake. Methods. The research methodology uses a systematic approach to data management using data lake and electronic passports, and fuzzy ontologies to formalize knowledge. Results. The implementation is demonstrated on the example of multiscale modeling of chemical materials and compounds, where the effectiveness of the model is quantified. The results indicate a significant increase in productivity, especially in data retrieval operations, as structured search protocols demonstrate higher efficiency compared to traditional approaches. Conclusion. The results show that integration of digital twins with ontological structures and architectures of agency services provides enhanced operational control and decision-making capabilities in high-tech production environments. The practical application of the model demonstrates its scalability and adaptability in various industries, contributing to both theoretical understanding and practical implementation of advanced production systems. This research develops the field of high-tech production management by providing a structured framework for the digital transformation of production operations.
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Semenova, V. A., and S. V. Smirnov. "Models and methods of ontological data analysis in the problem of structural analysis and synthesis of technical decisions." Ontology of Designing 13, no. 4 (2023): 531–47. http://dx.doi.org/10.18287/2223-9537-2023-13-4-531-547.
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The article explores the potential and demonstrates the effectiveness of using some models and methods of ontological data analysis in the problem of structural analysis and synthesis of technical decisions. Morphological analysis and synthesis of layout diagrams of artifacts are considered as a working methodology for structural design. A set-theoretic model of the morphological decision space is constructed for the classical version of the methodology. The model in-cludes the functional subsystems of the designed artifact, implementation options for these subsystems, and potential technical decisions themselves. Moreover, in contrast to existing versions of such formalization, the emphasis is on the description of binary relationships between the entities of the knowledge domain of morphological analysis. It is pro-posed to describe the incompatibility of implementation options for a single functional subsystem of a designed arti-fact and the restricted compatibility of implementation options for various functional subsystems within the frame-work of a single model, known in ontological engineering and, in particular in ontological data analysis as “existence constraints”. Analysis of one of the regularities inherent in this model made it possible to strictly substantiate the ap-proach common in structural design to describing the restricted compatibility of implementation options for various functional subsystems in the form of prohibitions. The advantages of using existence constraints to describe the mor-phological decision space are shown, and the frame of a formal ontology for the knowledge domain of morphological analysis is constructed. The structural synthesis of a technical decision is compared with the method of semantic identi-fication of an object, developed within the framework of ontological data analysis for processing incomplete and in-consistent empirical information about the results of measuring object properties. A conclusion is made about the suit-ability of the latter for solving the problem of structural synthesis when correcting the concept of a “normal” subset of properties and information about the costs and/or benefits of including each individual implementation option for the functional subsystems of the designed artifact.
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Padilla-Cuevas, Josué, José A. Reyes-Ortiz, and Maricela Bravo. "Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments." Future Internet 13, no. 6 (2021): 151. http://dx.doi.org/10.3390/fi13060151.
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An Ambient Intelligence responds to user requests based on several contexts. A relevant context is related to what has happened in the ambient; therefore, it focuses a primordial interest on events. These involve information about time, space, or people, which is significant for modeling the context. In this paper, we propose an event-driven approach for context representation based on an ontological model. This approach is extendable and adaptable for academic domains. Moreover, the ontological model to be proposed is used in reasoning and enrichment processes with the context event information. Our event-driven approach considers five contexts as a modular perspective in the model: Person, temporal (time), physical space (location), network (resources to acquire data from the ambient), and academic events. We carried out an evaluation process for the approach based on an ontological model focused on (a) the extensibility and adaptability of use case scenarios for events in an academic environment, (b) the level of reasoning by using competence questions related to events, (c) and the consistency and coherence in the proposed model. The evaluation process shows promising results for our event-driven approach for context representation based on the ontological model.
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Rogushina, J. V. "Fuzzy data in semantic Wiki-resources: models, sources and processing methods." PROBLEMS IN PROGRAMMING, no. 2 (June 2023): 67–83. http://dx.doi.org/10.15407/pp2023.02.067.
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We analyze main types of dirty data processed by intelligente information systems, criteria of data classification and means of detection non-classical properties of data. Results of this analysis are represented by ontological model that contains taxonomy of classical and nonclassical data and knowledge-oriented methods of their transformation. Special attention is paid to semantically incorrect data that corresponds to vague knowledge. This ontological model intended to provide more effectively methods for transforming raw data into smart data suitable for automatic analysis, knowledge acquisition and reuse in other information systems. The ontological approach provides integration of the proposed model with other external ontologies that formalize characteristics of various methods and software tools that can be used fo data analysis (data mining, inductive inference, semantic queries, and instrimental tools for testing various aspects of the ontology quality, etc.). The work uses the experience of knowledge base developing of the portal version of the Great Ukrainian Encyclopedia e-VUE. This information resource is based on the semantic Wiki technology, it has a large volume, a complex structure and contains a large number of various heterogeneous information objects. Wiki resources are interesting from the point of view of collaborative processing the fuzzy data that describe heterogeneous information objects and knowledge structures. Due to the fact that the creation of this information resource involves a large number of specialists of various scientific fields, who have different areas of expertise and qualifications in use of knowledge-oriented technologies, there are many differences in the understanding of the rules for presenting and structuring data, and therefore a significant part of the Encyclopedia content needs additional verification of its correctness. Therefore, we need in formalized and scalable solutions for detection and processing various types of inconsistence, incompleteness and semantic incorrectness of data. The proposed approach can be useful for the creation of other large-scale resources based on both the semantic Wiki technology and other technological platforms for collaborative processing of distributed data and knowledge.
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Namestnikov, A. М. "Application of the ontological approach in the problem of event data generation using simulation models." Ontology of Designing 13, no. 2 (2023): 243–53. http://dx.doi.org/10.18287/2223-9537-2023-13-2-243-253.
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The article describes an application of the ontological approach to solving the problem of generating event data coming from the logs of simulation experiments. Currently, as part of the scientific direction Intelligent analysis of processes, methods and algorithms are being developed that allow solving machine learning problems in relation to event data. Simulation modeling can play an important role in the formation of training samples. However the experimental results of simulation in the form of logs of a certain structure must be brought to the form of event logs as they are understood in the intellectual analysis of processes. This paper provides a statement of the problem for forming an ontological resource that makes it possible to generate an event log based on the results of simulation experiments with a discreteevent model in which requests for processing are presented in the form of agents. A formal description of the domain ontology and an algorithm for its redefinition based on the log data of the simulation model are given. As an object of simulation the paper proposes to consider a hierarchical decision-making system, which receives tasks of varying complexity. The level of complexity of tasks is used for choosing the level of hierarchy at which this task needs to be solved. The architecture of the developed ontological system is given, as well as the structure of concepts with the corresponding semantic relations and sets of instances.
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Ponciano, Jean-Jacques, Alain Trémeau, and Frank Boochs. "Automatic Detection of Objects in 3D Point Clouds Based on Exclusively Semantic Guided Processes." ISPRS International Journal of Geo-Information 8, no. 10 (2019): 442. http://dx.doi.org/10.3390/ijgi8100442.
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In the domain of computer vision, object recognition aims at detecting and classifying objects in data sets. Model-driven approaches are typically constrained through their focus on either a specific type of data, a context (indoor, outdoor) or a set of objects. Machine learning-based approaches are more flexible but also constrained as they need annotated data sets to train the learning process. That leads to problems when this data is not available through the specialty of the application field, like archaeology, for example. In order to overcome such constraints, we present a fully semantic-guided approach. The role of semantics is to express all relevant knowledge of the representation of the objects inside the data sets and of the algorithms which address this representation. In addition, the approach contains a learning stage since it adapts the processing according to the diversity of the objects and data characteristics. The semantic is expressed via an ontological model and uses standard web technology like SPARQL queries, providing great flexibility. The ontological model describes the object, the data and the algorithms. It allows the selection and execution of algorithms adapted to the data and objects dynamically. Similarly, processing results are dynamically classified and allow for enriching the ontological model using SPARQL construct queries. The semantic formulated through SPARQL also acts as a bridge between the knowledge contained within the ontological model and the processing branch, which executes algorithms. It provides the capability to adapt the sequence of algorithms to an individual state of the processing chain and makes the solution robust and flexible. The comparison of this approach with others on the same use case shows the efficiency and improvement this approach brings.
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Gribova, Valeriya, Yury Kulchin, Alexander Nikitin, et al. "A Multi-Model Ontological System for Intelligent Assistance in Laser Additive Processes." Applied Sciences 15, no. 8 (2025): 4396. https://doi.org/10.3390/app15084396.
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This study examines the key obstacles that hinder the mass adoption of additive manufacturing (AM) processes for fabrication and processing of metal parts. To address these challenges, the necessity of integrating an intelligent decision support system (DSS) into the workflow of AM process engineers is demonstrated. The advantages of applying a two-level ontological approach to the creation of semantic information to develop an ontology-based DSS are pointed out. A key feature of this approach is that the ontological models are clearly separated from data and knowledge bases formed on this basis. An ensemble of ontological models is presented, which is the basis for the intelligent DSS being developed. The ensemble includes ontologies for equipment and materials reference databases, a library of laser processing technological operation protocols, knowledge base of settings used for laser processing and for mathematical model database. The ensemble of ontological models is implemented via the IACPaaS cloud platform. Ontologies, databases and knowledge base, as well as DSS, are part of the laser-based AM knowledge portal, which was created and is being developed on the platform. Knowledge and experience obtained by various technologists and accumulated within the portal will allow one to lessen a number of extensive trial-and-error experiments to find suitable processing settings. In the long term, the deployment of this portal is expected to reduce the qualification requirements for AM process engineers.