Ontology Design Research Articles

A scoping review of literature on the application of swarm intelligence in the object classification domain

This scoping review aims to explore the various swarm technologies and how they have been used in the object classification domain with the desire to motivate the design of a generic swarm intelligence ontology based on the components of various swarm technologies. We used the PRISMA-ScR as a guide to our scoping review protocol. We conducted a search across thirteen databases and a random search as well on the internet for articles. We performed screening of all the articles by title to remove duplicates, we further on did a screening by the year of publication to ensure that all articles to be considered were published between 2012 and 2022 and we then did abstract or text synthesis. Our search query retrieved 3224 potential articles from the thirteen databases and 10 articles from a random search on the internet making a total of 3234 articles identified. Deduplication and screening were done on the identified articles and 287 articles which satisfied our inclusion criteria remained. We grouped the articles into three categories namely year of publication, swarm technology and swarm application. The year of publication showed a linear trend line which is an indication of growth in the swarm intelligence domain. Of the six categories of aims we identified we voluntarily chose to ignore articles where the aim was not specified. We noticed that 64.9% of articles were aimed at either modifying or improving. The swarm technology category indicated that 58.54% of the included articles were based on the Particle Swarm Optimization either independently or as part of a hybrid algorithm. 83.97% of the articles used classification as their swarm application. Interesting to note was the appearance of feature selection and optimization in this category. This scoping review gave an overview of how swarm technologies have been used in the object classification domain. Further research can be done by bringing and using existing algorithms in the development of generic swarm intelligence inspired ontologies.

An ontology design for validating childhood cancer registry data.

Ontologies can provide a valuable role in the work of cancer registration, particularly as a tool for managing and navigating the various classification systems and coding rules. Further advantages accrue from the ability to formalise the coding rule base using description logics and thereby benefit from the associated automatic reasoning functionality. Drawing from earlier work that showed the viability of applying ontologies in the data validation tasks of cancer registries, an ontology was created using a modular approach to handle the specific checks for childhood cancers. The ontology was able to handle successfully the various inter-variable checks using the axiomatic constructs of the web ontology language. Application of an ontological approach for data validation can greatly simplify the maintenance of the coding rules and facilitate the federation of any centralised validation process to the local level. It also provides an improved means of visualising the rule interdependencies from different perspectives. Performance of the automatic reasoning process can be a limiting issue for very large datasets and will be a focus for future work. Results are provided showing how the ontology is able to validate cancer case records typical for childhood tumours.

MODELLING THE DESIGN OF MODELS: AN EXAMPLE USING CRISP-DM

AbstractDesign is widely understood as a domain-independent notion, comprising any activity concerned with creating artefacts. This paper shows that models can be viewed as artefacts, and that the design of models resembles the design of artefacts in other domains. The function-behaviour-structure (FBS) ontology of design is applied to models, mapping generic characteristics of models derived from literature on modelling onto basic, design-ontological categories. An example of model design, namely the CRISP-DM model for designing data mining models, is analysed and compared with models of designing in other domains (systems engineering, mechanical engineering, software engineering, and service design). The results show that there are fundamental commonalities but also differences, revealing the need for further research in developing a theory of model design.

A survey of inspiring swarm intelligence models for the design of a swarm-based ontology for addressing the cyber security problem

The increased use of the internet raises concerns about the security of data and other resources shared in cyberspace. Although efforts to improve data security are visible, the need to continuously explore other avenues for preventing and mitigating cyberattacks is apparent. Swarm intelligence models have, in the past, been considered in cybersecurity though there was no formal representation of the swarm intelligence knowledge domain that defines how these models fit into the cybersecurity body of knowledge. This article reviews the aspects of three swarm intelligence models that may inspire the design of the desired swarm intelligence ontology. The algorithms are particle swarm optimization, ant colony optimization, and the artificial bee colony model. In each case, we investigate the main driving features of the model, the causal aspects, and the effects of those causal aspects on the resolution of the cybersecurity problem. We also investigate how these features can be recommended as the building blocks of the desired swarm intelligence ontology. Investigations indicate that the artificial bee colony model has three outstanding aspects considered for the design of the swarm intelligence ontology and that is the quality, popularity, and communication. Foraging through pheromone deposits is an outstanding component of ant colony optimization that aids in locating threats sources more quickly by using the shortest route or tracks with high pheromone deposits. The particle swarm optimization model, on the other hand, adds alignment, cohesion, and collision avoidance aspects to the ontology to augment the ant colony and artificial bee colony algorithms. In our view, although intrusion detection is a complex problem in cybersecurity, the power of integrated swarm intelligence models is more than the sum of the individual capabilities of each swarm intelligence model individually. The article, therefore, proposes a swarm intelligence ontology that will potentially bring us closer to resolving the general cybersecurity problem.

Domain Ontology Representation Model Based on Graph Databases

The article presents an approach to modeling domain ontologies based on graph databases. Ontology is traditionally considered as a means of studying and formalizing the subject area. Based on ontologies, knowledge bases of information systems are formed, which can later be replenished and used to study certain applied aspects of the subject area. At the same time, with the development of NoSQL technologies and graph databases aimed at optimizing work with related data, it becomes possible to design a data warehouse without a strict pre-established domain model. Due to the obvious graph nature of ontologies, graph databases are a promising solution for storing and working with ontologies. However, with all the similarities, the ontology and data models used in graph DBMSs are not so easy to combine. The paper proposes an approach to the integration of ontological and graph models of knowledge representation and considers its application in creating a database for a prototype of a web ontology editor. Visual tools for editing ontologies are described, an algorithm for layer-by-layer rendering of a directed graph is given, a mechanism for generating dynamic forms for editing classes and ontology instances is described, and basic support for ontological design patterns is implemented.

Remember the Future

The starting point of this study is the prehistoric “teganoschemo” archaeological find of the Syros-Keros civilization in the Aegean Sea. These artifacts have been causing debates among archaeologists as their raison d'être is still contested. The aim of this study is to bring a prehistoric ontological model of design and craft to contemporary design practices. In order to explore such alternative ontologies, we turn to the past and address themes of death and life embodied in these prehistoric artifacts. As we leave Modernity behind and transition towards Sustainment, a new ontology for Design is necessary. By understanding the ontological framework of prehistoric designers, we aim to create propositional artifacts that exemplify what design can be. The propositional artifacts created act as different phases in a research-through design process that aims to investigate how design operates within an alternative system of values.

Toward establishing a knowledge graph for drought disaster based on ontology design and named entity recognition

Abstract Drought disasters have caused serious impacts on the social economy and ecological environment, which are continuously and increasingly exacerbated by climate warming and other factors. Drought disaster management usually involves processing a mass of isolated data from many fields expressed in different terminologies and formats. These heterogeneous data or so-called data silos have greatly hindered drought disaster management in an information-rich manner. Establishing a drought disaster knowledge graph can facilitate the reuse of these heterogeneous data and provide references for drought disaster management, and ontology design and named entity recognition are the two major challenges. Therefore, in this study, we first designed a drought disaster ontology by recognizing the major concepts in the drought disaster field and their relationships, which was implemented with an ontology modeling language. We next constructed a drought disaster corpus and an integrated entity recognition model that was built by integrating multiple deep learning methods. Finally, we applied the integrated entity recognition model to extract information from the CNKI literature database. The integrated model shows satisfactory results in drought disaster named entity recognition. We thus conclude that combining ontology and deep learning technology toward establishing a knowledge graph for drought disasters is promising.

A reference implementation for knowledge assisted robot development for planetary and orbital robotics

The use of modular, yet reusable and interchangeable components offers flexibility for system designers and thus leads to a higher degree of reconfigurability with cost effective, adaptable and scalable solutions. The development of a robotic system remains, however, a complex task with increasing demands depending on the targeted capabilities, functionalities and operational constraints of the robot. This requires expert knowledge in mechanical, electrical and software engineering, as well as tools that can collect, process and use relevant data. As a result, the amount of available and managed information is increasing, while its relevance, usability, and knowledge that can be extracted from it are consequently decreasing: a situation described as information overload paradox.The design of a modular system can be based on the use of standardized modules with universal interconnects, but it should be aligned with a strong formalism, e.g. the semantic representation of components, to allow for a better management of the overall complexity. An ontology-based knowledge representation, for instance, which provides domain and application specific knowledge for the design of robotic systems, can be used as a method of storing and sharing data in a uniform, machine-readable and standardized way.In this paper, we introduce the Knowledge-based Open Robot voCabulary as Utility Toolkit (korcut) as a core component to support the ontology-driven development of robotic systems as part of a reference implementation of the Q-Rock development cycle. Q-Rock gathers methods to assist users in designing robot configuration by: (a) automatically exploring robot capabilities based on robot hardware, (b) proposing robot designs to meet the user’s needs, (c) refining the proposed robot designs. We use korcut to improve the robot design process in orbital and planetary robotics from the requirements definition to the development phases of complex modular robotic structures (e.g. composition of an unmanned ground vehicle with robotic arms). This is implemented by embedding semantic component descriptions in a state-of-the-art open-source 3D modeling software. Furthermore, the korcut ontology family includes various sub-ontologies to address specific space-related tasks, such as the modeling of a Standard Interconnect (SI) for On Orbit Services (OOS) and Orbital Factory. The ontology design follows criteria that have been derived from a survey conducted as part of this work. This paper also covers an evaluation of its current applications from a methodological, knowledge representation, and software tool perspectives. In the application part, we introduce the use of the ontology to model a multi-functional SI that enables mechanical connections between various (modular) robotic components, as well as transfer of power and data. Finally, we provide a critical analysis of our work and outline its future work.

Guidelines for the reuse of ontology content

Reuse of elements from existing ontologies in the construction of new ontologies is a foundational principle in ontological design. It offers the benefits, among others, of consistency and interoperability between such knowledge structures as well as sharing resources. Reuse is widely found within important collections of established ontologies, such as BioPortal and the OBO Foundry. However, reuse comes with its own potential problems involving ontological commitment, granularity, and ambiguity. Guidelines are proposed to aid ontology developers and curators in their prospective reuse of content. These guidelines have been gleaned over years of practice in the ontology field. The guidelines are couched in experiential reports on designing and curating particular ontologies (e.g., EXACT and EXACT2) and using generally accepted approaches (e.g., MIREOT) in doing so. Various software tools to assist in ontology reuse are surveyed and discussed.

Designing ontologies for behaviours based on temporal passive data

The use of ontologies to model human behaviours that affect health is challenging since this process involves data from multiple inter-related domains that unfold and evolve over time. However, while current ontology development methodologies are generic enough to model any domain of interest, they do not provide design guidelines for modelling time-related aspects. This paper proposes a methodology for ontology development that entails the requirements for behaviours modelling based on passive temporal data. Its main focus is on temporal representations of classes and their holistic relations since no other methodology approaches ontology design from its temporal perspective. We exemplify these ideas by modelling the sleep behaviour domain, its relations to other behavioural aspects, and its effects on health.

Applying the LOT Methodology to a Public Bus Transport Ontology aligned with Transmodel: Challenges and Results

We present an ontology that describes the domain of Public Transport by bus, which is common in cities around the world. This ontology is aligned to Transmodel, a reference model which is available as a UML specification and which was developed to foster interoperability of data about transport systems across Europe. The alignment with this non-ontological resource required the adaptation of the Linked Open Terms (LOT) methodology, which has been used by our team as the methodological framework for the development of many ontologies used for the publication of open city data. The ontology is structured into three main modules: (1) agencies, operators and the lines that they manage, (2) lines, routes, stops and journey patterns, and (3) planned vehicle journeys with their timetables and service calendars. Besides reusing Transmodel concepts, the ontology also reuses common ontology design patterns from GeoSPARQL and the SOSA ontology. As part of the LOT data-driven validation stage, RDF data has been generated taking as input the GTFS feeds (General Transit Feed Specification) provided by the Madrid public bus transport provider (EMT). Mapping rules from structured data sources to RDF were developed using the RDF Mapping Language (RML) to generate RDF data, and queries corresponding to competency questions were tested.

A systematic comparison and evaluation of building ontologies for deploying data-driven analytics in smart buildings

Ontologies play a critical role in data exchange, information integration, and knowledge sharing across diverse smart building applications. Yet, semantic differences between the prevailing building ontologies hamper their purpose of bringing data interoperability and restrict the ability to reuse building ontologies in real-world applications. In this paper, we propose and adopt a framework to conduct a systematic comparison and evaluation of four popular building ontologies (Brick Schema, RealEstateCore, Project Haystack, and Digital Buildings) from both axiomatic design and assertions in a use case, namely the Terminological Box (TBox) evaluation and the Assertion Box (ABox) evaluation. In the TBox evaluation, we use the SQuaRE-based Ontology Quality Evaluation (OQuaRE) framework and concede that Project Haystack and Brick Schema are more compact with respect to the ontology axiomatic design. In the ABox evaluation, we apply an empirical study with sample building data that suggests Brick Schema and RealEstateCore have greater completeness and expressiveness in capturing the main concepts and relations within the building domain. The results indicate that there is no universal building ontology for integrating Linked Building Data (LBD). We also discuss ontology compatibility and investigate building ontology design patterns (ODPs) to support ontology matching, alignment, and harmonisation.

Humanitarian expertise as a method of socio-humanitarian engineering (introduction to the ontology of humanitarian design)

The paper presents the conception of humanitarian expertise practice as a method. It is justified that the so-called post-non-classical situation allows coexistence of various ontologies and ontological patterns. It is presumed that these ontologies are project and human-created. The accustomed approaches of learning the world through objects and mastering the world in a necessary way are being replaced with an approach which measures, on the one hand, the constant transformation of the worlds, on the other – the metamorphoses and authors of the projects that go through their own process of changes together with humancreated worlds. The article presents the method of humanitarian expertise understood as the method of socio-humanistic engineering which implies construction and alteration of social worlds and management of metamorphosis of these changes. The author demonstrates that the transition to non-classical situation of self-determination is related to the replacement of the principle of human-sizedness of the world and the principles of objectivity, rationality and cognizability of the world with other patterns: that the world is not objective, not humanscaled, not sensible or rational. It is diverse – depending on the patterns of the designer. The article presents the principle scheme of this method. It describes the situation of launch and initiation of the project aimed not only at creation of new worlds but management of the metamorphosis of the changes in the authors of these changes. It is the unique feature of humanitarian projection and social engineering that differs from previously described experience and practice of the application of the project approach, where the authors of the projects were not the subject of reflexive self-projection.

Optimization and experimental validation of 3D near-isotropic auxetic structures

The maturation of additive manufacturing has caused an explosion in lattice metamaterials. One of the most promising metamaterial families are auxetics, but these structures often exhibit anisotropy which limits their use. In this study, novel polygon celled 3D star structures were investigated and engineered to counteract design deficiencies. A new lattice design ontology was developed and used to carry out low cost optimisation with curved links. The resulting cells opened new forms of symmetry which were shown to reduce the anisotropy of the lattices by between 75% and 90%. The cubic and rhombic dodecahedral cells performed promisingly with Poisson’s ratios of −0.449 and −0.401 and anisotropic range of 0.022 and 0.085 respectively. Link thickness was parameterised and used to aid cell scaling and balance stiffness and metamaterial behaviour while ensuring cell manufacturability. The experiments demonstrated that the geometrical simplicity was beneficial to the cell properties and the success probability of the manufacturing process. The new optimisation method described in this study has been demonstrated to be sufficiently low cost to be applied at the cell level. It will pave the way to practical strain based design of graded structures which are vital for the practical growth of metamaterials.

Specimen, biological structure, and spatial ontologies in support of a Human Reference Atlas

The Human Reference Atlas (HRA) is defined as a comprehensive, three-dimensional (3D) atlas of all the cells in the healthy human body. It is compiled by an international team of experts who develop standard terminologies that they link to 3D reference objects, describing anatomical structures. The third HRA release (v1.2) covers spatial reference data and ontology annotations for 26 organs. Experts access the HRA annotations via spreadsheets and view reference object models in 3D editing tools. This paper introduces the Common Coordinate Framework (CCF) Ontology v2.0.1 that interlinks specimen, biological structure, and spatial data, together with the CCF API that makes the HRA programmatically accessible and interoperable with Linked Open Data (LOD). We detail how real-world user needs and experimental data guide CCF Ontology design and implementation, present CCF Ontology classes and properties together with exemplary usage, and report on validation methods. The CCF Ontology graph database and API are used in the HuBMAP portal, HRA Organ Gallery, and other applications that support data queries across multiple, heterogeneous sources.

Building a knowledge graph for operational hazard management of utility tunnels

The operational hazard management of the utility tunnel infrastructure is crucial for sustainable and resilient urban development. It not only involves various domain expertise such as safety, pipeline, structure, equipment, and electricity, but also requires timely and efficient access to and decision support from the relevant information of critical resources. However, current operational hazard management practices rely mainly on the experience of engineers, rendering it difficult to ensure management quality, thus increasing the risk of utility tunnel accidents. Hence, a knowledge graph-based decision support approach is proposed herein for the operational hazard management of utility tunnels, which illustrates the ontology design and information extraction from structured field inspection data and unstructured normative text files. The experimental case study demonstrates that this approach can improve the hazard management capabilities of utility tunnels by providing decision aids such as query, analysis, and control measure feedback.

Sistem Rekomendasi Film Dengan Pendekatan Ontologi

Movie is one of the easiest and cheapest entertainment human can experience. Nevertheless, there is an abundant amount of movies to watch. In the US and Canada alone, there are 403 movies produced in 2021. That is a huge amount of movies one person can watch. Most of people usually confused in determining which movies to watch, especially after watching a movie that truly suits their taste. Determining a decision in choosing a movie to watch requires a recommendation system. The recommendation system will provide decisions with good accuracy if it is collaborated with the Semantic Web using ontologies. In this study, researchers aims to build a movie ontology design which will later be used as a processing database in a movie selection recommendation system. In building the ontology, researcher requires the Methontology method. The methontology stages are performing the stages of specification, knowledge acquisition, conseptualizationo, integration, implementation, evaluation, and documentation.

An intelligent analysis method of security and stability control strategy based on the knowledge graph

The security and stability control system is the guarantee of the security and stability operation of the power grid. With the increasing scale of distributed new energy access to the power grid, the security and stability control strategy of the power grid is becoming more complex, and it is becoming increasingly important to correctly analyze and implement the security and stability control strategy. In order to ensure the correctness of the security and stability control strategy implemented by the security and stability control device, it is necessary to analyze the security and stability control strategy in detail. Therefore, this article proposes an intelligent analysis method of the security and stability control strategy based on the knowledge graph. First, this article introduces the ontology design method of the security and stability control strategy based on the knowledge graph, combines the characteristics and applications of the knowledge graph, analyzes the relationship between the elements of the strategy, and designs a clear-structured knowledge network. Second, this article analyzes the automatic construction technology of the graph, constructs the six-element ontology model of the security and stability control strategy, and realizes the human–computer interaction functions such as auxiliary decision making, strategy reasoning, and intelligent search based on the knowledge graph. Using artificial intelligence technology, this article takes the security and stability control strategy of a certain area’s security and stability control system as an example to model and manage. The results show that it can assist the tester to quickly retrieve the strategy, effectively improve the detection efficiency of the security and stability control strategy, avoid the omission and ambiguity caused by the manual understanding of the strategy, and ensure the accuracy and comprehensiveness of the security and stability control strategy detection.

Development of machine tool communication method and its edge middleware for cyber-physical manufacturing systems

ABSTRACT By enabling the fusion of cyber and physical world, Cyber-physical systems (CPSs) have emerged as a key technology of the fourth industrial revolution – Industry 4.0. One of the major challenges for developing manufacturing CPSs is establishing communication between physical resources and Internet/cloud-hosted applications. Recently, MTConnect has become a widely popular communication method for monitoring machine tools in cyber manufacturing. However, it does not allow remote operations of machine tools over the Internet, which is essential in many manufacturing CPSs. This paper presents an Internet-scale service-oriented communication method named Machine Tool Communication (MTComm), which provides capabilities of both monitoring and operating heterogeneous machine tools over the Internet. MTComm allows machine tools to exchange manufacturing services and associated information in XML format through RESTful web services. This paper describes design and development of MTComm components, ontology, and methodology of data acquisition and direct operation through five types of services. To reduce communication latency and improve performance, three optimization strategies were developed and used in an edge-based middleware. Experiments were conducted in a testbed with five machines at different stages of MTComm development and results demonstrated excellent feasibility for efficiently monitoring and operating heterogeneous machine tools in a scalable cyber-physical manufacturing environment.

Blockchain Enterprise Ontologies: TOVE and DEMO

Enterprise ontology for blockchain transactions includes datalogical, infological and essential levels. OntoClean analyzes ontologies based on formal, domain-independent properties (metaproperties), being the first attempt to formalize the notion of ontological analysis for computer systems. The notions are extracted from the philosophical ontology. In the semantic web, a property is a binary relationship, with a subtle distinction between ownership and class. Thus, a metaproperty is a property of a property or a class. The design of ontology can be done when there is a basic understanding of the blockchain analysis.