Ontological Description Research Articles

A fighter for respect and awe for God’s world of creation

The overarching aim of this article is to give the first concise introduction in English to the oeuvre of the Danish ecotheologian Ole Jensen. The article lays out four key insights which Jensen develops mainly between 1967–1976. These are (1) his reception and continuation of the creation theology developed by K. E. Løgstrup, (2) the thesis that pollution is blasphemy, (3) his description of a trustworthy ontology between illusion and restriction, and (4) his theological critique of ideology aimed at Western culture. Although the scope of the article is not limited to the early period, my claim is that these four insights constitute the base from which to grasp the unifying ideas in Jensen’s body of work. Subsequently, the article argues that Jensen’s theological contributions can be understood as the very first account of a Scandinavian ecotheology. In a constructive conversation with the sociologist Hartmut Rosa, the article ends by considering the possibilities and challenges for igniting the necessary motivation for social change in a time of ecological crisis.

A behaviouristic semantic approach to blockchain-based e-commerce

Electronic commerce and finance are progressively supporting and including decentralized, shared and public ledgers such as the blockchain. This is reshaping traditional commercial activities by advancing them towards Decentralized Finance (DeFi) and Commerce 3.0, thereby supporting the latter’s potential to outpace the hurdles of central authority controllers and lawgivers. The quantity and entropy of the information that must be sought and managed to become active participants in such a relentlessly evolving scenario are increasing at a steady pace. For example, that information comprises asset or service description, general rules of the game, and specific technologies involved for decentralization. Moreover, the relevant information ought to be shared among innumerable and heterogeneous stakeholders, such as producers, buyers, digital identity providers, valuation services, and shipment services, to just name a few. A clear semantic representation of such a complex and multifaceted blockchain-based e-Commerce ecosystem would contribute dramatically to make it more usable, namely more automatically accessible to virtually anyone wanting to play the role of a stakeholder, thereby reducing programmers’ effort. However, we feel that reaching that goal still requires substantial effort in the tailoring of Semantic Web technologies, hence this article sets out on such a route and advances a stack of OWL 2 ontologies for the semantic description of decentralized e-commerce. The stack includes a number of relevant features, ranging from the applicable stakeholders through the supply chain of the offerings for an asset, up to the Ethereum blockchain, its tokens and smart contracts. Ontologies are defined by taking a behaviouristic approach to represent the various participants as agents in terms of their actions, inspired by the Theory of Agents and the related mentalistic notions. The stack is validated through appropriate metrics and SPARQL queries implementing suitable competency questions, then demonstrated through the representation of a real world use case, namely, the iExec marketplace.

RETRACTED: Design and Implementation of Folk Arts and Crafts Resource Library System Based on Ontology Description and Random Matrix

This article first constructs an ontology, designs the ontology of the resource library, and then uses the ontology to generate formatted SMD. It uses semantic elements to standardize the description of system resources, organizes folk arts and crafts resources in a machine understandable manner, and presents semantic features to users in an intuitive manner. And use random matrix theory to extract the correlation between data from massive amounts of data. The experimental results show that the running time of the system algorithm reaches 1.8 seconds, effectively avoiding the algorithm's extended state estimation falling into local optima and greatly reducing the computational complexity of the algorithm. This study is conducive to promoting the role of resource library systems and improving retrieval efficiency.

An ontology-based knowledge graph for representing interactions involving RNA molecules

The “RNA world” represents a novel frontier for the study of fundamental biological processes and human diseases and is paving the way for the development of new drugs tailored to each patient’s biomolecular characteristics. Although scientific data about coding and non-coding RNA molecules are constantly produced and available from public repositories, they are scattered across different databases and a centralized, uniform, and semantically consistent representation of the “RNA world” is still lacking. We propose RNA-KG, a knowledge graph (KG) encompassing biological knowledge about RNAs gathered from more than 60 public databases, integrating functional relationships with genes, proteins, and chemicals and ontologically grounded biomedical concepts. To develop RNA-KG, we first identified, pre-processed, and characterized each data source; next, we built a meta-graph that provides an ontological description of the KG by representing all the bio-molecular entities and medical concepts of interest in this domain, as well as the types of interactions connecting them. Finally, we leveraged an instance-based semantically abstracted knowledge model to specify the ontological alignment according to which RNA-KG was generated. RNA-KG can be downloaded in different formats and also queried by a SPARQL endpoint. A thorough topological analysis of the resulting heterogeneous graph provides further insights into the characteristics of the “RNA world”. RNA-KG can be both directly explored and visualized, and/or analyzed by applying computational methods to infer bio-medical knowledge from its heterogeneous nodes and edges. The resource can be easily updated with new experimental data, and specific views of the overall KG can be extracted according to the bio-medical problem to be studied.

Choosing the Sweet Life with DOLCE

An ontology in philosophy is a description of what exists; an ontology in information science is the formal specification of a domain for information organization. A top-level ontology is an ontology of high-level abstractions that is meant to provide a standard for other ontologies to make them interoperable. Top-level ontologies commit to certain philosophical assumptions in the worlds they model, such as naive scientific realism, or the choice to model only those worlds which “actually” exist. This paper uses a comparison of Basic Formal Ontology (BFO) and Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE) to investigate whether naive scientific realism is useful as a philosophical stance in ontological modelling. It investigates the specific philosophical and technical features of DOLCE which make it unique. BFO and DOLCE are compared, as well as a miniature literature review of comparisons between other top-level ontologies. Then it describes the history of DOLCE and BFO’s development in the context of the collaboration between Barry Smith and Nicola Guarino. Finally, it examines the application of DOLCE in various domains, such as “sweetening” WordNet.

Beyond International Relations and toward International Relationality?

This article provides a review and commentary on the articles in this special issue, which offer alter-IRs as approaches to bringing climate change into international relations theory and practice as a force or phenomenon that can transform theory and practice. I summarize the articles, as I read them, and suggest that this is a largely futile task. Is description of new ontologies and epistemologies sufficient to bring climate change into IR in a meaningful way? If the discipline is so constrained by its deeply rooted ontology and epistemology, why make the effort to attempt this transformation? And given that our task as philosophers is to ‘change the world’, what are the theories and practices that will make this happen?

A unified approach to publish semantic annotations of agricultural documents as knowledge graphs

The research results presented in this paper were obtained as part of the D2KAB project (Data to Knowledge in Agriculture and Biodiversity) which aims to develop semantic web-based tools to describe and make agronomical data actionable and accessible following the FAIR principles. We focus on constructing domain-specific Knowledge Graphs (KGs) from textual data sources, using Natural Language Processing (NLP) techniques to extract and structure relevant entities. Our approach is based on the formalization of a semantic data model using common linked open vocabularies such as the Web Annotation Ontology (OA) and the Provenance Ontology (PROV). The model was developed by formulating motivating scenarios and competency questions from domain experts. This model has been used to construct three different KGs from three distinct corpora: PubMed scientific publications on wheat and rice genetics and phenotyping, and French agricultural alert bulletins. The named entities to be recognized include genes, phenotypes, traits, genetic markers, taxa and phenological stages normalized using semantic resources such as the Wheat Trait and Phenotype Ontology (WTO), the French Crop Usage (FCU) thesaurus and the Plant Phenological Description Ontology (PPDO). Named entities were extracted using different NLP approaches and tools. The relevance of the semantic model was validated by implementing experts questions as SPARQL queries to be answered on the constructed RDF knowledge graphs. Our work demonstrates how domain-specific vocabularies and systematic querying of KGs can reveal hidden interactions and support agronomists in navigating vast amounts of data. The resources and transformation pipelines developed are publicly available in Git repositories.

Ontological description method for building service-oriented distributed learning systems

The subject of the research is the analysis and justification of the use of software engineering processes based on ontologies of data access and representation of access to knowledge bases and knowledge reuse in the language of algebra of finite predicates, which is a class of descriptive logics. This approach allows you to use the advantages of ontologies and logic programming in the refactoring of distributed distance learning systems. The purpose of the work is to create a formalism for describing the interaction of services and algorithms for building web service interfaces for the implementation of an effective SOA system using the paradigm of access to data based on ontologies. To achieve the goal, the following tasks were solved: an analysis of the main types of interaction structures of SOA services, an overview of implementations of systems working with a family of descriptive logic languages, namely, algebra of finite predicates, and a description of the structure of the ontology necessary for the operation of service-oriented systems, which has the markup of the Semantic Web standard using finite predicate algebra equations. The task is an urgent task of ensuring the organization of interaction of Internet resources in the development of distributed virtual learning systems, and such interaction is enabled by the service-oriented architecture of software development. The article examines modern technologies of the Semantic Web and their role in ensuring the creation of applied software systems of distributed learning resources built using distributed interactive services. The considered methods and materials include methods of algebra of finite predicates, theory of algorithms, object-oriented design, theory of unification. The results. The semantics of the SOA system is obtained, which makes it possible to describe SOA systems in the languages of descriptive logic. The effectiveness of the mathematical formalism of the algebra of finite predicates for the tasks of logical analysis of applied ontologies, the use of knowledge reuse methods, and the description of service-oriented systems is shown. The necessity of using algorithms for automatic construction of web interfaces is shown. The conclusions of the work highlight the advantages of the researched solution, namely, algorithms for the automated construction of web service interfaces for SOA architecture, which make it possible to automatically build web service interfaces. Algorithms differ in a more general model and speed of work and require an assessment of complexity.

Kierkegaard’s Descriptive Philosophy of Religion: The Imagination Poised between Possibility and Actuality

Rethinking the powers of the imagination, Søren Kierkegaard both anticipates and challenges contemporary approaches to a descriptive philosophy of religion. In contrast to the reigning approaches to religion in his day, Kierkegaard reconceives philosophy as, first of all, descriptive of human, including specifically ethical and religious, existence. To this end, he develops conceptual tools, including a descriptive ontology of human existence, a “pluralist epistemology” exploring both cognitive and passional dimensions of religion, and a role for the poetic in philosophy, strikingly expressed in his observer figures who “imaginatively construct” “thought projects” to explore human existence. While this new descriptive account anticipates subsequent approaches to the philosophy of religion, it could be interpreted as another “objectivist” endeavor, yet Kierkegaard attempts more in this descriptive philosophy. He imaginatively deploys conceptual and rhetorical strategies maieutically to both describe and elicit self-reflection aimed at transformation, thus expanding the imagination’s uses for his readers. Comparing Kierkegaard to Pierre Hadot’s recovery of ancient Greek philosophy as “a way of life” will show how Kierkegaard also engages the particularity of “the Christian principle”, with implications for how philosophy can both describe and elicit the pathos of other religious traditions as well.

Reac4Cat-Ontology: Harnessing the Power of Ontological Description Logic in Catalysis Research as a Practical Approach to Knowledge Inferences

Maximizing the use of digitally captured data is a key requirement for many of the late adopters of digital infrastructure. One of the newcomers is the chemical industry in the area of digitized laboratories. Here, tools and services that satisfy individual needs still need to be developed and distributed within the community. This work explores the potential of using graph databases — specifically those modeled via ontological knowledge graphs — to describe complex data linkages and draw logical conclusions. While knowledge graphs are not widely utilized in catalysis research, this study introduces a methodology to highlight their usability for semantic description and integration into diverse value chains with contact to the domain of (bio)chemistry and catalysis.A demonstration is performed how ontologies and their knowledge graphs can be applied to perform essential functions of semantic annotation to chemical reactions, which are difficult to model relational. Traditional data description methods can be neglected using description logic, showing how logical inferences at the machine level can enrich data. This work also illustrates the seamless integration of this enhanced data into process simulations, connecting semantic description with practical applications. The immediate benefits for catalysis research are emphasized and the development of new tools and services envisioned. By clarifying how these graphs can be integrated into existing workflows, researchers are empowered to make the most of digitally acquired data in catalytic processes. This practical methodology lays the foundation for improved decision-making and innovation, fostering advancements in the field of catalysis research.

Towards a formal ontology of engineering functions, behaviours, and capabilities

In both applied ontology and engineering, functionality is a well-researched topic, since it is through teleological causal reasoning that domain experts build mental models of engineering systems, giving birth to functions. These mental models are important throughout the whole lifecycle of any product, being used from the design phase up to diagnosis activities. Though a vast amount of work to model functions has already been carried out, the literature has not settled on a shared and well-defined approach due to the variety of concepts involved and the modeling tasks that functional descriptions should satisfy. The work in this paper posits the basis and makes some crucial steps towards a rich ontological description of functions and related concepts, such as behaviour, capability, and capacity. A conceptual analysis of such notions is carried out using the top-level ontology DOLCE as a framework, and the ensuing logical theory is formally described in first-order logic and OWL, showing how ontological concepts can model major aspects of engineering products in applications. In particular, it is shown how functions can be distinguished from the implementation methods to realize them, how one can differentiate between capabilities and capacities of a product, and how these are related to engineering functions.

Methods for Thematic Analysis and Ranking in Information Analysis Systems Based on Relational DBMS

The paper presents the models and algorithms for searching, filtering and ranking data in an information analysis system, based on the ontological description of its structure. The rules for filtering and ranking objects based on their boolean, numeric or enumerable properties are specified by the users, and based on these rules SQL queries are evaluated. Another problem considered is taking subject area into account when searching for objects. Adding this allows one to solve many tasks that occur in current research information systems, such as searching for experts in given subject areas or generating reports. A search query can be specified in the form of a set of keywords, and a statistical approach is used for comparing keyword sets.

Designing an intelligent territorial safety management system

The conceptual stage of designing an intelligent territorial safety management system is presented. The article shows the problems of information support for management associated with the need to process a large volume of unformalized data and their low reliability. Existing descriptions of objects and processes are not constructive. The approval and decision-making processes are poorly algorithmized and there are no feedback mechanisms reflecting the quality of decisions. As an alternative, the article proposes the use of intelligent technologies that change the mechanisms for collecting, processing and using data. An ontological description of a multi-level management model is presented that formalizes the main tasks of ensuring the natural and technogenic security of territories. Management levels and objects are highlighted, and their information support is shown. The model is based on assessments of territorial risks, representing a combination of comprehensive monitoring indicators. The novelty of the approach lies in the possibility of justifying the types and volumes of activities with the magnitude of risks, as well as linking management results with the necessary resources. The model is the basis of the intelligent system project. Using object-oriented programming methods, the transition from ontological description to structural and functional designing is shown. Representation of ontology elements in the form of sets allows the construction of multidimensional analytical models that reveal ways to solve management problems in specific conditions. This makes it possible to justify the composition of information and the requirements for its quality for each level of the territorial management hierarchy. Problem solving examples of ensuring territorial safety in accordance with the proposed classification are given. The model can be used as a scientific basis for management digitalization programs implemented in the constituent entities of the Russian Federation.

Context-attentive robot reconfiguration for human-machine space missions

With humankind’s aspiration of extraterrestrial inhabitation, the need for robotic support is eminent. To master the emerging challenge of providing astronauts with assistive space robots possessing the required adaptability to new situations and tasks under the constraints of severely limited supply chains in extraterrestrial missions, the utilization of existing hardware to its fullest is required. We propose the combination of a concept with an architecture to jointly support context-aware collaboration between humans and robotic systems for implementing effective resource utilization in space missions. The underlying framework is an implementation of a flexible architecture that enables context awareness for robotic systems. It supports processing nodes for retrieval of context information from the raw sensor values as well as further inferences using the output of nodes. Context information spans across three entities and describes the current state of the environment, the astronaut, and the robot itself. This information then can be used to infer the human’s current intention as well as influence the behaviour to be executed next. Additionally, dynamic changes in the data processing chains are handled by the framework to facilitate an adequate adaptation of the system to situational events. We combine this architecture with the concept of space robots as a composition from building blocks, which are supported and made accessible by a software toolkit. The modular design approach enables online self-reconfiguration of robotic hardware and software components. In combination with dynamic mission planning, based on ontological descriptions of available resources and functionalities, robots are able to adapt their physical and computational appearance dynamically during a mission according to different tasks and goals. By incorporating these two developments in a joint deployment we envision raising the efficiency of robotic systems in human-machine interaction through the usage of self-reconfiguration as a reactive behavior in order to adapt to a specific task, recognized or derived from a human’s intention. Transfer of the proposed idea back to Earth may help to abate resource dissipation caused by deploying specialized monolithic systems with a narrow range of capabilities through utilizing the adaptivity of reconfigurable robots.

Exploring Potentilla nepalensis Phytoconstituents: Integrated Strategies of Network Pharmacology, Molecular Docking, Dynamic Simulations, and MMGBSA Analysis for Cancer Therapeutic Targets Discovery.

Potentilla nepalensis belongs to the Rosaceae family and has numerous therapeutic applications as potent plant-based medicine. Forty phytoconstituents (PCs) from the root and stem through n-hexane (NR and NS) and methanolic (MR and MS) extracts were identified in earlier studies. However, the PCs affecting human genes and their roles in the body have not previously been disclosed. In this study, we employed network pharmacology, molecular docking, molecular dynamics simulations (MDSs), and MMGBSA methodologies. The SMILES format of PCs from the PubChem was used as input to DIGEP-Pred, with 764 identified as the inducing genes. Their enrichment studies have shown inducing genes' gene ontology descriptions, involved pathways, associated diseases, and drugs. PPI networks constructed in String DB and network topological analyzing parameters performed in Cytoscape v3.10 revealed three therapeutic targets: TP53 from MS-, NR-, and NS-induced genes; HSPCB and Nf-kB1 from MR-induced genes. From 40 PCs, two PCs, 1b (MR) and 2a (MS), showed better binding scores (kcal/mol) with p53 protein of -8.6 and -8.0, and three PCs, 3a, (NR) 4a, and 4c (NS), with HSP protein of -9.6, -8.7, and -8.2. MDS and MMGBSA revealed these complexes are stable without higher deviations with better free energy values. Therapeutic targets identified in this study have a prominent role in numerous cancers. Thus, further investigations such as in vivo and in vitro studies should be carried out to find the molecular functions and interlaying mechanism of the identified therapeutic targets on numerous cancer cell lines in considering the PCs of P. nepalensis.

Local Government: A Social Ontology of Care

Setting out to determine what ‘local government’ is and how it can be understood, I conducted an analysis of the concept ‘local government’ by identifying its institutional, behavioural and territorial attributes. This analysis informed an ontological description of the nature of local government and the underlying assumptions about this reality. Ontological, local government, as a collection of ‘Dasein’ with an immanent tension between anxiety and care, may simultaneously be viewed as being a social collective of individuals, an institution consisting of individuals, and a social action or intervention performed by caring individuals. The description of the nature of local government provides a point of departure for describing and comparing this reality as situated in different contexts. It also serves as a proposed menu for the questioning and challenging of underlying assumptions about local government. The value of this social ontology of care lies in the description of the nature of the reality of local government situated in different contexts. Furthermore, it serves as an agenda for questioning and challenging the underlying assumptions about local government within different contexts.

Functional Programming of Intelligent Systems

An intelligent system is a system that uses intelligence to shape its behavior in its environment. This intelligence depends on the following main factors: the first is the ability of the system to model the environment with which the system interacts. The second factor: using this model to successfully plan and solve problems that determine the behavior of the system in the environment in order to achieve the goals set for the system. Modeling of the environment is based on the use of knowledge about the environment and its components, which the system collects using its sensors and organs, as well as the knowledge base, which stores information previously collected or incorporated during the development of the system. This information in the form of knowledge uses various forms of mathematical structures that form the basis of the model, logic and ontology that are part of the knowledge representation. Problem solving applies either previous experience, or uses a logical conclusion, based on the logic embedded in the system during its development, or ontological description, included in the representation of knowledge and relationships between elements. When developing an intelligent system, you can apply the methods and tools of functional programming as a way to represent the development of a particular system, and analyze its capabilities and efficiency at the computational level.

Wildfire risk weighting and behaviour prediction using open geospatial data and ontologies

This article presents a novel approach to wildfire risk assessment and behaviour prediction by leveraging open geospatial data and ontologies. The proposed methodology includes a spatially weighted index model and multicriteria analysis to represent the risk of forest fires in the affected area. It bridges gaps in theory and practice, offering a comprehensive solution for evaluating potential forest fire risk in near real time, predicting fire behaviour and elucidating the semantics of fire management. During dry and hot conditions, forest fires tend to escalate. Hence, we propose an algorithm that combines experts’ empirical criteria and open-source data to identify dangerous fires in near real time, aiding authorities in directing attention to the riskiest areas. The objective is to predict forest fire behaviour, a complex and nonlinear system influenced by dynamic factors such as weather conditions, topography and land use. Our methodology enables real-time assessment of potential forest fire risks, complemented by predictive fire behaviour scenarios and a descriptive ontology of fire management semantics. We examine existing fire-related ontologies and propose a comprehensive one encompassing incident descriptions, firefighting resources, actor interrelations and knowledge for effective action. By classifying fire sources, our algorithm enables strategic decision-making to prevent uncontrolled fires. This solution significantly enhances data using semantic and spatial relationships among wildfire resources. Furthermore, we demonstrate how ontologies improve data integration and interoperability among diverse systems and organisations involved in forest fire risk management, fostering better coordination and faster responses to critical situations. To facilitate decision-making, we create decision-making scenarios linked to analysed hot spots, drawing from open hot spot data such as National Aeronautics and Space Administration (NASA) Fire Information for Resource Management System (FIRMS), OpenStreetMap (OSM), OpenWeatherMap (OWM) and OpenTopoData (OTD). We propose an ordinal and linguistic classification system (F1–F5) denoting risk levels as low, moderate, high, very high and extreme. These values are obtained through factor aggregation and fuzzy logic. A publicly accessible, interactive web map displays the results derived from this model. Overall, our contributions to wildfire risk management provide authorities with a valuable tool to make informed decisions and mitigate the damaging effects of wildfires.

Ontological Description of Design Rationale of Steel Design Knowledge and Its Use

Ontological Description of Design Rationale of Steel Design Knowledge and Its Use

Construction of injury process from Japanese consumer product narrative injury data using an ontology-based method

Understanding of how injuries occur plays an effective role in accident learning and prevention. Existing frameworks focus on crucial information but ignore their causal relationships, which can lead to an incomplete understanding of the injury process. In this study, the descriptive framework of injury data (DFID) is expanded and combined with accident causation models used to elaborate on the causality of each injury factor. Subsequently, the injury process description ontology (IPD-Onto) based on DFID (extension) is established through a seven-step method developed by Stanford University. The IPD-Onto divides injury cases into five unified classes and constructs the injury process through the object properties. The ontology-based description of the injury process (with causal relationships) provides additional description and interpretation capabilities that are understandable by human experts or computers. The results of the Protégé DL query show that the ontology-based method enables the machine to interpret the injury process.