General Ontology Research Articles

The ontology of coevolution beyond economic systems

AbstractThis paper provides an analysis of the general ontology of coevolutionary processes. I argue that to properly understand the ontological phenomenon of coevolution, we need to move away from neophobic, flat, and substance-based ontologies and adopt a pluralist and emergentist process metaphysics that takes into account both horizontal and vertical codetermination. Following this approach, I differentiate between ontological (co)evolution in a general and specific sense. General (co)evolution can be observed in physical and chemical matter. Before the emergence of living matter, the universe evolved, achieving more ontological complexity and qualitative density. Since physical and chemical matter are made up of a complex interplay of continuities and discontinuities, physical and chemical entities and processes are multiple and codetermine each other through a dynamic complex patterning, as basically described by what the Spanish philosopher Gustavo Bueno called symploké following Plato’s Sophist. Therefore, physical and chemical evolutionary processes are more accurately described as coevolutionary processes. On the other hand, specific coevolution can be observed in the biological, social, and cultural/artificial realms. Its ontological specificity lies in the dynamic interactions of novelty, replication, and selection, which are absent in physical and chemical matter. In conclusion, I argue that rather than unnecessarily complicating our view of reality, this approach is manageable epistemologically and allows for a better understanding of dynamic codetermination in the universe, from physical matter to cultural spheres.

Developing a Chatbot to Support Individuals With Neurodevelopmental Disorders: Tutorial.

Families of individuals with neurodevelopmental disabilities or differences (NDDs) often struggle to find reliable health information on the web. NDDs encompass various conditions affecting up to 14% of children in high-income countries, and most individuals present with complex phenotypes and related conditions. It is challenging for their families to develop literacy solely by searching information on the internet. While in-person coaching can enhance care, it is only available to a minority of those with NDDs. Chatbots, or computer programs that simulate conversation, have emerged in the commercial sector as useful tools for answering questions, but their use in health care remains limited. To address this challenge, the researchers developed a chatbot named CAMI (Coaching Assistant for Medical/Health Information) that can provide information about trusted resources covering core knowledge and services relevant to families of individuals with NDDs. The chatbot was developed, in collaboration with individuals with lived experience, to provide information about trusted resources covering core knowledge and services that may be of interest. The developers used the Django framework (Django Software Foundation) for the development and used a knowledge graph to depict the key entities in NDDs and their relationships to allow the chatbot to suggest web resources that may be related to the user queries. To identify NDD domain-specific entities from user input, a combination of standard sources (the Unified Medical Language System) and other entities were used which were identified by health professionals as well as collaborators. Although most entities were identified in the text, some were not captured in the system and therefore went undetected. Nonetheless, the chatbot was able to provide resources addressing most user queries related to NDDs. The researchers found that enriching the vocabulary with synonyms and lay language terms for specific subdomains enhanced entity detection. By using a data set of numerous individuals with NDDs, the researchers developed a knowledge graph that established meaningful connections between entities, allowing the chatbot to present related symptoms, diagnoses, and resources. To the researchers' knowledge, CAMI is the first chatbot to provide resources related to NDDs. Our work highlighted the importance of engaging end users to supplement standard generic ontologies to named entities for language recognition. It also demonstrates that complex medical and health-related information can be integrated using knowledge graphs and leveraging existing large datasets. This has multiple implications: generalizability to other health domains as well as reducing the need for experts and optimizing their input while keeping health care professionals in the loop. The researchers' work also shows how health and computer science domains need to collaborate to achieve the granularity needed to make chatbots truly useful and impactful.

An ontology and rule-based method for human–robot collaborative disassembly planning in smart remanufacturing

Disassembly is a decisive step in the remanufacturing process of End-of-Life (EoL) products. As an emerging semi-automatic disassembly paradigm, human–robot collaborative disassembly (HRCD) offers multiple disassembly methods to enhance flexibility and efficiency. However, HRCD increases the complexity of planning and determining the optimal disassembly sequence and scheme. Currently, the optimisation process of heuristic methods is difficult to interpret, and the results cannot be guaranteed as globally optimal. Consequently, this paper introduces a general ontology model for HRCD, along with a rule-based reasoning method, to automatically generate the optimal disassembly sequence and scheme. Firstly, the HRCD ontology model establishes the disassembly-related information for EoL products in a standardised approach. Then, customised disassembly-related rules are proposed to regulate the precedence constraints and optional disassembly methods for each disassembly task of EoL products. The optimal disassembly sequence and scheme are automatically generated by combining supportive rules with the ontology model. Lastly, the human–robot collaborative disassembly planning of a gearbox is presented as a case study to validate the feasibility of the proposed methods. Our method generates an optimal disassembly scheme compared with other heuristic algorithms, achieving the shortest process time of 308 units and the fewest number of disassembly direction change of 3 times. Additionally, the reasoning procedure can be easily tracked and modified. The proposed method is both universal and easily reproducible, allowing it to be extended to support the entire remanufacturing process.

An optimized system for sensor ontology meta‐matching using swarm intelligent algorithm

AbstractIt is beneficial to annotate sensor data with distinct sensor ontologies in order to facilitate interoperability among different sensor systems. However, for this interoperability to be possible, comparable sensor ontologies are required since it is essential to make meaningful links between relevant sensor data. Swarm Intelligent Algorithms (SIAs), namely the Beetle Swarm Optimisation Algorithm (BSO), present a possible answer to ontology matching problems. This research focuses on a method for optimizing ontology alignment that employs BSO. A novel method for effectively controlling memory use and striking a balance between algorithm exploration and exploitation is proposed: the Simulated Annealing‐based Beetle Swarm Optimisation Algorithm (SA‐BSO). Utilizing Gray code for solution encoding, two compact operators for exploitation and exploration, and Probability Vectors (PVs) for swarming choosing exploitation and exploration, SA‐BSO combines simulated annealing with the beetle search process. Through inter‐swarm communication in every generation, SA‐BSO improves search efficiency in addressing sensor ontology matching. Three pairs of real sensor ontologies and the Conference track were used in the study to assess SA‐BSO's efficacy. Statistics show that SA‐BSO‐based ontology matching successfully aligns sensor ontologies and other general ontologies, particularly in conference planning scenarios.

Object-Oriented Animals

In Graham Harman’s Object-Oriented Ontology (OOO), an apparent tension arises between his pursuit of a self-proclaimed “new theory of everything,” or general ontology, and his assertion that any ontology must be able to account for distinctions among various regions of being. This paper delves into this tension between universality and specificity, particularly concerning the question of animal ontology, and examines the potential for constructing an object-oriented animal ontology. By juxtaposing Harman’s perspectives with those of Matthew Calarco and other scholars, I aim to demonstrate the feasibility of developing an animal ontology using the framework of OOO.

Developing A New Model for Context-Awareness in Ambient Intelligence

Ontologies are a powerful way to model context, thanks to their expressiveness, ability to share knowledge, support for logical inference, and extensibility. While there are many generic ontology that capture and represent general context concepts, such as the SOCAM and CoOL projects, they are not tailored specifically for ambient intelligence and smart homes. This research aims to develop a specific ontology for these domains, building on existing generic ontologies and incorporating logical inference capabilities to assist people with reduced mobility and the elderly in carrying out their daily activities without constant assistance from others.

Research on ontology construction of traditional Chinese handmade paper: Take Kaihua paper as an example

Abstract Digital technology has broadened the research methods in the field of cultural heritage protection, and promoted the online organization and utilization of different resources. New digital technology is used to further explore the resources related to traditional Chinese handmade paper (TCHP) in order to comprehensively and systematically realize the knowledge association of different types of handmade paper. In this article, the characteristics of TCHP are combined to existing mature and generic ontologies to design a new ontology model of TCHP, and Protégé software is used to construct the visual ontology. The model is verified by analyzing the digital resources of Kaihua paper. Constructing the ontology of TCHP can realize the knowledge organization and visual presentation of related resources, and also promote the further utilization of the resources and wider spread of the culture of TCHP.

Learning resource recommendation via knowledge graphs and learning style clustering

An e-learning system should recommend learners appropriate learning resources according to their actual needs and cognitive status for improving their learning performance. To overcome the deficiencies of existing approaches (e.g., poor interpretability, limited efficiency and accuracy of recommendation), we propose a new recommendation approach to learning resources via knowledge graphs and learning style clustering. In this approach, the knowledge graphs of an online learning environment are constructed based on a generic ontology model, and the graph embedding algorithm and graph matching process are applied to optimize the efficiency of graph computation for identifying similar learning resources. By introducing learning style theory, learners are clustered based on their learning styles. Based on the clustering results, the learners’ degrees of interest in similar learning resources are measured, and the recommendation results are obtained according to the degrees of interest. Finally, the experiments demonstrate that the proposed approach significantly enhances the computational efficiency and the quality of learning resource recommendation compared with the existing approaches in large-scale graph data scenarios.

About a Fruitful Misunderstanding: From Souriau’s Modes of Existence to Latour’s Ecologizing Inquiries

This article examines the particular way Souriau’s concepts of instauration and modes of existence have been inherited by Bruno Latour in his Inquiry into Modes of Existence. It suggests that Bruno Latour has hacked some key-aspects of Souriau’s general ontology in order to regionalize it and, by doing so, to give the Moderns an accurate depiction of the plurality of beings they hold dear. It then shows how Souriau’s concept of instauration is crucial to Latour’s project of rethinking and repopulating modern institutions, in a gesture aimed at making metaphysics a vital practice that has the power to make the world worth of worrying and caring for.

Artificial Learning for Part Identification in Robotic Disassembly Through Automatic Rule Generation in an Ontology

With the increasing concern for sustainable treatment of waste electrical and electronic equipment (WEEE), methods of robotic disassembly of WEEE to address various challenges of handling end-of-life products has been a trend in research. The main challenge for robotic disassembly is the uncertainties of product structures, models, and conditions. The ability of a robotic disassembly system to learn new product structures and reason about existing knowledge of product structure is vital to addressing this challenge. This paper presents an effective learning framework and demonstrates the system’s ability to learn relevant information for the disassembly of LCD monitors. The learning algorithm uses a database of previous disassembly experience of the product family and analyses it to create rules and relations between the components and disassembly concepts before expanding the generic ontology for future disassembly runs. The results show a significant increase from 11% to 87% in successful part identification of LCD monitors after being trained on past disassembly experience. The proposed method can greatly aid robotic disassembly of any product family. Note to Practitioners—Robotic systems struggle to disassemble electronic waste due to the complexity and uncertainties in end-of-life products and variations in models and parts. An artificially intelligent method is proposed to enable a robotic disassembly system to address these uncertainties. The method uses a computing technique resembling the cognitive reasoning of a human mind in the form of a map of disassembly concepts connected by relationships. Artificial learning by the robotic system occurs by collecting data from previous disassembly runs of a product, analyzing the data, and expanding the map of knowledge with new concepts and relational rules found. The approach is tested on the robotic disassembly system’s ability to identify parts of LCD monitors which possess uncertainties. An improvement from 11% of successful part identification to 87% is found, which demonstrate that learning has taken place. This approach will be implemented in a larger robotic disassembly system and tested with real robotic disassembly runs in the near future.

Listen carefully to experts when you classify data: A generic data classification ontology encoded from regulations

Along with the proliferation of big data technology, organizations are involved in an overwhelming data ocean, the huge volume of data makes them at a loss in the face of frequent data breaches due to their failure of efficient data security management. Data classification has become a hot topic as a cornerstone of data protection especially in China in recent years, by categorizing information types and distinguishing protective measures at different classification levels. Both the text and tables of the promulgated data classification-related regulations (for simplicity, laws, regulations, policies, and standards are collectively referred to as “regulations”) contain a wealth of valuable information which can guide the work of data classification. To best assist data practitioners, in this paper, we automatically “grasp” expert experience on how to classify data from the analysis of such regulations. We design a framework, GENONTO, that automatically extracts data classification practices (DCPs), such as information types and their corresponding sensitive levels to construct an information type lexicon as well as to encode a generic ontology on top of 38 real-world regulations promulgated in China. GENONTO employs machine learning techniques and natural language processing (NLP) to parse unstructured text and tables. To our knowledge, GENONTO is the first work that explores critical information like the category and the sensitivity of information types from regulations, and organizes them in a structured form of ontology, characterizing the subsumptive relations between different information types. Our research helps provide a well-defined integrated view across regulations and bridges the gap between what experts say and how data practitioners do.

Possibilia, Qualia, and Sensibilia

In this article I shall first and foremost attempt to show that the semantic requirements of Wittgenstein’s Tractatus logico-philosophicus intend the objects of the Tractatus to be conceived of as possibilia in the Russellian sense of 1903, i.e., as objects that may exist or may not exist; secondly, that the general ontology of the Tractatus suggests integrating this onto-semantic conception with a conception of these objects not properly as qualia but as sensibilia in the Russellian sense of 1914, i.e., as sense-data that may exist or may not exist.

Жизненный цикл: смысловая матрица процессного моделирования

Acceleration of socio-technological changes increases demands and complexity of process modeling tasks. Developing the appropriate thinking skills is becoming a mass necessity. This paper describes a method for representation of pro- cesses, allowing systematization of such skill based on life cycle. Any process is then represented as a sequence of stag- es: perception, analysis, design, action, coordination, and evaluation. This sequence is formalized as a circular trajecto- ry on a phase space, the Cartesian axes of which are the activity and potency factors of classical semantics. As a result, the scheme receives a simple mathematical expression and is interfaced with standard methods of semantic measure- ments. The experimentally presented structure was revealed in the word2vec English language vector model, which additionally aligns it with machine learning and artificial intelligence algorithms. The developed model is considered as general ontology of processes in Nature, used in natural thinking as a stereotype of building cause-and-effect models of events. The result obtained opens up opportunities for the development of methods of process and causal-sense model- ing for scientific, technical and everyday purposes.

Dyskusja komplikacji generowanych przez koncepcję monadyzmu biologicznego Stanisława Ignacego Witkiewicza

The article focuses on Stanisław Ignacy Witkiewicz’s metaphysical concept, namely biological monadism. According to Witkacy, the Whole of Existence constitutes a multiplicity of monads – Particular Existences. It is them – occurring in various configurations – that constitute the substantive foundation of reality. The essential characteristic of these monads is their corporeal character, which means that Witkiewicz’s Particular Existence constitutes an original unity of the temporal (duration) and spatial (expanse) component; a unity finding expression in the statement that the monad is a corporeal consciousness and in the Whole of Existence there is no place for the objective existence of inanimate matter. The article exposes an important limitation of Witkiewicz’s metaphysics. It seems that the permanent presence of the Infinite in Witkacy’s General Ontology results in the indelible Mystery of Existence, which neutralizes the ultimate status of the why question. Being in Witkiewicz’s perspective becomes mysterious, enigmatic and senseless but, at the same time, it is deprived of any trace of randomness. In this way the structure of Being included in Witkiewicz’s monadic categorial network excludes the sense of the why question related to the Whole of Existence.

Ontology Generator

Abstract The paper proposes a simple method for constructing ontological theories—an ‘ontology generator’. It shows that such a generator manages to produce major existing ontological theories, e.g., Realism, Nominalism, Trope theory, Bundle theory, Perdurantism, Endurantism, Possibilism, Actualism and more. It thus turns out, surprisingly, that all these seemingly unrelated different ontological theories that were designed by thinkers hundreds of years apart, can all be generated using the same simple mechanism. Moreover, this same generator manages to produce entirely novel ontological theories, that fare no worse than existing ones in meeting the same common metaphysical challenges.

Construction of a Generic and Evolutive Wheel and Lexicon of Food Textures.

In the context of data management and processing, food science needs tools to organize the results of diverse studies to make the data reusable. In sensory analysis, there are no classification or wheel of textural attributes that can be used to interpret the results of sensory studies. Research from the literature and databases was used to elaborate a list of attributes related to texture. With the help of a group of experts in food texture, work on these attributes and the related concepts was conducted to classify them into several categories, including intensity levels. The classification was represented as a texture wheel, completed by a generic lexicon of definitions of texture concepts. The work can be useful as a reference in texture attributes related to foods, and thanks to implementation in a general ontology based on food processing and observation, it can help query and interpret texture-related results from sensory studies.

Baumgarten's Steps toward Spinozism

I argue that Baumgarten's rich and once influential Metaphysica contains an ontology that pushes him toward a Spinozistic conclusion, one that he fiercely sought to avoid. After examining Baumgarten's distinctive account of the core of Spinozism, I present his path as a series of independently motivated steps, focusing on his general ontology and his accounts of the world and God. Baumgarten himself would not be happy with these results, and I concede that some of his efforts to thwart Spinozism look promising. But there is one route to Spinozism that he fails to block, and at a key juncture, he inadvertently aids the Spinozist's cause. I conclude with an epilogue on how Baumgarten's path also foreshadows the next Spinozism flare-up heading into the German pantheism controversy.

Background knowledge in ontology matching: A survey

Ontology matching is an integral part for establishing semantic interoperability. One of the main challenges within the ontology matching operation is semantic heterogeneity, i.e. modeling differences between the two ontologies that are to be integrated. The semantics within most ontologies or schemas are, however, typically incomplete because they are designed within a certain context which is not explicitly modeled. Therefore, external background knowledge plays a major role in the task of (semi-) automated ontology and schema matching. In this survey, we introduce the reader to the general ontology matching problem. We review the background knowledge sources as well as the approaches applied to make use of external knowledge. Our survey covers all ontology matching systems that have been presented within the years 2004–2021 at a well-known ontology matching competition together with systematically selected publications in the research field. We present a classification system for external background knowledge, concept linking strategies, as well as for background knowledge exploitation approaches. We provide extensive examples and classify all ontology matching systems under review in a resource/strategy matrix obtained by coalescing the two classification systems. Lastly, we outline interesting and yet underexplored research directions of applying external knowledge within the ontology matching process.

An ontology-based, general-purpose and Industry 4.0-ready architecture for supporting the smart operator (Part I – Mixed reality case)

The advent of novel industry 4.0-driven technologies is offering significant opportunities to manufacturing systems, but at the same time it is posing new great challenges. The growing number of connected and interconnected devices is enormously increasing the amount of data generated, which must be properly organized to give value to the business. Basically, the need for approaches that are able to guarantee compliance with FAIR data principles is significantly emerging. Recently, the KNOW4I platform has been proposed in the literature to support the smart operator through a suite of Smart Utilities and Objects (Longo et al., 2022). The main purpose of this paper is to extend such platform, in the form of an ontology-based, general-purpose and industry 4.0-ready architecture, capable of improving the capabilities of the smart operator, with a focus on mixed reality. The novel proposal is based on two fundamental aspects: (1) a new general ontology, developed through the ontology engineering methodology; (2) the adoption of FIWARE, an open-source infrastructure, capable of enabling interoperability between different systems. The proposed architecture is implemented and validated on two case studies belonging to the manufacturing sector, which respectively concern (1) scheduled maintenance and alarm management and (2) customer order management. The experimental phase shows that the architecture is able to effectively and efficiently support the smart operator.

Social positioning theory and Dewey’s ontology of persons, objects and offices

ABSTRACT Social positioning theory, in defending a general social ontology, is a particular extension of critical realism. It is a theory of social constitution that clarifies how items including human beings and things are relationally organized as instances of community components. This extension of critical realism is directly comparable to fundamental but underexamined contributions of the classical American pragmatist John Dewey and specifically his elaboration of a social ontology incorporating an emphasis upon offices that individuals and things come to occupy. In this paper, it is argued that there are substantial correspondences between social positioning theory and Dewey’s concern with offices that come to be filled. By drawing on social positioning theory the significance of an overlooked feature of Dewey’s social ontology comes to be better appreciated. Equally by conducting this comparison Dewey’s discussion of offices is recognized as anticipating some of the insights that social positioning theory has recently systematised.