Ontology Schema Research Articles

Культура – знак – значение: о природе и структуре культуры и знака

The article examines the concept of culture as a paradigmatic structure that defines the variety of possible forms of social life, activity, and behavior in a certain community. It examines the structure and nature of the sign and its place in culture. The author sets this concept of culture and ideas about the structure of the sign, starting from some of F. Saussure’s ideas. He accepts Saussure’s distinction between language and speech within “linguistic activity”, but in the language itself he also distinguishes two areas of existence: language as a paradigmatic structure of a single subject and language as a paradigmatic system existing at the community level. As a result, the author sees not two, but three areas of manifestation in “language activity”. He identifies similar three areas in any semiotic activity and in activity in general. At the same time, in the course of generalization in the series “linguistic activity – sign activity – activity”, the social paradigmatic aspect of these activities is also generalized from language to the sign system and culture as a whole. Since language in public form, and language in individual form, and speech have the word as a basic structural unit, then we can talk about three ontological forms (modi) of the word: in public language, in individual language, in speech. The author identifies similar three ontological modi for an arbitrary sign. Taking as a basis the binary structure of an abstract sign (the plan of expression and the plan of content associated with each other) and the idea of the three ontological modi of the sign, we obtain a triangular prism as an ontological scheme of the sign, where the nodes of the prism correspond to various aspects of the sign, three vertical edges – three ontological modi of the sign, the upper face – the plan of expression (syntax), the bottom face – the plan of content (semantics). Based on the obtained ontological scheme of the sign, the author interprets the semiotic representations of some alternative research programs

Ontology learning from object-relational mapping metadata and relational database

Ontologies play an important role in representing the semantics of data sources. Building an ontology as a representation of domain knowledge from available data sources is not a simple process, particularly when dealing with relational data, which remains prevalent in existing knowledge systems. In this study, we create an ontology from a relational database using object-relational mapping (ORM) metadata as additional rules for mapping. Our method comprises two main phases: ontology schema construction using ORM metadata and the generation of ontology instances from the relational database. During the initial phase, we analyzed the ORM metadata to map it to an resource description framework schema (RDF(S))-OWL representation of the ontology. In the subsequent phase, we applied mapping rules to convert the relational database (RDB) data into ontological instances, which are then represented as RDF triples. Using ORM metadata, we enhance the accuracy of the resulting ontology, particularly in terms of extracting concepts and hierarchical relationships. This study contributes to the field of ontology learning by showcasing a novel approach that leverages ORM metadata to create ontologies from relational databases.

Key Components of the Ontological Scheme of the World in “Mathematical Principles of Natural Philosophy”

The author presents a version of the ontological scheme of Newton’s mechanistic worldview based on both the study of previous versions of its understanding and the text of the “Mathematical Principles of Natural Philosophy”. Newton developed a model of new universality or a homogeneous and isotropic world in which uniform laws operate. This model is based on several ontological postulates Newton introduced, which can be isolated from several provisions of his classic work. The new mechanistic worldview is based on the imputation of the world of universal simplicity. The quantitative “unit” of a simple, homogeneous, physical-geometric universe is an ambivalent corpuscle-point. The main constants of the “mechanistic universe” are the diversity of the numbers of masses, motions, and forces connected by clear reciprocal relationships. Newton also introduced theoretical space and time as a privileged, absolute reference system. Finally, in the Newtonian version of the mechanistic worldview, there are compelled metaphysical ingredients or inexplicable and transcendental qualities. They are gravity, ether, and God. Thus, the ontological scheme of Newton’s mechanistic worldview is a construction based on the sequential mental experiment of presenting the universe exclusively from the side of its “objectivity” and “sensory certification”.

Enterprise data and semantic modelling: conceptual model of information technology incident management

Knowledge management methods and their efficient implementation across the organization determine sound and resilient management of processes. This paper studies the semantic integration of enterprise data sources essential to service management processes. Implementing a semantic layer within the enterprise architecture uses various tools, methods, and techniques. The semantic conceptual model unifies and implements intelligent integration of multiple data sources across the enterprise, achieving consistency and more accessible interpretation. Specifically, we draw our attention to incident and problem management within enterprises. We propose an ontology - a conceptual model for the incident management process. The incident ontology presented as an intelligent data integration layer component aims to achieve operational excellence. Besides, this ontology is a fundamental part of the proactive process in problem management. An ontology as a logic-based system supports integrity validation. It infers new, no explicitly modeled facts in the problem domain, thus helping experts better analyze and understand the problem. We discuss the conducted experiment results with the proposed in this article conceptual model using the enterprise knowledge graph platform. It can be perceived as a framework for a query-answering system with components, including ontology schema, data mapping, and classification methods for data graph enrichment.

Advanced file carving: ontology, models and methods

File carving techniques are important in the field of digital forensics. At the same time, the rapid growth in the amount and types of data requires the development of file carving methods in terms of capabilities, accuracy, and computational efficiency. However, most of the methods are developed to solve specific tasks and are based on a certain set of assumptions and a priori knowledge about the files to be recovered. There is a lack of research that systematizes methods and structures approaches to identify gaps and determine perspective directions for development, considering the latest advances in information technology and artificial intelligence. The subject matter of this article is the structure, factors, efficiency criteria, methods, and tools of file carving, as well as the current state and tendencies of development of file carving methods. The goal of this study is to systematize knowledge about advanced file carving methods and identify perspective directions for their development. The tasks to be solved are as follows: to identify the main stages of file carving and analyze approaches to their implementation; to build an ontological scheme of file carving; and to identify perspective directions for the development of carving methods. The methods used were literature review, systematization, and summarization. The obtained results are as follows. An ontological scheme for the file carving concept is constructed. The scheme includes the principles, properties, phases, techniques, evaluation criteria, tools used, and factors influencing file carving. The features, limitations, and fields of application of the data recovery methods are provided. It was established that the most widespread approach to file reconstruction is still a manually detailed analysis of the internal structure of files and/or their contents, identifying specific patterns that allow reassembling the sequence of data fragments in the correct order. However, most of the methods do not provide one hundred percent guaranteed results. This article analyzes the current state and prospects of using artificial intelligence methods in the field of digital forensics, particularly for identifying data blocks, clustering, and reconstructing files, as well as restoring the contents of media files with damaged or lost headers. The necessity of having priori information about the file structure or content for successfully carving fragmented data is determined. Conclusions. The scientific novelty of the obtained results is as follows: for the first time, advanced file carving methods are systematized and analyzed by directions of development and the perspectives of using artificial intelligence for identifying data blocks, clustering, and file content restoration; for the first time, an ontological scheme of file carving is constructed, which can be used as a roadmap for developing new advanced systems in the digital forensics field.

OERL: Enhanced Representation Learning via Open Knowledge Graphs

The sparseness and incompleteness of knowledge graphs (KGs) trigger considerable interest in enhancing the representation learning with external corpora. However, the difficulty of aligning entities and relations with external corpora leads to inferior performance improvement. Open knowledge graphs (OKGs) consist of entity-mentions and relation-mentions that are represented by noncanonicalized freeform phrases, which generally do not rely on the specification of ontology schema. The roughness of the nonontological construction method leads to a specific characteristic of OKGs: diversity, where multiple entity-mentions (or relation-mentions) have the same meaning but different expressions. The diversity of OKGs can provide potential textual and structural features for the representation learning of KGs. We speculate that leveraging OKGs to enhance the representation learning of KGs can be more effective than using pure text or pure structure corpora. In this paper, we propose a new <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">OERL</b> , <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">O</b> pen knowledge graph <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</b> nhanced <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</b> epresentation <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</b> earning of KGs. OERL automatically extracts textual and structural connections between KGs and OKGs, models and transfers refined profitable features to enhance the representation learning of KGs. The strong performance improvement and exhaustive experimental analysis prove the superiority of OERL over state-of-the-art baselines.

Painting and Ontology: D. H. Lawrence as an Art Historian

More than any other twentieth-century writer, D. H. Lawrence developed a profound understanding of painting and evaluated this art form through the prism of his idiosyncratic ontological scheme. In allegiance to his polaristic philosophy, in which everything is created by the opposition of static and dynamic, mind and body, optical and tactile, “Will-to-Motion” and “Will-to- Inertia,” light and darkness, Lawrence conceived the history of visual arts as a mirror of this universal opposition of ultimate metaphysical forces. Despite his general view that Western art was entirely under the dominion of idea, mind, and light, Lawrence pointed to several examples in which dark, bodily, and haptic experiences were processed pictorially. This essay intends to introduce Lawrence as an art historian who understood works of art and art historical periods as constituted out of a never-ending power struggle between the corporeal and the spiritual, and who always sought and called for their reconciliation and balance in his literature.

Maintenance planning recommendation of complex industrial equipment based on knowledge graph and graph neural network

Maintenance planning is a significant part of predictive maintenance, which involves task planning, resource scheduling, and prevention. With large-scale sensor systems in modern factories, much data will be captured during monitoring and maintenance of complex industrial equipment. Accumulated data facilitates maintenance planning becomes more thorough and timely. Recently, a knowledge graph (KG) was offered to handle large-scale, unorganized maintenance data semantically, resulting in better data usage. Some prior studies have utilized KG for maintenance planning with semantic searching or graph structure-based algorithms, nevertheless neglecting the prediction of potential linkage. To fill this gap, a maintenance-oriented KG is established firstly based on a well-defined domain-specific ontology schema and accumulated maintenance data. Then, an Attention-Based Compressed Relational Graph Convolutional Network is proposed to predict potential solutions and explain fault in maintenance tasks. Lastly, a maintenance case of oil drilling equipment is carried out, where the proposed model is compared with other cutting-edge models to demonstrate its effectiveness in link prediction. This research is anticipated to shed light on future adoption of KG in maintenance planning recommendations.

Brain Data Standards - A method for building data-driven cell-type ontologies

Large-scale single-cell ‘omics profiling is being used to define a complete catalogue of brain cell types, something that traditional methods struggle with due to the diversity and complexity of the brain. But this poses a problem: How do we organise such a catalogue - providing a standard way to refer to the cell types discovered, linking their classification and properties to supporting data? Cell ontologies provide a partial solution to these problems, but no existing ontology schemas support the definition of cell types by direct reference to supporting data, classification of cell types using classifications derived directly from data, or links from cell types to marker sets along with confidence scores. Here we describe a generally applicable schema that solves these problems and its application in a semi-automated pipeline to build a data-linked extension to the Cell Ontology representing cell types in the Primary Motor Cortex of humans, mice and marmosets. The methods and resulting ontology are designed to be scalable and applicable to similar whole-brain atlases currently in preparation.

The Construction of Knowledge Graphs in the Aviation Assembly Domain Based on a Joint Knowledge Extraction Model

The aviation assembly domain, which is a complex system, involves the multi-dimensional information of parts, processes, tools, plants and operation projects. In order to assist the knowledge management from natural language text in the aircraft manufacturing process, this paper proposes the corresponding ontology scheme and the joint knowledge extraction model, which is necessary for construct the knowledge graph in the aviation assembly domain. The model is able to automated end-to-end construct knowledge graph. The proposed model, which is based on reinforcement learning approach and a novel labeling scheme, takes the constraint relationships between entities and relations as an important identification basis. The model does not rely on manual feature setting, while it greatly reduces the training cost. The proposed joint knowledge extraction model was testified from the practical scenarios of the general assembly and component assembly. The experimental results showed that the proposed model showed an excellent performance in the aviation assembly domain, with the F1-score of 89.71% for entities, the F1-score of 91.27% for relations, and the overall average F1-score of 82.41%. Based on the superior performance of the model, the knowledge graph of the general assembly and component assembly, which included 1, 308 pairs of triples composed of five kinds of entities and three kinds of relations, was further constructed in the aviation assembly domain.

Первоисточники учения о стадиальности Пути в индо-тибетской Махаяне

The Mahāyāna concept of gradual Dharma teaching, learning and staged realization of the Path of Enlightenment in Tibet was developed by Tsongkhapa and others as a practical guide to the stages of the Path (Lamrim). However, Lamrim is not a Tibetan teaching and expresses a more general concept of gradualness, which has an Indo-Buddhist origin. The article is to present the system of Indian primary sources of this concept. The novelty of the approach is due to the fact that the authors consider the “internal” position in the systematization and classification of the teachings of the Buddha, presented by the Madhyamikas, especially the reformer of Tibetan Buddhism, Je Tsongkhapa, to be a very significant factor in the reconstruction of the Mahāyāna concept of gradualness. The authors come to conclusions also containing novelty. First, the concept of the "Three Turns of the Wheel of the Teaching" formulated in the “Samdhinirmochana Sūtra” is the first hermeneutical scheme for ordering and classifying the many teachings of the Buddha. It was based on the principle of gradual assimilation of the ontology of emptiness by students. Within this gradualism conceptualization scheme, based on the philosophical (ontological) criteria for classifying the teachings of the Buddha, the Prajnaparamita Sūtras are the root source of the concept of gradualness. Secondly, the Mahāyāna concept of gradualness has both explicit and implicit aspects. The explicit aspect is represented by those Prajnaparamita Sūtras, in which the main subject is the doctrine of emptiness and contains the substantiation of the gradualness of the Path, depending on the depth of comprehension of emptiness and selflessness. This aspect of the Prajnaparamita is presented in Nāgārjuna's six treatises on the Madhyamaka. Chandrakirti revealed the connection of the deep view with the stages of the Path of the Bodhisattvas. Thirdly, along with the ontological scheme for substantiating gradualness, the Indian primary sources also present practical schemes for the gradual systematization of the Buddha's teachings: the concept of three chariots ("Lotus Sūtra"), as well as the doctrine of bhūmi ("Yogācārabhūmi" by Asanga) and six (ten ) paramitās ("Bodhicharyāvatāra" by Śantideva). This article is part of a larger study of the sources of the Mahāyāna concept of gradualness. Results of this analysis are significant for the correct source systematization of Buddhist doctrines and practices.

Cultural information bubbles: A new approach for automatic ethical evaluation of digital artwork collections based on Wikidata

Abstract Large digital repositories created and maintained by art museums provide open access to millions of works of art and make them available to new audiences with diverse backgrounds, views, and needs. Digitization of cultural collections by art museums has opened an opportunity to correct the historical injustices and imbalances in information representation. The first step toward this goal is a systematic critical evaluation of digital cultural collections from an ethical perspective. In this study, we propose and apply a new automated methodology for evaluation of digital cultural collections, based on a recently proposed ethical framework for evaluation of knowledge organization systems. The developed approach utilizes Wikidata for automatic creation of a unified ontological scheme comprised of ethically marked properties of cultural heritage items. These properties are used to automatically measure and compare the compliance of a database with a set of ethical criteria, on a large scale, in a database-agnostic manner. The findings, based on two prominent art museums—the Metropolitan Museum of Art and the Rijksmuseum—as well as the Wikidata artwork collection, indicate the presence of biases and a Western cultural information bubble. The Met artwork database’s scores are relatively close to Wikidata and more inclusive and balanced than those of the Rijksmuseum.

Multi-task learning with graph attention networks for multi-domain task-oriented dialogue systems

A task-oriented dialogue system (TOD) is an important application of artificial intelligence. In the past few years, works on multi-domain TODs have attracted increased research attention and have seen much progress. A main challenge of such dialogue systems is finding ways to deal with cross-domain slot sharing and dialogue act temporal planning. However, existing studies seldom consider the models’ reasoning ability over the dialogue history; moreover, existing methods overlook the structure information of the ontology schema, which makes them inadequate for handling multi-domain TODs. In this paper, we present a multi-task learning framework equipped with graph attention networks (GATs) to probe the above two challenges. In the method, we explore a dialogue state GAT consisting of a dialogue context subgraph and an ontology schema subgraph to alleviate the cross-domain slot sharing issue. We further construct a GAT-enhanced memory network using the updated nodes in the ontology subgraph to filter out the irrelevant nodes to acquire the needed dialogue states. For dialogue act temporal planning, a similar GAT and corresponding memory network are proposed to obtain fine-grained dialogue act representation. Moreover, we design an entity detection task to improve the capability of soft gate, which determines whether the generated tokens are from the vocabulary or knowledge base. In the training phase, four training tasks are combined and optimized simultaneously to facilitate the response generation process. The experimental results for automatic and human evaluations show that the proposed model achieves superior results compared to the state-of-the-art models on the MultiWOZ 2.0 and MultiWOZ 2.1 datasets.

Categorical Preference of the Mind

Fundamental to the traditional, Cognitive Science of Religion (CSR) mind-based model is that the human mind perceives the world through the use of ontological categories. These categories are often defined as templates, which are associated with the recognition of basic ontological categories organized hierarchically due to evolutionarily sourced strategic connections: PERSON &gt; ANIMAL &gt; PLANT &gt; ARTIFACT &gt; OBJECT. If the field of CSR is to use such foundational concepts as MCIs, ontological categories, socially strategic and inference generation, we must first test and verify that this hierarchical ontological schema is in fact valid, especially given some recent shifts away from the mind-based model. The goal of this study was to analyze participant preferences for different aspects of the CSR mind-based model, such as template categories and socially strategic inferences. To test this, participants saw four conditions, each with a variety of images that reflected these categories and inferences. Main findings saw no preference between hypothesized template categories, preference for socially strategic images within the same category, and preference for non-threatening images over threatening images of the same category. The latter two findings (socially strategic; threat avoidance) confirm core theories and recent work in CSR; the former finding (no hierarchy preference) calls into question the nature and use of ontological categories.

What do they make us see: a comparative study of cultural bias in online databases of two large museums

PurposeLarge cultural heritage datasets from museum collections tend to be biased and demonstrate omissions that result from a series of decisions at various stages of the collection construction. The purpose of this study is to apply a set of ethical criteria to compare the level of bias of six online databases produced by two major art museums, identifying the most biased and the least biased databases.Design/methodology/approachAt the first stage, the relevant data have been automatically extracted from all six databases and mapped to a unified ontological scheme based on Wikidata. Then, the authors applied ethical criteria to the results of the geographical distribution of records provided by two major art museums as online databases accessed via museums' websites, API datasets and datasets submitted to Wikidata.FindingsThe authors show that the museums use different artworks in each of its online databases and each data-base has different types of bias reflected by the study variables, such as artworks' country of origin or the creator's nationality. For most variables, the database behind the online search system on the museum's website is more balanced and ethical than the API dataset and Wikidata databases of the two museums.Originality/valueBy applying ethical criteria to the analysis of cultural bias in various museum databases aimed at different audiences including end users, researchers and commercial institutions, this paper shows the importance of explicating bias and maintaining integrity in cultural heritage representation through different channels that potentially have high impact on how culture is perceived, disseminated, contextualized and transformed.

As Data Flows Surge Data Infrastructure Groans

As Data Flows Surge Data Infrastructure Groans

A unified ontology-based data integration approach for the internet of things

&lt;span lang="EN-US"&gt;Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additional semantic layer for cloud-based IoT platforms to build a schema for data generated from diverse sources. We tested the proposed model on real data consisting of approximately 160,000 readings from various sources in different formats like CSV, JSON, raw data, and XML. The data were collected through the file transfer protocol (FTP) and generated 960,000 resource description framework (RDF) triples. We evaluated the proposed approach by running different queries on different machines on SPARQL protocol and RDF query language (SPARQL) endpoints to check query processing time, validation of integration, and performance of the unified ontology model. The average response time for query execution on generated RDF triples on the three servers were approximately 0.144 seconds, 0.070 seconds, 0.062 seconds, respectively.&lt;/span&gt;

Ontology specific visual canvas generation to facilitate sense-making-an algorithmic approach

Ontologies are domain-specific conceptualizations that are both human and machine-readable. Due to this remarkable attribute of ontologies, its applications are not limited to computing domains. Banking, medicine, agriculture, and law are a few of the non-computing domains, where ontologies are being used very effectively. When creating ontologies for non-computing domains, involvement of the non-computing domain specialists like bankers, lawyers, farmers become very vital. Hence, they are not semantic specialists, particularly designed visualization assistance is required for the ontology schema verifications and sense-making. Existing visualization methods are not fine-tuned for non-technical domain specialists and there are lots of complexities. In this research, a novel algorithm capable of generating domain specialists’ friendlier visualization canvas has been explored. This proposed algorithm and the visualization canvas has been tested for three different domains and overall success of 85% has been yielded.

Some reflections on principles of Isthmo-Colombian Amerindian ontologies

The search for ontological principles specifi c for the Isthmo-Colombian region developed slowly during the last decade and started from ethnographic data and anthropological experiences which diverge in specifi c ways from the ideal-typical ontological notions of animism or analogism. Th e paper present refl ections on a set of ontological principles, which – based on the current state of analysis – allow to characterize a variety of Isthmo-Colombian socio-cosmologies in non-essentialist terms and in delineation to Amazonian animism, which became used as interpretative frame also for contemporary indigenous groups further north. Th us, rather than proposing the existence of a specifi c and rigid Isthmo-Colombian ontology I will try to summarize a number of basic principles along which local socio-cosmologies diff er from the great ontological schemes like animism and analogism. By making some ontological links between the Isthmo- Colombian area and Mesoamerica visible the paper invites to rethink local principles in ontological terms, while avoiding the imposition of theoretically attractive, but only partially fi tting ontological schemata, which may cause selective misreadings and biased interpretations of local ontological principles.

How universal generalization works according to natural reason

Universal Generalization, if it is not the most poorly understood inference rule in natural deduction, then it is the least well explained or justified. The inference rule is, prima facie, quite ambitious: on the basis of a fact established of one thing, I may infer that the fact holds of every thing in the class to which the one belongs—a class which may contain indefinitely many things. How can such an inference be made with any confidence as to its validity or ability to preserve truth from premise to conclusion? My goal in this paper is to explain how Universal Generalization works in a way that makes sense of its ability to preserve truth. In doing so, I shall review common accounts of Universal Generalization and explain why they are inadequate or are explanatorily unsatisfying. Happily, my account makes no ontological or epistemological presumptions and therefore should be compatible with whichever ontological or epistemological schemes the reader prefers.