Ontology Language Research Articles

Efficient Composition Algorithm Strategies on Semantic Web Services Using Nature Inspired Approach

Web services are used all around the world for commercial purposes. It works majorly by Universal Resource Locators, which are stored in the repository UDDI. The different web service has to be composed for creating new business services. It is time dependent for composing more web services, which is massive. A semantically described WSDL description solves automatic composition of web services. Also with ontological models and languages, such as RDF, OWL, and SWRL, the better automatic discovery, selecting, integration, and composition of services have been done. Service requirements, such as connectivity, quality-of-service properties, correctness, and scalability, need to be satisfied. For achieving these, many evolutionary algorithms will be used for improving quality of service parameters. This paper describes many optimizations algorithms which will be used efficiently in optimizing composition techniques in semantic web.

The Malware Detection Approach in the Design of Mobile Applications

Background: security has become a major concern for smartphone users in line with the increasing use of mobile applications, which can be downloaded from unofficial sources. These applications make users vulnerable to penetration and viruses. Malicious software (malware) is unwanted software that is frequently used by cybercriminals to launch cyber-attacks. Therefore, the motive of the research was to detect malware early before infection by discovering it at the application-design level and not at the code level, where the virus will have already damaged the system. Methods: in this article, we proposed a malware detection method at the design level based on reverse engineering, the unified modeling language (UML) environment, and the web ontology language (OWL). The proposed method detected “Data_Send_Trojan” malware by designing a UML model that simulated the structure of the malware. Then, by generating the ontology of the model, and using RDF query language (SPARQL) to create certain queries, the malware was correctly detected. In addition, we proposed a new classification of malware that was suitable for design detection. Results: the proposed method detected Trojan malware that appeared 552 times in a sample of 600 infected android application packages (APK). The experimental results showed a good performance in detecting malware at the design level with precision and recall of 92% and 91%, respectively. As the dataset increased, the accuracy of detection increased significantly, which made this methodology promising.

An Effective Resource Matching Scheme Based on a Novel Unified Descriptive Model for Modern Manufacturing Industry Systems

In order to effectively solve the problem of heterogeneous design/manufacturing/service resources and isolation in the whole lifecycle and realize unified description of design/manufacturing/service resources and resource sharing across subjects and stages, this paper proposes a hierarchical and modularized ontology-based resource-unified descriptive model, according to the characteristics of design/manufacturing/service resources. We analyze all kinds of properties of the resources, design a specific descriptive model of ontology, function, and service, ensure the consistency and independence of resource descriptions, and use the OWL (Web Ontology Language) ontology descriptive language and Protégé tools to verify. Then, based on the unified descriptive model, a resource matching method based on multi-level tags is proposed, which matches the task request with the resources in the resource library, selects the resources that meet the task request, and guarantees the resource sharing across subjects and stages. The resource matching work first performs task description and decomposition, and uses information entropy and rough set theory to sort the importance of subtasks, then uses the semantic similarity algorithm to complete multi-level tags’ matching. Finally, two examples are used to prove the feasibility and effectiveness of the experiment.

The Interactive Method for Language Science and Some Salient Results

The use of information technology in linguistic research gave rise in the 1950s to what is known as Natural Language Processing, but that framework was created without paying due attention to the need for logical reconstruction of linguistic concepts which were borrowed directly from barely (or even not at all) formalised structural linguistics. The Computer-aided Acquisition of Semantic Knowledge project (CASK) based on the Knowledge Discovery in Databases technology (KDD) enabled us to interact with computers while gathering and improving our knowledge about languages.
 Thus, with the help of data mining tools, as a result of revisiting two sorts of generally admitted linguistic theories (the Predicate Argument Structure theory and Information Structure theory), we succeeded in improving these local linguistic approaches by proposing to unify the Associative Semantics (AS) theory (in which we introduced the concept of ortho-information) with the Meta-Informative Centering (MIC) theory (in which we described the meta-informative layer of natural languages). The resulting Distributed Grammar (DG) program (sketched out in this paper) treats, in addition to the above types of information, the third one, para-information (concerning identity and alikeness with respect to context and language ontology) which – despite many studies – had no uniform theoretical background in general linguistics. This DG program aims to lay the foundations for creating the theoretical background of Conceptual Linguistics.

An adaptive deep learning model towards fault diagnosis of hydraulic piston pump using pressure signal

Hydraulic pump is a critical component of a hydraulic transmission system. Its normal and stable operation will directly affect the reliability of the whole system. Owing to the complexity and concealment of fault information, it is crucial to explore an effective method for fault diagnosis of hydraulic piston pump. The obvious change of vibration signal can be observed when different fault types occur, and the implied characteristics of pressure signals are also varying. In this research, an adaptive convolutional neural network (CNN) is constructed based on the ontology representation of pump. First, time–frequency characteristics of pressure signals are obtained via continuous wavelet transform. Second, a deep CNN is established by setting initial hyperparameters. Third, Bayesian optimization is employed to achieve automatic learning of main important hyperparameters to construct an adaptive CNN. The proposed method has better performance for fault diagnosis of hydraulic piston pump compared with other modern intelligent methods.

On the ontology of language: A critique of trait theory

In this article, we present a comparative analysis of the ontological assumptions about language at play within structural linguistics and trait theory. The ontological discussions demonstrate a fundamental incongruence between trait theory’s aim of description and its assumptions about language. This discussion guides a broader analysis of the structuring effect of the ontology of language within the study of subjectivity. We also develop the proposition that an integrative reading of structural linguistics and the phenomenology of speaking can be a constructive way to think coherently about language as system and language as subjectivity by insisting on speech as corporeal intention and reference and, thereby, lived.

Novel approach for semantic similarity cross ontology

Measuring <span>semantic similarity between terms is a crucial step in information retrieval and integration since it necessitates semantic content matching. Even though several models have been proposed to measure semantic similarity, these models are not able to effectively quantify the weight of relevant items that affect the semantic similarity judgment process. In this study, we present a new method for measuring semantic similarity between cross-ontologies, that consists of hybridizing node-based approaches such as WuP and Reda with the weight of similarity computed using WordNet. The proposed approach has been experimented to show its efficiency with two ontologies, configuration management tool (CMT) and ConfOf, from the conference domaine in the web ontology language (OWL) ontologies benchmark OAEI 2015 and evaluated using two metrics: density and cohesion.</span>

Henri Lefebvre's conception of nature-society in the revolutionary project of autogestion

Henri Lefebvre's intricate material-dialectical approach to the nature-society problematic, taken together with his advocacy of a praxis oriented to total transformation from the ground up through autogestion, offers a unified, critical, and dialectical approach to political ecology. Unfortunately, his work in these areas has too often been interpreted as divided and fragmentary, splitting his radical analysis of the production of space-time from his critical praxis related to autogestion. We offer a corrective to this by elaborating briefly on his use of Marx's material-dialectical approach, outlining how Lefebvre brings this method to bear on the nature-society problematic, and how his theorization of autogestion points to a radical praxis aimed at overcoming the social-ecological contradictions of capital. His engagement with Marx's theory of metabolic rift, and his advocacy of a radical project of autogestion as part of the critique of everyday life, serve to place the underlying issue of alienation in spatial terms, offering geography a transformative perspective that avoids positing closed systems and attempting to exhaust the various meanings assigned to nature. In this, Lefebvre demonstrates how the nature-society problematic overflows issues of ontological framing and language, calling for a unity of radical theory and practice to overcome the separations.

The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development

BackgroundOntologies of precisely defined, controlled vocabularies are essential to curate the results of biological experiments such that the data are machine searchable, can be computationally analyzed, and are interoperable across the biomedical research continuum. There is also an increasing need for methods to interrelate phenotypic data easily and accurately from experiments in animal models with human development and disease.ResultsHere we present the Xenopus phenotype ontology (XPO) to annotate phenotypic data from experiments in Xenopus, one of the major vertebrate model organisms used to study gene function in development and disease. The XPO implements design patterns from the Unified Phenotype Ontology (uPheno), and the principles outlined by the Open Biological and Biomedical Ontologies (OBO Foundry) to maximize interoperability with other species and facilitate ongoing ontology management. Constructed in Web Ontology Language (OWL) the XPO combines the existing uPheno library of ontology design patterns with additional terms from the Xenopus Anatomy Ontology (XAO), the Phenotype and Trait Ontology (PATO) and the Gene Ontology (GO). The integration of these different ontologies into the XPO enables rich phenotypic curation, whilst the uPheno bridging axioms allows phenotypic data from Xenopus experiments to be related to phenotype data from other model organisms and human disease. Moreover, the simple post-composed uPheno design patterns facilitate ongoing XPO development as the generation of new terms and classes of terms can be substantially automated.ConclusionsThe XPO serves as an example of current best practices to help overcome many of the inherent challenges in harmonizing phenotype data between different species. The XPO currently consists of approximately 22,000 terms and is being used to curate phenotypes by Xenbase, the Xenopus Model Organism Knowledgebase, forming a standardized corpus of genotype–phenotype data that can be directly related to other uPheno compliant resources.

ViLO — A Core Ontology of Vietnamese Legal Documents

Legal ontologies play a key role in various legal applications and have been broadly used by many stakeholders. Innovative systems and ontologies in the law hold potential to conduct legal research. With the needs for legal information management in smart applications, especially for Vietnamese law, it is vitally important to construct core legal ontologies for knowledge representation. This study proposes a core ontology for Vietnamese legal documents which covers general legal domain called as ViLO. The ViLO ontology mainly consists of related institutions of Vietnamese political system, types and structures of legal documents. The method of the NeOn-based collaborations among domain experts and ontology engineers was conducted to build up the ViLO ontology. Through FOCA-based validation results, the proposed method was shown to be effective and efficient. The resulting ontology was demonstrated to be reliable and enriched. The ViLO ontology is supposed to be a basis for further constructions of domain ontologies and artificial intelligence applications in Vietnamese law.

A multiplatform reasoning engine for the Semantic Web of Everything

The Internet of Everything and Semantic Web can be joined by giving more intelligence to pervasive systems. To that end, reasoning capabilities should be enabled even for very resource-constrained embedded devices. This paper presents Tiny-ME (the Tiny Matchmaking Engine), a matchmaking and reasoning engine for the Web Ontology Language (OWL), designed and implemented with a compact and portable C core. Main features are high resource efficiency and multiplatform support, spanning containerized microservices, desktops, mobile devices, and embedded boards. The OWLlink interface has been extended to enable non-standard reasoning services for matchmaking in Web, Cloud, and Edge computing. A prototype evaluation is proposed, including a case study on the Pixhawk Unmanned Aerial Vehicle (UAV) autopilot and performance highlights.

Identifying Adversaries’ Signatures Using Knowledge Representations of Cyberattack Techniques on Cloud Infrastructure

Advanced Persistent Threats (APTs) have increased in parallel to growing cloud infrastructure and cloud Software-as-a-Service (SaaS) needs, exposing new vulnerabilities within the cloud environment. Moreover, APT groups are becoming more sophisticated and organised which needs to be addressed by the research community to enable faster response and more importantly, prevent threats within the domain. The MITRE ATT&CK Cloud framework offers one of the leading structured inventories within this context. Our research is to expose patterns and signatures of a select group of APT’s on the MITRE Cloud Framework by using Formal Concept Analysis (FCA) to construct a “lattice graph” and an ontology. The goal is to develop a better conceptualisation of the MITRE ATT&CK Cloud Matrix framework for cyber security experts to be able to proactively act upon adversary techniques. The MITRE ATT&CK framework was retrieved, cleaned, and pre-processed to construct the lattice and ontology using data cleaning methods, FCA tools such as Concept Explorer, and the Web Ontology Language (OWL), with additional symbolic reasoning and inference generation. This resulted in knowledge representations/graphs, which are highly efficient representations of this knowledge field. The underlying linkages between techniques and targets specific to those APTs are further exposed and enriched and presented visually and integrated into the ontology. The ontology gives formalisation to associations and implications between techniques, tactics, and APTs – enabling cyber security practitioners to forecast potential targets and techniques based on their scenario, but also to attribute certain technique patterns and signatures to individual APTs. Cyber security practitioners can query from this knowledge graph and formulate strategic proactive measures. From these findings, the applications and constraints of the APTs’ cyber-attack techniques and their associated patterns were determined. The findings provide a guideline for future additional research in the field of AI knowledge representation in cybersecurity, as well as highlighting certain limitations in this field of research.

193 Arachnoid Cysts as Genetically-encoded Harbingers of Neurodevelopmental Pathology

INTRODUCTION: Arachnoid cysts (ACs) are the most common congenital intracranial lesions. While familial cases implicate genetic factors, their ultimate cause remains unknown. Herein, we describe a multi-omics approach to disease state characterization including traditional whole exome sequencing, integrative genomics with analytics of large bulk-RNA and single cell RNA sequencing (scRNAseq) data, and a novel phenomics technique using natural language processing and Human Phenotypic Ontological (HPO) language clustering. METHODS: Whole exome sequencing was performed on 1560 individuals (520 parent-offspring "trios"). Genes with likely pathogenic mutations were defined as those with >1 de novo variant (DNV) reaching threshold for exome-wide significance (p<2.5 x 10-6) and having high pLI score (>0.9). This high-confidence pathogenic gene set and a secondary probable pathogenic gene set (>1 DNV, regardless of exome-wide significance or pLI score) were analyzed in bulk-RNA and scRNAseq datasets to assess spatiotemporal and cell-type relationships of gene expression. Phenomic analysis was conducted by subjecting patient medical records to a natural-language-processing (NLP) algorithm. Phenotypes were catalogued with the Human Phenotype Ontology (HPO) language tree and mapped with uniform manifold approximation and projection (UMAP) clustering. RESULTS: 7 genes reached our pathogenic threshold, ADNP, ARIDB1, KDM5C, PURA, FOXP1, MAP2K1, and SCN2A. Strikingly, all but SCN2A play critical roles in epigenetic regulation of gene expression in the developing brain. Bulk-RNA datasets reveal that these genes converge in networks essential for chromatin remodeling and mRNA processing. scRNAseq datasets revealed an association with excitatory and inter-neurons known to play a role in developmental delay. HPO clustering revealed four major phenotypic clusters defined by neurodevelopmental delay (NDD), seizures, both or asymptomatic. In a subgroup of traditionally phenotyped patients, there was statistically significant enrichment of neuraxial phenotypes - including NDD - among those harboring DNVs. CONCLUSION: This novel association between ACs and multiple epigenetic regulators of gene expression provides the first insight into intracranial AC pathobiology. HPO clustering reveals clinically relevant subsets of ACs and implies that traditionally symptomatic or asymptomatic ACs may be harbingers of genetically-driven aberrant neurodevelopment.

Використання систем організації знань на основі онтологій у WIKI-ресурсах

The paper considers the theoretical foundations of knowledge organization systems (KOSs) in intelligent ontology-based applications. The aim of this study is to analyze the use of different types of KOSs to organize and improve the knowledge base of semantic Wiki resources that contain heterogeneous multimedia content of large volume and have a complex structure integrated knowledge from different domains. The dialects of the OWL ontology representation language and their expressiveness for representing special cases of ontologies used in KOSs are considered. The criteria for the classification of KOSs and sphere of their usage are analyzed. Formal model of ontology for semantic Wiki resource is proposed. This model is integrated with various implementing means for different types of relations between objects in the Semantic MediaWiki environment based on templates. Problems of access and retrieval of information in these resources and methods of their solving from the KOSs point of view are considered. The software implementation of the proposed approach with the example of the portal version of the Great Ukrainian Encyclopedia (e-VUE) is realized. The urgency of the problem intensifies by the need for national information resources in martial law situation, for which the determining factors of effective information processing are both the ability to obtain satisfaction of complex information needs and the relevance of the information obtained. This increases the importance of official government portals that integrate reliable data from various fields of knowledge and prevent possible misrepresentation (both accidental and malicious) of information in resources with open content generation.

Graphol: A Graphical Language for Ontology Modeling Equivalent to OWL 2

In this paper we study Graphol, a fully graphical language inspired by standard formalisms for conceptual modeling, similar to the UML class diagram and the ER model, but equipped with formal semantics. We formally prove that Graphol is equivalent to OWL 2, i.e., it can capture every OWL 2 ontology and vice versa. We also present some usability studies indicating that Graphol is suitable for quick adoption by conceptual modelers that are familiar with UML and ER. This is further testified by the adoption of Graphol for ontology representation in several industrial projects.

A multipurpose TNM stage ontology for cancer registries

BackgroundPopulation-based cancer registries are a critical reference source for the surveillance and control of cancer. Cancer registries work extensively with the internationally recognised TNM classification system used to stage solid tumours, but the system is complex and compounded by the different TNM editions in concurrent use. TNM ontologies exist but the design requirements are different for the needs of the clinical and cancer-registry domains. Two TNM ontologies developed specifically for cancer registries were designed for different purposes and have limitations for serving wider application. A unified ontology is proposed to serve the various cancer registry TNM-related tasks and reduce the multiplication effects of different ontologies serving specific tasks. The ontology is comprehensive of the rules for TNM edition 7 as required by cancer registries and designed on a modular basis to allow extension to other TNM editions.ResultsA unified ontology was developed building on the experience and design of the existing ontologies. It follows a modular approach allowing plug in of components dependent upon any particular TNM edition. A Java front-end was developed to interface with the ontology via the Web Ontology Language application programme interface and enables batch validation or classification of cancer registry records. The programme also allows the means of automated error correction in some instances. Initial tests verified the design concept by correctly inferring TNM stage and successfully handling the TNM-related validation checks on a number of cancer case records, with a performance similar to that of an existing ontology dedicated to the task.ConclusionsThe unified ontology provides a multi-purpose tool for TNM-related tasks in a cancer registry and is scalable for different editions of TNM. It offers a convenient way of quickly checking validity of cancer case stage information and for batch processing of multi-record data via a dedicated front-end programme. The ontology is adaptable to many uses, either as a standalone TNM module or as a component in applications of wider focus. It provides a first step towards a single, unified TNM ontology for cancer registries.

Ontology-Based Approach Supporting Multi-Objective Holistic Decision Making for Energy Pile System

The traditional way of designing energy pile system is mostly single domain/objective oriented, which lacks of means to coherently consider different while relevant factors across domains. The cost for life cycle design, construction and maintenance, return of investment, CO2 emission related sustainable requirements, and so on also need to be considered, in a systematic manner, along with the main functional design objective for loading capacity and robustness. This paper presents a novel multi-objective holistic approach for energy pile system design using ontology based multi-domain knowledge orchestration, which can holistically provide the designers with across domain factors regarding financial, safety, and environmental impact, for smart and holistic consideration during the early design stage. A prototypical ontology-based decision tool has been developed, aiming at the holistic optimization for energy pile system by combining ontology and Semantic Web Rule Language rules. A case study was performed to illustrate the details on how to apply knowledge query to provide a series of design alternatives autonomously by taking different design parameters into account. The method has demonstrated its practicability and scientific feasibility, it also shows the potential to be adopted and extended for other domains when dealing with multi-objective holistic design making.

Reasoning about location of robot-operated object based on probabilistic ontologies

Background: A robot needs to acquire the location of objects when performing daily tasks. Compared to industrial robots, a service robot faces a more complex and unstructured working environment where the location of the target object is usually uncertain. For example, due to diversity in personal habits and seasons, apples may be located in refrigerators, tables, or other places in the living environment. Methods: We propose a novel method for semantic localization of the robot-operated object based on probabilistic ontologies (PR-OWL) and multi-entity Bayesian networks (MEBN). The probabilistic web ontology language is used to describe and model the highly uncertain knowledge about the storage location of objects in the human household environment. Furthermore, the target location is inferred based on the multi-entity Bayesian network. Results: The proposed method is capable to adapting to environmental changes and achieves reliable probability estimation of object location. Experiments on simulated robotic tasks verify the effectiveness of the method. Conclusions: We show that applying PR-OWL combined with MEBN to locate the target object for the robot is feasible， which can improve the cognitive and self-adaptive ability of the robot.

A novel semantic representation approach for web documents using deep entity linking and multidocument support

SummaryRepresenting semantic web information in the form of existing formats like extensible mark‐up language (XML), resource description framework (RDF) or web ontology language (OWL) is limited by the inability to maintain intradocument relationships between different semantic entities. Moreover, these standards are built for generic data representation and thus do not have inherent support for the semantic description of the document and, consequently, do not support features like multidocument linkages and context‐sensitivity. In order to remove these drawbacks, a semantic web‐specific document representation approach, namely, deep semantic XML (DS‐XML) using deep linking and machine learning, is presented in this paper. The DS‐XML approach facilitates the use of semantics with the help of a novel document structure that focuses on defining any web document in a semantic form. It includes ontologies and linkage between different vocabularies, which assists in achieving semantic interoperability. In order to make this approach future proof, a novel deep linking approach is integrated at the document level, which allows DS‐XML to understand more about the contents of the document and represent information in an aggregated manner. The deep linking layer is combined with the machine learning‐based classification layer that allows the document information to be represented in an interactive manner. The proposed DS‐XML approach is tested on different document retrieval applications, including a few Internet of Things (IoT) applications, and the representation performance is found to be superior to the existing semantic approach (XML, RDF and OWL).

Merleau-Ponty’s Embodied Ontology and Literature: Gesture, Metaphor, Flesh, and Sensible Ideas

This essay traces out the importance of the poetic and creative use of language to Merleau-Ponty’s ontology. Why Merleau-Ponty’s phenomenology of embodiment inevitably had to turn towards a poetic use of language and to see the overlap between literature and philosophy in articulating an ontology is examined. The tie between a deeper sense of metaphor and the structure of the flesh of the world is explored. The attempt to articulate the latent background of perception leads to the essential role of what will be called the “physiognomic imagination”, which is a different use of imagination than “make-believe” and is key to the unfolding of the depths of perceptual sense. Understanding the efficacy of the literary use of language to the manifestation of further sense also requires an understanding of the temporality of the institution and the ongoing becoming of the real in Merleau-Ponty’s ontology. This essay argues that Merleau-Ponty’s turn to poetic language was both a source of his insights for ontology and the way that he came to express his own philosophy as a necessary outcome of fidelity to the phenomenology of perception. Given the parallel structure of the flesh of the world and metaphor, the dialogical nature of the perceptual encounter with the “voice of silence”, and the increasing importance of physiognomic imaginations, the temporality of institution and “sensible ideas” to his indirect ontology, the literary and poetic use of language had to assume a central role in the articulation of the flesh ontology as well as to the further manifestation of sense. This assertion is meant to rectify the reading and commentaries that fail to see this necessity and instead interpret Merleau-Ponty’s increasing use of poetic language as merely a residue of his evolving writing style and not as the necessary outcome of his ontological insights. This essay is also meant to address phenomenologists who fail to turn to literature and the poetic expression of embodied ontology as failing to carry forth Merleau-Ponty’s revisioning of philosophy and centrality of perception and embodiment.