Ontology Repository Research Articles

Ontologies related to livestock for the Global Burden of Animal Diseases programme: a review.

The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on agricultural animals, livestock production systems and associated communities worldwide. As part of the objectives of GBADs'Animal Health Ontology theme, the programme reviewed conceptual frameworks, ontologies and classification systems in biomedical science. The focus was on data requirements in animal health and the connections between animal health and human and environmental health. In May 2023, the team conducted searches of recognised repositories of biomedical ontologies, including BioPortal, Open Biological and Biomedical Ontology Foundry, and Ontology Lookup Service, to identify animal and livestock ontologies and those containing relevant concepts. Sixteen ontologies were found, covering topics such as surveillance, anatomy and genetics. Notable examples include the Animal Trait Ontology for Livestock, the Animal Health Surveillance Ontology, the National Center for Biotechnology Information Taxonomy and the Uberon Multi-Species Anatomy Ontology. However, some ontologies lacked class definitions for a significant portion of their classes. The review highlights the need for domain evidence to support proposed models, critical appraisal of external ontologies before reuse, and external expert reviews along with statistical tests of agreements. The findings from this review informed the structural framework, concepts and rationales of the animal health ontology for GBADs. This animal health ontology aims to increase the interoperability and transparency of GBADs data, thereby enabling estimates of the impacts of animal diseases on agriculture, livestock production systems and associated communities globally.

Comprehensive selective improvements in agri-informatics semantics

The advent of information technology re-innovates all sectors of bio-sciences. Researchers use Semantic Web to improve web searching, mining and integration, which alleviates the time-consuming task of finding relevant and high-quality content. Semantics is improved through ontology engineering in any domain. Amended and developed ontologies will be uploaded to existing standardised and approved biomedical repositories. The establishment of a World Wide Web Consortium (W3C) approved and standardised ontology repository is the most ambitious goal. This work will solely focus on some selected agri-ontologies. The main objective is to promote outcome-based research and transformation styles of relevant expertise sharing. The intended goal is to win project funding to train and equip students with relevant skills and expertise. Need-based and market-oriented training and professional grooming are a tangible asset for students. The majority of traditional Web development freelancers are unaware of ontology or semantic web market demand. Freelancing is another option for expert Ontology developers. However, agriculture students are used to all the research vocabulary and terminologies in their area, but they do not know how to contribute their expertise to improve the efficiency of the Semantic Web in their domain. If the improvement in relevant ontology becomes a part of the Semantic Web, then it is termed ‘Real-time Web semantics enhancement’. In other words, the target ontology becomes a part of the future Web of meaning.

Ontological support system of managerial decision-making of production tasks for a food enterprise

Resource and energy efficiency of industrial production, in particular, food production, is a defining requirement that will ensure its functioning without loss of quality and quantity of final products. This is achieved by observing the requirements for the operational parameters of the company’s technological processes and their operational changes. Given the complexity of the functioning of the energy component of the world and Ukraine due to military operations and their consequences, the issue of quality/cost ratio has become more acute. Therefore, for large manufacturing enterprises, the development of systems for supporting management decision-making in accordance with the Industry 4.0 concept becomes relevant. This will contribute to improving the production and economic indicators of the enterprise through coordinated actions of all links of production activities by structuring and processing large amounts of heterogeneous information. The purpose of the study is to develop a decision support system for the task of choosing the structure of an automated control system based on an ontological knowledge base. The developed application ontology uses descriptive logic and is interpreted as part of a digital production double implemented by a single ontological knowledge base and ontological repository. Considering existing international standards, the OWL2 language was chosen for the implementation of the ontological knowledge base. The ontology system architecture contains an ontology server, a Node-Red application, and a user form. A project decision support system that issues recommendations based on requests for the structure of the control system for a technological facility with uncertainties, considering the requirements and restrictions set for each technological process of a food enterprise, reduces the time to choose the appropriate structures, schemes, and methods. Thus, the designer receives the necessary information, supported by knowledge from the subject area, for the synthesis of an effective automated control system. It is also assumed that the ontological system will be expanded by connecting new created applied ontologies that implement related tasks of an industrial enterprise

An automated process for supporting decisions in clustering-based data analysis

Background and objectiveMetrics are commonly used by biomedical researchers and practitioners to measure and evaluate properties of individuals, instruments, models, methods, or datasets. Due to the lack of a standardized validation procedure for a metric, it is assumed that if a metric is appropriate for analyzing a dataset in a certain domain, then it will be appropriate for other datasets in the same domain. However, such generalizability cannot be taken for granted, since the behavior of a metric can vary in different scenarios. The study of such behavior of a metric is the objective of this paper, since it would allow for assessing its reliability before drawing any conclusion about biomedical datasets. MethodsWe present a method to support in evaluating the behavior of quantitative metrics on datasets. Our approach assesses a metric by using clustering-based data analysis, and enhancing the decision-making process in the optimal classification. Our method assesses the metrics by applying two important criteria of the unsupervised classification validation that are calculated on the clusterings generated by the metric, namely stability and goodness of the clusters. The application of our method is facilitated to biomedical researchers by our evaluomeR tool. ResultsThe analytical power of our methods is shown in the results of the application of our method to analyze (1) the behavior of the impact factor metric for a series of journal categories; (2) which structural metrics provide a better partitioning of the content of a repository of biomedical ontologies, and (3) the heterogeneity sources in effect size metrics of biomedical primary studies. ConclusionsThe use of statistical properties such as stability and goodness of classifications allows for a useful analysis of the behavior of quantitative metrics, which can be used for supporting decisions about which metrics to apply on a certain dataset.

DEVELOPMENT OF A VISUAL SEMANTIC WEB ONTOLOGY BASED LEARNING MANAGEMENT SYSTEM

This paper specifically aim at developing a visual semantic web ontology based e-Learning management system. The existing e-learning platforms have failed to address some challenges including managing the huge e-Learning content that is continuously grows on the web, meeting the learner's requirements when searching for an electronic learning content, representing the knowledge in a format that is easy to read and making it capable of thinking and thus allowing the re-use of e-Learning objects. In addition, most search results contain some irrelevant documents that cannot serve the need of the learner. Therefore, this thesis designed a common interface for learners, instructors, and administrators of academic institutions to upload and access learning materials. The new system created an ontology repository to maintain learners’ personalization details and taxonomy of the learning resources and integrate the knowledge embedded in many remote ontologies for improved e -Learning management system. In addition, an intelligent search engine through which learners can semantically search their learning materials and filter the search results returned by the search engine based on some semantics and the user’s preferences created. These designs simulated using a web-system developed with PHP, MySQL and JavaScript. The System Design followed the Object Oriented Design and Analysis Methodology for componentization of the system modules giving room for coupling, decoupling, modification, encapsulation and reuse, as well as easy maintainability. Unified Modeling Language extensively used to simplify the explanation of the system modules. The software performance wastested; the result shows that visual semantic web ontology-based e-Learning management system achieved 95% accuracy in returning the desired web search result.

Dynamic adaption in cyber-physical production systems based on ontologies

The paradigmatic shift of production systems towards Cyber-Physical Production Systems (CPPSs) requires the development of flexible and decentralized approaches. In this way, such systems enable manufacturers to respond quickly and accurately to changing requirements. However, domain-specific applications require the use of suitable conceptualizations. The issue at hand, when using various conceptualizations is the interoperability of different ontologies. To achieve flexibility and adaptability in CPPSs though requires overcoming interoperability issues within CPPSs. This paper presents an approach to increase flexibility and adaptability in CPPSs while addressing the interoperability issue. In this work, OWL ontologies conceptualize domain knowledge. The Intelligent Manufacturing Knowledge Ontology Repository (IMKOR) connects the domain knowledge in different ontologies. Testing if adaptions in one ontology within the IMKOR provide knowledge to the whole IMKOR. The tests showed, positive results and the repository makes the knowledge available to the whole CPPS. Furthermore, an increase in flexibility and adaptability was noticed.

Semantic Web Ontology Technology and Its Impact on E-Learning

This paper aims at portraying the imparts of integrating semantic web ontology technology into conventional online learning platform. This semantic e-learning system will have all the features of existing e-learning system as well as additional feature of semantic web ontology technology, which provides an adaptable, personalized and intelligent learning environment. With the incorporation of this technology, students can access the learning materials uploaded on the learning environment by the instructors as well as engage on self-directed learning by searching the ontology backbone of the semantic web. The ontology repository within the e-learning platform helps to maintain learners’ personalization details, as well as learning resources pertaining to different domains of knowledge and with the help of intelligent search engine, learners can semantically search through the ontology for learning materials based on their preferences, thus they are not placed at the mercy of the learning materials provided by the instructors. This semantic web ontology will be very helpful in promoting customized learning, thereby replacing the existing instructor centric e-learning systems. This paper has been able to show the tremendous improvement in electronic learning, following the integration of semantic web ontology approach and it will be very helpful to schools and other learning institutions in providing a sophisticated and adaptable learning environment for their students or learners.

АРХИТЕКТУРА ПОСТРОЕНИЯ БАЗЫ ЗНАНИЙ ПРОЕКТНОЙ ОРГАНИЗАЦИИ

The article presents the results of software package development to create a knowledge base for a design organization. The definition of the concept of knowledge is presented on the basis of existing definitions in open sources. The architecture of the software package is described, its main modules are listed, as well as third-party software systems used in the development of the software package. The article considers the organization of data storage subsystem of the software complex and describes the data model of this subsystem. An approach to organize a repository of the software package ontologies based on a database in an RDF format is described. The software structure for the implementation of connectors for integration with the existing systems of the design organization is presented. The article also describes a method for expanding a search query using ontology and a full-text search to take into account the features of the subject area in the search process. The information and digital model of the user of the design organization is described with reference to the artifacts of the design organization.

The development of a system for automated ontology building based on heterogeneous ontology design patterns

Currently, ontologies have become the main means of formalizing and systematizing knowledge and data in scientific subject domains (SSDs). In this regard, there is an urgent need for the methods and software tools allowing to involve specialists from different scientific subject domains in the process of ontology building. A possible way to solve this problem is to use ontology design patterns (ODPs). The paper presents an approach to the development of a system supporting the automated construction of the SSD ontologies based on ontology design patterns, which are the formal descriptions of field-proven solutions to typical ontological modeling problems. The main components of this system are repositories of heterogeneous ODPs and basic ontologies, including concepts common to most SSDs, and editors of patterns and ontologies used to build and populate ontologies.

Ontology Based Clinical Decision Support System for Geriatrics

This paper discusses an ontology based clinical decision support system for the specialty of Geriatric Medicine. We created a domain level ontology based on Handbook of Geriatrics and then mapped it to an upper level Basic Formal Ontology. The decision support system has been developed in Prolog. For accessing this ontology, we created an interactive web and android application which acts as a front-end to the system. Both applications are able to display the ontology structure and to predict the disease based on the symptom entered. We have uploaded our ontology to Bio-Portal, which is one of the most comprehensive biomedical ontology repository. It can be accessed using the URL https://bioportal.bioontology.org/ontologies/G-O.

Biomedical ontologies and their development, management, and applications in and beyond China

Abstract Since the boom of biomedical big data studies, various big data processing technologies have been developed rapidly. As an important form of knowledge representation, ontology has become an important means for the utilization and integration of biomedical big data. The emergence of new technologies for ontology development has resulted in the generation of many biomedical ontologies by many ontology development communities. The Open Biological and Biomedical Ontology Foundry, an academic organization for bio-ontology developers, has provided a set of principles to guide community-based open ontology construction. The Open Biological and Biomedical Ontology Foundry have also built many widely used ontologies, such as Gene Ontology, Human Phenotype Ontology, and Chemical Entities of Biological Interest. Other various ontology repositories have also been created and used to support ontology reuse. Many efficient tools for ontology applications, such as data annotation and terms mapping, have also been developed. High quality ontologies are also being used to develop new methods and tools for biomedical data analysis. The applications of Gene Ontology and Human Phenotype Ontology for data analysis and integration in recent years are reviewed here. To promote the development and applications of biomedical ontologies in China, a research community, OntoChina, was founded recently. OntoChina aims to support the development of reference ontologies, especially bilingual and Chinese translated ontologies. OntoChina also encourages ontology developers to follow the Open Biological and Biomedical Ontology Foundry principles.

Semantic annotation and harvesting of federated scholarly data using ontologies

PurposeEffective synthesis of learning material is a multidimensional problem, which often relies on handpicking approaches and human expertise. Sources of educational content exist in a variety of forms, each offering proprietary metadata information and search facilities. This paper aims to show that it is possible to harvest scholarly resources from various repositories of open educational resources (OERs) in a federated manner. In addition, their subject can be automatically annotated using ontology inference and standard thematic terminologies.Design/methodology/approachBased on a semantic interpretation of their metadata, authors can align external collections and maintain them in a shared knowledge pool known as the Learning Object Ontology Repository (LOOR). The author leverages the LOOR and show that it is possible to search through various educational repositories’ metadata and amalgamate their semantics into a common learning object (LO) ontology. The author then proceeds with automatic subject classification of LOs using keyword expansion and referencing standard taxonomic vocabularies for thematic classification, expressed in SKOS.FindingsThe approach for automatic subject classification simply takes advantage of the implicit information in the searching and selection process and combines them with expert knowledge in the domain of reference (SKOS thesauri). This is shown to improve recall by a considerable factor, while precision remains unaffected.Originality/valueTo the best of the author’s knowledge, the idea of subject classification of LOs through the reuse of search query terms combined with SKOS-based matching and expansion has not been investigated before in a federated scholarly setting.

Ontological approach to modeling innovation processes on the example of a distributed educational network of the University

The key task of the current stage of the education system development is the task of transition to new methods of organization and support of the educational process, allowing providing high-quality training of graduates with practical knowledge and skills in demand in the labor market. To solve this task is possible only with the use of innovative methods and tools for the creation of information-educational environment in the formation and processing of learning objects and software services distributed in the educational network and allowing the flexible implementation of the processes of educational and methodological support of educational activities. The aim of the research is to determine the possibilities of using the ontological approach to the construction of innovative automated education management systems, including the construction of individual learning trajectories. In this regard, the problem of modeling and algorithmization of the formation of educational programs as a chain of interrelated training modules and objects, taking into account the implementation of a competence-based model of learning in a distributed educational environment of the University, seems to be interesting. The modern education system is to be aimed primarily at adaptive generation of educational content, taking into account the needs of students and in accordance with constantly changing conditions and needs of the labor market. At present, research in this area mainly concerns issues such as the use of multimedia technologies and simulation programs, knowledge testing technologies based on the competency model, methods for measuring the degree of satisfaction with the quality of training, and management methods based on the portfolio of students. These issues and problems are considered with varying degrees of detail, for example, in [1, 2, 3, 4] and other works. The developed methodology for the formation of educational programs is based on the research results of these authors and is developing towards the use of ontologies that can integrate various concepts of professional and educational standards and create on their basis fundamentally new educational modules and objects. In our opinion, it corresponds to world trends in the development of science in this field of knowledge. It is propose d to use the methods and methodologies of knowledge engineering as engineering methods: ontological engineering methods used for semantic modeling of the information and educational environment, allowing to represent the subject area in the form of a set of interconnected ontologies; methods for constructing and visualizing ontologies; methodologies for building databases and knowledge bases and forming complex queries to databases and knowledge bases; methods for semantic analysis of metadata; graph theory. As a result of the analysis of the objects of the information and educational environment, the requirements for the meta-description of educational objects and services are identified, and a description of the concepts of basic ontologies of the informational and educational environment is presented. The article also discusses the possibilities of using modern software for the formation of an intellectual repository of ontologies. Thus, the proposed toolkit for generating educational programs, in our opinion, will allow us to formalize, simplify, and significantly accelerate the process offlexible development of materials necessary for organizing and supporting the educational process. Application of the described approach makes it possible to improve the quality of training of specialists due to the prompt creation of organizational, managerial and educational materials adapted to the requirements of the labor market, taking into account the peculiarities of forms and methods of training.

Ontology-based methods of thermophysical data integration

The article describes new technologies and tools used for drastic upgrading the database THERMAL, one of the oldest thermophysical databases. The database upgrade project provides for a essential expansion of its volume and service capabilities, as well as the possibility of permanently updating the conceptual scheme with the advent of new objects and notions. The developed technology ensures the conversion of old and newly loaded documents to a common semantically integrated infrastructure. In accordance with the project, the whole process of creating data and their further support includes three stages: conversion of all data, regardless of format, to a structured JSON document; creation of the ontology repository and the binding of terms from a JSON documents with the classes of ontologies for semantic integration; tuning of the high-performance computing platform to manage an extensive collection of JSON files and perform complex searches.

Automatic Relationship Construction in Domain Ontology Engineering using Semantic and Thematic Graph Generation Process and Convolution Neural Network

In recent studies, Ontology construction plays an important role in translating raw text into useful knowledge. The proposed methodology supports efficient retrieval using multidimensional theory and implements integrated data training techniques before enter the trial process. The proposed approach has used the Semantic and Thematic Graph Generation Process to extract useful knowledge, and uses data mining techniques and web solutions to present knowledge as well as improve search speed and information retrieval accuracy. Established ontology can help clarify what it means for different ideas and relationships. Due to the rise of the ontology repository, the process of matching can take a long time. To avoid this, the method produces a hierarchical structure with in-depth interpretation of the data. A system is designed to remove domain dependencies using a dynamic labeling scheme using basic theorem, and the results show that it is possible to automatically and independently construct an independent domain.

Developing an ontology schema for enriching and linking digital media assets

Abstract The abundance of digital media information coming from different sources, completely redefines approaches to media content production management and distribution for all contexts (i.e. technical, business and operational). Such content includes descriptive information (i.e. metadata) about an asset (e.g. a movie, song or game), as well as playable media (e.g. audio or video files). Metadata is organised following a variety of inconsistent structures and formats that are supplied by various content providers. Some challenges have been addressed in terms of standardising and enriching media assets metadata from a semantic perspective. Well known examples include Europeana and DBpedia. Nevertheless, due to the ongoing variability and evolution of digital contents, constant support and creation of new semantic representations are necessary. This article presents an ontology schema covering the requirements of users (content providers and content consumers) involved in the overall life cycle of a digital media asset, which has been designed and developed for a real scenario. The construction of this schema has been documented and evaluated following a methodology supported by quantitative and qualitative metrics. As part of the tangible results, the following outcomes were produced: (i) an RDF/XML schema available via Zenodo and GitHub; (ii) competence questions used for validation are published at GitHub; (iii) an exemplary ontology repository; and (iv) CRUD (Create, Read, Update and Delete) technologies for managing semantic repositories based on such schema. These results form an active part of the framework of a European project and other ongoing research initiatives.

The cell line ontology-based representation, integration and analysis of cell lines used in China

BackgroundThe Chinese National Infrastructure of Cell Line stores and distributes cell lines for biomedical research in China. This study aims to represent and integrate the information of NICR cell lines into the community-based Cell Line Ontology (CLO).ResultsWe have aligned, represented, and added all identified 2704 cell line cells in NICR to CLO. We also proposed new ontology design patterns to represent the usage of cell line cells as disease models by inducing tumor formation in model organisms, and the relations between cell line cells and their expressed or overexpressed genes or proteins. The resulting CLO-NICR ontology also includes the Chinese representation of the NICR cell line information. CLO-NICR was merged into the general CLO. To serve the cell research community in China, the Chinese version of CLO-NICR was also generated and deposited in the OntoChina ontology repository. The usage of CLO-NICR was demonstrated by DL query and knowledge extraction.ConclusionsIn summary, all identified cell lines from NICR are represented by the semantics framework of CLO and incorporated into CLO as a most recent update. We also generated a CLO-NICR and its Chinese view (CLO-NICR-Cv). The development of CLO-NICR and CLO-NIC-Cv allows the integration of the cell lines from NICR into the community-based CLO ontology and provides an integrative platform to support different applications of CLO in China.

Evaluation of ontology structural metrics based on public repository data.

The development and application of biological ontologies have increased significantly in recent years. These ontologies can be retrieved from different repositories, which do not provide much information about quality aspects of the ontologies. In the past years, some ontology structural metrics have been proposed, but their validity as measurement instrument has not been sufficiently studied to date. In this work, we evaluate a set of reproducible and objective ontology structural metrics. Given the lack of standard methods for this purpose, we have applied an evaluation method based on the stability and goodness of the classifications of ontologies produced by each metric on an ontology corpus. The evaluation has been done using ontology repositories as corpora. More concretely, we have used 119 ontologies from the OBO Foundry repository and 78 ontologies from AgroPortal. First, we study the correlations between the metrics. Second, we study whether the clusters for a given metric are stable and have a good structure. The results show that the existing correlations are not biasing the evaluation, there are no metrics generating unstable clusterings and all the metrics evaluated provide at least reasonable clustering structure. Furthermore, our work permits to review and suggest the most reliable ontology structural metrics in terms of stability and goodness of their classifications. Availability: http://sele.inf.um.es/ontology-metrics.

Harnessing the Power of Unified Metadata in an Ontology Repository: The Case of AgroPortal

As any resources, ontologies, thesaurus, vocabularies and terminologies need to be described with relevant metadata to facilitate their identification, selection and reuse. For ontologies to be FAIR, there is a need for metadata authoring guidelines and for harmonization of existing metadata vocabularies—taken independently none of them can completely describe an ontology. Ontology libraries and repositories also have to play an important role. Indeed, some metadata properties are intrinsic to the ontology (name, license, description); other information, such as community feedbacks or relations to other ontologies are typically information that an ontology library shall capture, populate and consolidate to facilitate the processes of identifying and selecting the right ontology(ies) to use. We have studied ontology metadata practices by: (1) analyzing metadata annotations of 805 ontologies; (2) reviewing the most standard and relevant vocabularies (23 totals) currently available to describe metadata for ontologies (such as Dublin Core, Ontology Metadata Vocabulary, VoID, etc.); (3) comparing different metadata implementation in multiple ontology libraries or repositories. We have then built a new metadata model for our AgroPortal vocabulary and ontology repository, a platform dedicated to agronomy based on the NCBO BioPortal technology. AgroPortal now recognizes 346 properties from existing metadata vocabularies that could be used to describe different aspects of ontologies: intrinsic descriptions, people, date, relations, content, metrics, community, administration, and access. We use them to populate an internal model of 127 properties implemented in the portal and harmonized for all the ontologies. We—and AgroPortal’s users—have spent a significant amount of time to edit and curate the metadata of the ontologies to offer a better synthetized and harmonized information and enable new ontology identification features. Our goal was also to facilitate the comprehension of the agronomical ontology landscape by displaying diagrams and charts about all the ontologies on the portal. We have evaluated our work with a user appreciation survey which confirms the new features are indeed relevant and helpful to ease the processes of identification and selection of ontologies. This paper presents how to harness the potential of a complete and unified metadata model with dedicated features in an ontology repository; however, the new AgroPortal’s model is not a new vocabulary as it relies on preexisting ones. A generalization of this work is studied in a community-driven standardization effort in the context of the RDA Vocabulary and Semantic Services Interest Group.

Retracted: The role of ontology repositories in supporting knowledge management processes

Ontology witnessed over the past years, the development of a huge increase in the number of applications that address many areas, especially in the Semantic Web context, arose digital repositories discovering many applications in various information systems, especially in e-learning systems, particularly with regards to store digital bond, where you need warehouses to represent the scope of the information and records of users define multiple languages rankings etc. This can be achieved by using the ontology presented in the language of the electronic ontology. Because the ontology provide new technologies and daily operations support, so becoming ontology and Semantic Web community are interested in using the warehouses containing semantic content (ontology).