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Organizational scholars concurred that positive workplace relationships with others can helps employee to gain from these relationships but, they lack insights into how or why this occurs. Moreover, the relationship dynamics focus on what the relationships provide without considering the how these relationships initiated, builds and maintains. To line of this, the current study aims to find the impact of mentoring functions (career, psychosocial, role modeling) and employee performance (career success, organization citizenship behavior, and job performance) via mediating effect of relational self-efficacy. For this purpose, the data were gathered from 310 branch banking employees of Pakistani conventional banks. PLS-SEM was used for data analysis. The results indicate that there is direct relationship between mentoring functions and employee’s performance. Moreover, the finding also shows that employee relational self-efficacy mediates the relationship between mentoring functions and employee performance. Theoretical and practical implications are discussed along with suggestions for future research.

This article presents the creation of an ontology describing Bulgarian folklore. The ontology has been developed based on the CCO (Cataloging Cultural Objects) standard. CCO leads us to provide data content standards. The set of ontologies is a knowledge base used by intelligent agents. One of the main problems with systems and developments describing different cultural and/or historical sites is the difficulty in sharing information between individual societies or systems. The use of standards greatly facilitates the dissemination of data. The CCO standard provides clear and precise definitions of the individual attributes that an object must possess. The ontologies developed by Protégé are designed in such a way as to meet the requirements of the standard. The created ontologies describe 7 folklore areas with specific ones being: music, dances and musical instruments. The work on creating this ontology directs us to create web applications of the developed ontologies.

PurposeThis work provides a generic review of the existing data mining ontologies (DMOs) and also provides a base platform for ontology developers and researchers for gauging the ontologies for satisfactory coverage and usage.Design/methodology/approachThe study uses a systematic literature review approach to identify 35 DMOs in the domain between the years 2003 and 2021. Various parameters, like purpose, design methodology, operations used, language representation, etc. are available in the literature to review ontologies. Accompanying the existing parameters, a few parameters, like semantic reasoner used, knowledge representation formalism was added and a list of 20 parameters was prepared. It was then segregated into two groups as generic parameters and core parameters to review DMOs.FindingsIt was observed that among the 35 papers under the study, 26 papers were published between the years 2006 and 2016. Larisa Soldatova, Saso Dzeroski and Pance Panov were the most productive authors of these DMO-related publications. The ontological review indicated that most of the DMOs were domain and task ontologies. Majority of ontologies were formal, modular and represented using web ontology language (OWL). The data revealed that Ontology development 101, METHONTOLOGY was the preferred design methodology, and application-based approaches were preferred for evaluation. It was also observed that around eight ontologies were accessible, and among them, three were available in ontology libraries as well. The most reused ontologies were OntoDM, BFO, OBO-RO, OBI, IAO, OntoDT, SWO and DMOP. The most preferred ontology editor was Protégé, whereas the most used semantic reasoner was Pellet. Even ontology metrics for 16 DMOs were also available.Originality/valueThis paper carries out a basic level review of DMOs employing a parametric approach, which makes this study the first of a kind for the review of DMOs.

The exponential growth of data and the boom of online businesses necessitates the need for data to be machine-readable, as humans are no longer able to manually manage the vast amounts of data. Ontologies can define concepts and relations that are amenable to processing by machines. Ontologies are created in silos and pockets of domains, and the need to merge these resources is key to universal access to multi-domain knowledge. Merging of ontologies has been explored to an extent over the last two decades, and this paper explores the extent of the tools and techniques available with a case study of merging two ontologies which are publicly available, the Person ontology and Institutional ontology, using the latest tools available on the most popular ontology editor, Protégé. It is found that automated merging tools have not been improved much over the last two decades, and the most current merging tools provided combine the two ontologies into one but do not unite or merge any of the classes or axioms which are equivalent. This can be seen in the axiom count, which does not decrease in the merged ontology, showing that no similar classes or actual axioms were merged. Protégé plugins which used to provide the semi-automatic mapping of similar classes to assist the merging process were found to be no longer available, and manual mapping by the knowledge engineer was required. This supports further research in automated ontology merging techniques.

Cryptoccurency is a digital currency that is used as a medium of exchange as well as rupiah and dollars. And just like currency, Cryptocurrency also experiences value volatility or commonly reffered to as fluctuation. The purpose of this study is to estimate the fluctuating cryptocurrency value by implementing it into ontology using protégé tools. With the ontology, it can make it easier for users to find information about cryptocurrency. The results of this study indicate that ontology is one of the bases of Knowledge Managament Systems which can make it easier to systematizem, improve and accelerate knowledge management so that it is easy to understand for cryptocurrency users. Another result of this research is the creation of an ontology cryptoccurency with the blockchain subclass, users, currency, economu and factors. Each of these subclasses has more subclasses in a structured manner, and the results of making computer technique ontology in estimating the economic value of cryptocurrency are useful for users or people who want to find out more information about cryptocurrency.

Purpose Semantic modelling is an essential prerequisite for designing the intelligent human–computer interaction in future aircraft cockpit. The purpose of this paper is to outline an ontology-based solution to this issue. Design/methodology/approach The scenario elements are defined considering the cognitive behaviours, system functions, interaction behaviours and interaction situation. The knowledge model consists of a five-tuple array including concepts, relations, functions, axioms and instances. Using the theory of belief-desire-intention, the meta-model of cognitive behaviours is established. The meta-model of system functions is formed under the architecture of sub-functions. Supported by information flows, the meta-model of interaction behaviours is presented. Based on the socio-technical characteristics, the meta-model of interaction situation is proposed. The knowledge representation and reasoning process is visualized with the semantic web rule language (SWRL) on the Protégé platform. Finally, verification and evaluation are carried out to assess the rationality and quality of the ontology model. Application scenarios of the proposed modelling method are also illustrated. Findings Verification results show that the knowledge reasoning based on SWRL rules can further enrich the knowledge base in terms of instance attributes and thereby improve the adaptability and learning ability of the ontology model in different simulations. Evaluation results show that the ontology model has a good quality with high cohesion and low coupling. Practical implications The approach presented in this paper can be applied to model complex human–machine–environment systems, from a semantics-driven perspective, especially for designing future cockpits. Originality/value Different from the traditional approaches, the method proposed in this paper tries to deal with the socio-technical modelling issues concerning multidimensional information semantics. Meanwhile, the constructed model has the ability of autonomous reasoning to adapt to complex situations.

Semantik web merupakan teknologi yang mampu memahami konteks seperti halnya manusia memahami konteks tersebut. Teknologi semantik dapat dimanfaatkan dalam berbagai bidang, salah satunya adalah klasifikasi topik skripsi mahasiwa. Banyak skripsi membahas topik serupa, tapi dengan peristilahan berbeda. Hal tersebut seringkali menimbulkan kesulitan dalam menentukan apakah suatu topik sudah terlalu sering dibahas. Oleh sebab itu, penelitian ini bertujuan untuk mengklasifikasikan dan memetakan bidang minat skripsi mahasiswa Program Studi S1 Teknik Informatika (TI) Unpad. Langkah-langkah yang dilakukan dalam penelitian ini adalah mengumpulkan data, menentukan entitas, implementasi ontologi, dan klasifikasi data menjadi beberapa kelas berdasarkan bidang minat di Program Studi TI Unpad (Sistem Informasi dan Multimedia, Kecerdasan Buatan dan Robotika, Jaringan Komputer, dan Metode Numerik). Langkah akhirnya adalah proses training dan testing data menggunakan algoritma k-nearest neighbour (KNN). Klasifikasi aktual data menunjukkan bahwa mayoritas skripsi di Prodi TI Unpad adalah tentang Sistem Informasi dan Multimedia, dengan presentase 50.23%. Sedangkan, klasifikasi prediktif data dengan algoritma KNN menunjukkan persentase 47.88%. Hasil yang berbeda tersebut diperoleh karena Confusion Matrix menunjukkan nilai sebagai berikut: AUC (0.711), CA (0.545), F1(0.578), Precision (0.669), Recall (0.545).

Natural language processing (NLP) is rapidly increasing in all domains of knowledge acquisition to facilitate different language user. It is required to develop knowledge-based NLP systems to provide better results. Knowledge based systems can be implemented using ontologies where ontology is a collection of terms and concepts arranged taxonomically. The concepts that are visualized graphically are more understandable than in the text form. In this research paper, new multilingual ontology visualization plug-in MLGrafViz is developed to visualize ontologies in different natural languages. This plug-in is developed for Protégé ontology editor. This plug-in allows the user to translate and visualize the core ontology into 135 languages.

The present work describes the development of a conceptual representation model of the domain of the theory of formal grammars and abstract machines through ontological modeling. The main goal is to develop an ontology capable of deriving new knowledge about the mood of an Alzheimer’s patient in the categories of wandering, nervous, depressed, disoriented or bored. The patients are from elderly care centers in Ambato Canton-Ecuador. The population consists of 147 individuals of both sexes, diagnosed with Alzheimer’s disease, with ages ranging from 75 to 89 years. The methods used are the taxonomic levels, the semantic categories and the ontological primitives. All these aspects allow the computational generation of an ontological structure, in addition to the use of the proprietary tool Pellet Reasoner as well as Apache NetBeans from Java for process completion. As a result, an ontological model is generated using its instances and Pellet Reasoner to identify the expected effect. It is noted that the ontologies come from the artificial intelligence domain. In this case, they are represented by aspects of real-world context that relate to common vocabularies for humans and applications working in a domain or area of interest.

In the framework of an intelligent assembly information system, the three-dimensional model of a product serves as a critical information source for the system, which also provides initial product feature information for assembly sequence planning. At present, in the process of extracting information from the STEP neutral file, the products are rarely performed at the assembly level. In addition, the characteristic of semantic expression of the same parts included in a product is always ignored. In this paper, based on the theory of ontology, the OntoSTEP model is constructed to extract information from STEP neutral files at the assembly level. A set of extraction rules for the basic corresponding information of the same parts in the assembly are developed. Further, a SWRL rule library is established in Protege to realize the comprehensive information extraction of the assembly hierarchy for a product from its 3D model, which lays the foundation for the assembly sequence planning.

In present paper we consider ontology-driven approach applied to neurocognitive science. At the beginning, a brief overview of the works revealing the prospects and possibilities of constructing ontological models in this field of knowledge is given. Based on the conducted analysis we have concluded that the scientific community states the urgency of creating an ontology intended to accumulate interdisciplinary knowledge necessary for assessing cognitive functions being the most complex functions of the brain, through which the process of rational cognition of the world is carried out. So we have analyzed the key features of the knowledge representation about cognitive functions in the field of psychology, cognitive science and neurobiology. As a result we propose conceptual structure, basic classes and relations for the cognitive functions ontology intended to the clearer understanding of the relationships between the brain activity patterns and the human cognitive abilities. The ontology was implemented using OWL in the Protege 5.2 ontology editor environment. It accumulates knowledge about cognitive functions and methods for assessing them with use of neuropsychological tests and EEG methods. A certain set of axioms also have been implemented and approved.

In the European Union, the silver economy is focused on developing strategies to facilitate the elderly population, mainly in terms of creating services based on innovations and technology. The paper encompasses a detailed overview of the silver economy in Estonia and the introduction of ICT solutions for the elderly population through knowledge management techniques. A knowledge map has been created using the Ontology model in Protege to demonstrate the key knowledge resources for ICT integration in the silver economy. The results and information displayed in the knowledge map have been gathered from two detailed workshops which were further validated through questionnaires and interviews from the professionals in the field. The purpose of this paper is to discuss the different knowledge resources and competencies relevant to the integration of ICT in the silver economy which will serve as a basis for the development of a knowledge management model in the future.

The World Health Organization (WHO) indicates that the proportion of the elderly will soon include nearly a quarter of the world population. Ensuring that health systems are prepared to deal with this phenomenal rate of aging and associated diseases generates many challenges. Among these challenges is facing Alzheimer’s Disease (AD) that may occur at some point in the elderly life and may harm societies. AD is considered a neurological, psychological, mental, and health setback. The Clinical Decision Support System (CDSS) can improve patient care and support many medical functions, such as diagnosing diseases that can reduce preventable harm. This research’s main objective is to design, implement, and evaluate the Alzheimer’s Disease Diagnosis Ontology (ADDO). It is a comprehensive semantic knowledge base toward the development of fuzzy ontology-based CDSS for AD diagnosis. ADDO can serve as a core component of CDSS, which provides representation, annotation, and access to aspects related to AD’s study and diagnosis. Toward the management of this objective, ADDO is based on the essentials of the Open Biomedical Ontology (OBO) and follows the Basic Formal Ontology (BFO) and the Ontology for General Medical Sciences (OGMS) principles. ADDO focuses on representing the patient characteristics, complications, drugs, diagnosis examination tests, and key aspects of their periodic visits in a standard way. The possibility of semantic interoperability is taken into account by integrating ADDO and a heterogeneous AD dataset. We used ADNI as a case study to mapping a set of real instances. To manage the medical domain’s uncertainty, ADDO is extended to fuzzy ontology to accommodate the medical linguistic variables and enhance diagnosis results’ efficiency. ADDO is constructed using Protege 5.5.0 software and evaluated using the HermiT reasoner and SPARQL semantic queries. ADDO currently includes 7060 concepts, 99 properties, 46274 axioms, and 30708 annotations. As a result, ADDO is consistent and more reliable in managing most AD aspects than other existing AD ontologies.

The article describes a classification system with natural language processing. Many systems use neural networks, but it needs massive amounts of data for training, which is not always available. Authors propose to use ontologies in such systems. As example of such approach it is shown the classification system, which helps to form a list of the best candidates during the recruitment process. An overview of the methods for ontologies constructing and language analyzers appropriate for classification systems are presented. The system in the form of a knowledge base is constracted. Described system supports Ukrainian and English languages. The possible ways of system expansion is regarded.

User-friendly formal specification and verification of concurrent and distributed systems for various domains, such as automatic control systems, telecommunications, and business processes, are active research topics due to their practical significance. In this paper, we present methods of developing verification-oriented domain-specific process ontologies used to describe concurrent systems of subject domains. One of the advantages of such ontologies is their formal semantics, which provides formal verification of the described systems. Our method is based on an abstract verification-oriented process ontology. We use two methods of domain specialization of the abstract process ontology. The declarative method relies on specializing classes of the original ontology, introducing new declarative classes, and using a new set of axioms to set restrictions on classes and relations of the abstract ontology. The constructive method uses semantic markup and pattern matching techniques to link domain concepts to classes of the abstract process ontology. We provide detailed ontological specifications for these techniques. Our methods preserve the formal semantics of the original process ontology; therefore, formal verification methods can be applied to the resulting domain-specific process ontologies. We demonstrate that the constructive method is a refined version of the declarative method. We illustrate our methods on the example of constructing an ontology for standard elements of automatic control systems: we develop declarative descriptions of the classes and restrictions of the domain-specific ontology in the Protege system in the Web Ontology Language (OWL) using inference rules written in the Semantic Web Rule Language (SWRL) and construct a system of semantic markup patterns that implements standard elements of automatic control systems.

Mentoring occurs every day in the workplace, as experienced employees (mentors) help guide inexperienced ones (protégés) toward a common goal. Both the mentor and protégé possess hallmark characteristics that contribute to a successful mentorship. The typology of mentoring includes formal versus informal, as well as group, one-on-one, peer, remote, and invisible mentors. The benefits of these mentorships can impact students, inexperienced employees, health care institutions, education institutions, patient care, and the mentors themselves. Finally, there are recommendations for fostering mentoring for educators and managers.

We analyse modern approaches to the interaction of the educational services market with the labour market through recognition of non-formal and informal learning outcomes. The authors prove the expediency of semantic technologies used for information processing at the knowledge level. ESCO classifier that combines services of the labour market and the educational market is examined in detail. This classifier allows jobseekers and employers from different EU member states to handle information on learning outcomes more efficiently. The analyzes of practical ESCO classifier usage on example of the European Employment Service (EURES) demonstrates that this approach provides all necessary information for jobseekers abroad. The ontological analysis is an efficient way to model the ideas of various subject domains and it allows to represent formally their semantics. Hence, the research analyzes the ontological model for this information system and its components; in particular, the authors provide the described content of the ESCO ontological model which consists of three elements – occupations, skills and qualifications. The paper offers an information system for semantic identification and documentation of non-formal and informal learning outcomes based on the ESCO ontological model. The authors select and analyze the main stages of the system development: an ontology scheme in the Protege editor is created; the process of integrating the ontology in the RDF-repository is described; the architecture and user interface of the suggested information system are developed. Semantic graphs database GraphDB is used for ontology storage. To implement the addition and modification of data in GraphDB repository, connectors are used. Access to the RDF-repository is provided with SPARQL query language, whose outcomes are represented as result sets or RDF-graphs. In addition, the research justifies the use of React framework for development of the information system user interface. The architecture and user interface of information system proposed in this research work allow to carry out the semantic identification and documentation of non-formal and informal learning outcomes. Thus, they increase the efficiency of managing the information about these outcomes. Problems in programming 2020; 2-3: 11-21

PurposeHealth-care ontologies and their terminologies play a vital role in knowledge representation and data integration for health information. In health-care systems, Internet of Technology (IoT) technologies provide data exchange among various entities and ontologies offer a formal description to present the knowledge of health-care domains. These ontologies are advised to assure the quality of their adoption and applicability in the real world.Design/methodology/approachOntology assessment is an integral part of ontology construction and maintenance. It is always performed to identify inconsistencies and modeling errors by the experts during the ontology development. A smart health-care ontology (SHCO) has been designed to deal with health-care information and IoT devices. In this paper, an integrated approach has been proposed to assess the SHCO on different assessment tools such as Themis, Test-Driven Development (TDD)onto, Protégé and OOPs! Several test cases are framed to assess the ontology on these tools, in this research, Themis and TDDonto tools provide the verification for the test cases while Protégé and OOPs! provides validation of modeled knowledge in the ontology.FindingsAs of the best knowledge, no other study has been presented earlier to conduct the integrated assessment on different tools. All test cases are successfully analyzed on these tools and results are drawn and compared with other ontologies.Originality/valueThe developed ontology is analyzed on different verification and validation tools to assure the quality of ontologies.

In this paper, an optimization problem for selecting equipment types when designing chemical and technological systems for multipurpose chemical production is stated along with proposed approaches to solving this problem. Based on hypergraph theory, an ontology structure was developed for determining the equipment type depending on the properties of the substances under treatment. An ontology prototype was developed in the Protege software environment.

Transferring knowledge from experts to apprentices is critical for sustaining a company’s competitive advantage. Further, existing literature indicates that employees in the Millennial (Y) generati...

Map projections are an area of cartography with a firm mathematical foundation for their creation and display providing a basis for a knowledge representation. Using only variations on a single equation set, an infinite number of projections can be created, but less than 100 are in active use. Because each projection preserves specific characteristics, such as area, angles, global look, or a compromise of properties, classifications of map projections have been developed to aid in knowledge representation. These classifications are used for decision-making. They help select the correct projection for the map use. They assist users with determining the correct orientation, standard parallels and meridians. The classifications also inform the user how to adjust the selection based on size, extent, and latitude. Semantics can be used to automate map projections knowledge into a knowledge base that can be accessed by humans and machines. This work details a semantic representation of map projections knowledge and provides a simple example of a use case that exploits the knowledge base.

Highlights •Social Media, FCA and fluent editor tool is used for the construction of ontology.•A small ontology is constructed for terrorism domain.•Utilizing the reasoner the semantic query can be processed like a relational database.•User defined relationships are used for the construction of ontology.Semantic Web, deals with the meaning of information in a defined domain and Ontologies are the backbone of Semantic Web. Domain Ontologies are crucial source of information for knowledge-based system. Still, domain ontology development is a labor- intensive process and is highly dependent on developers knowledge. In this work, a novel semiautomatic method is proposed to build an ontology on terrorism domain. Terrorism activities provide crucial information to enhance security system for any country worldwide. Social media data, namely, Twitter text data is extracted to attain latest information related to domain and next, concepts and relationships are identified and mapped using formal concept analysis. Several user-defined relationships are presented through fluent editor tool. Also, knowledge is extracted with the help of query-based system through a reasoner window of fluent editor. The developed domain ontology is published on web using ontology web language which can be utilized in other related application areas. The proposed work is significant as it develops a wide-coverage domain ontology for terrorism domain using a tool named Fluent Editor, in place of standard tool protege and semantic information is extracted similar to query-based system with 100% accuracy.

Conventional search engines provide a lot of irrelevant results to the user’s search query, which consumes a lot of time and effort, as the context and semantics of the request made by the user are not analyzed to the optimum extent. This highlights for the need of a methodology embedded in the search machinery, enabling semantic web search. Ontologies have proven to be an effective technology for such semantic knowledge representation and information retrieval. In this research paper, the researcher has constructed a string ontology in a new domain (the music domain) from scratch using Protege 5.0 for semantic information retrieval for a query in the search engine. This ontology is further used in the proposed ontology based semantic information retrieval method (OBSIRM), which has been built to refine the web search in the music domain. The researcher has proposed a novel approach to refine the web search in which the query is first replaced with abbreviations along with the use of the multilingual concept to search a query. The results of the proposed method have been compared with Google. The accuracy and efficiency of the proposed method has been measured in terms of precision and recall. The average precision and recall of OBSIRM is 1.43 and 0.7 as compared to generic Google search engine i.e. 1.04 and 0.51. Hence it can safely be concluded that in the domain of research the OBSIRM performs better in terms of users’ expectations than Google (for string instrument domain considered by the researcher) as far as relevant information retrieval is concerned.

According to the W3C, the semantic web is the future of the www. The data that is based on the semantic web can be understood by machines and devices. The main component of the semantic web is the ontology, which is known as the backbone of the semantic web. There are many tools used to edit and create an ontology, however, few kinds of research construct an ontology using oriented programming. SPARQL and API OWL are used to access and edit ontologies, though they are not using oriented programming. The main objective of this paper is to build an ontology using oriented programming and allowable to access OWL entities. Owlready module is effectively used in sport ontology for football in 11 European Leagues.

Description logic ontologies, such as ontologies written in OWL, and non-monotonic rules, as known in Logic Programming, are two major approaches in Knowledge Representation and Reasoning. Even though their integration is challenging due to their inherent differences, the need to combine their distinctive features stems from real world applications. In this paper, we give an overview of NoHR, a reasoner designed to answer queries over theories composed of an OWL ontology in a Description logic and a set of non-monotonic rules. NoHR has been developed as a plug-in for the widely used ontology editor Protege, building on a combination of reasoners dedicated to OWL and rules, but it is also available as a library, allowing for its integration within other environments and applications. It comes with support for all polynomial OWL profiles and the integration of their constructors as well as for standard built-in Prolog predicates, and allows the direct consultation of databases during query evaluation and the usage of sophisticated mechanisms, such as tabling already computed results, all of which enhances the applicability and the efficiency of query answering.

This study proposed protégé’s ego-resiliency as a parsimonious predictor of perceived mentoring. Uncertainty-avoidance and collectivism orientations were hypothesized as boundary conditions of this relationship. An additive multiple moderation model was developed using conservation of resource theory. Data were collected from 193 employees of a large Southeast Asian commercial bank. Results of structural equation modeling indicated that protégé’s ego-resiliency was positively related to perceived mentoring. This positive relation was stronger for protégés who held weaker uncertainty-avoidance orientations and was stronger for those who held collectivistic orientations. Implications for theory and practice are discussed.

Workplace mentoring relationships have been advanced as critical to employee development. However, mentoring research has tended to find small to moderate effects of mentoring on protégé and mentor outcomes and considerable heterogeneity in effect sizes. These findings underscore the need to better understand the psychology of mentoring relationships in order to maximize the benefits of mentoring for mentors, protégés, and organizations. In this article, after briefly reviewing established research on workplace mentoring relationships, we introduce five relationship science theories from outside organizational psychology and organizational behavior that provide new insight into the psychology of workplace mentoring: attachment theory, interdependence theory, self-expansion theory, Rhodes’ model of formal youth mentoring, and the working alliance. We then discuss several unique features of workplace mentoring that should be considered when applying these relationship science theories and introduce provocative ideas for future research. We conclude by discussing practical implications for mentors, protégés, and organizations.

This paper presents the ontology of the concurrent processes close to Hoare communicating sequential processes. It is a part of an intellectual system for supporting verification of behavioral properties of such processes. Our ontological representation of the processes is oriented both to the application of formal verification methods and to the extraction of information from technical documentation (by our previously developed system of information extraction from a natural language text). We describe the ontology classes and domains that define communicating concurrent processes. These processes are characterized by sets of local and shared variables, a list of actions on these variables which change their values, a list of channels for the process communication (which, in turn, are characterized by the type of reading messages, capacity, modes of writing and reading, and reliability), and also a list of communication actions for sending messages. In addition to the formal mathematical definition of classes and domains of the ontology, examples of descriptions of some ontological classes, as well as typical properties and axioms for them, are specified in the editor Protege in the OWL language with the use of the inference rules in the SWRL language. We define the formal operational semantics of communicating processes for their ontological representation. This semantics is a labeled transition system. It is reduced to the local operational semantics of separate process instances in the interleaving model. We specialize several types of processes from the subject domain of automatic control systems that model the typical functional elements of the automatic control system (sensors, comparators and regulators), as well as their combinations. The concepts of the specialized ontology are illustrated by the example of a control part of a bottle-filling system.

Background Fast food with its abundance and availability to consumers may have health consequences due to the high calorie intake which is a major contributor to life threatening diseases. Providing nutritional information has some impact on consumer decisions to self regulate and promote healthier diets, and thus, government regulations have mandated the publishing of nutritional content to assist consumers, including for fast food. However, fast food nutritional information is fragmented, and we realize a benefit to collate nutritional data to synthesize knowledge for individuals. Methods We developed the ontology of fast food facts as an opportunity to standardize knowledge of fast food and link nutritional data that could be analyzed and aggregated for the information needs of consumers and experts. The ontology is based on metadata from 21 fast food establishment nutritional resources and authored in OWL2 using Protégé. Results Three evaluators reviewed the logical structure of the ontology through natural language translation of the axioms. While there is majority agreement (76.1% pairwise agreement) of the veracity of the ontology, we identified 103 out of the 430 statements that were erroneous. We revised the ontology and publicably published the initial release of the ontology. The ontology has 413 classes, 21 object properties, 13 data properties, and 494 logical axioms. Conclusion With the initial release of the ontology of fast food facts we discuss some future visions with the continued evolution of this knowledge base, and the challenges we plan to address, like the management and publication of voluminous amount of semantically linked fast food nutritional data.

Background 2019-nCoV has been spreading around the world and becoming a global concern. To prevent further widespread of 2019-nCoV, confirmed and suspected cases of COVID-19 infection are suggested to be kept in quarantine. However, the diagnose of COVID-19 infection is quite time-consuming and labor-intensive. To alleviate the burden on the medical staff, we have done some research on the intelligent diagnosis of COVID-19. Methods In this paper, we constructed a COVID-19 Diagnosis Ontology (CDO) by utilizing Protégé, which includes the basic knowledge graph of COVID-19 as well as diagnostic rules translated from Chinese government documents. Besides, SWRL rules were added into the ontology to infer intimate relationships between people, thus facilitating the efficient diagnosis of the suspected cases of COVID-19 infection. We downloaded real-case data and extracted patients’ syndromes from the descriptive text, so as to verify the accuracy of this experiment. Results After importing those real instances into Protégé, we demonstrated that the COVID-19 Diagnosis Ontology showed good performances to diagnose cases of COVID-19 infection automatically. Conclusions In conclusion, the COVID-19 Diagnosis Ontology will not only significantly reduce the manual input in the diagnosis process of COVID-19, but also uncover hidden cases and help prevent the widespread of this epidemic.

Today, data which is growing exponentially; has become very important in the both backup and analysis phase. For this reason, it is necessary to store, transfer and examine the data in a correct structure according to the semantic web principles. In addition, the aim of the computers to automatically infer some operations without the need for human intervention and to be more beneficial to people in this state is being worked on. An example of the human resources ontology developed with the Protege tool is described in order to accelerate and correct the semantic network processes with the ontologies created for this purpose. In addition, the developed ontology was queried using SPARQL language. In this study, it is aimed to query different types of heterogeneous data together with RDF queries. Thus, in addition to relational databases, which are still indispensable today, many heterogeneous data will be queried and inferences can be made by computers.

The task of structure designe of the software complex of tools for inductive modeling on the GMDH basis is considered. A novel is the use of the knowledge base in the form of an ontology of the subject area of inductive modeling. The application of the ontological approach to the construction of the knowledge base makes it possible to reuse information and effectively process this information when modeling complex systems of different nature using statistical data, to form queries and obtain logical conclusions. Fragments of the ontology of inductive modeling based on GMDH as an example of creating a formal description of the subject area are given. The Protege_4.3 ontoeditor was used to construct ontological models of the inductive modeling domain.

Guiding the building occupants under fire emergency to a safe place is an open research problem, and finding solutions to address the problem requires a perfect knowledge of the fire building evacuation domain. The use of ontologies to model knowledge of a domain allows a common and shared understanding of that domain, between people and heterogeneous systems. This paper presents an ontology that aims to build a knowledge model to understand the referred domain better and help develop more capable building evacuation solutions and systems. The herein proposed ontology considers the different variables and actors involved in the fire building evacuation process. We followed the Methontology methodology for its developing, and we present all the development steps, from the specification to its implementation with the Protégé tool. info:eu-repo/semantics/publishedVersion

Indonesia has many ethnic groups and each ethnic group has various types of dances. Jaipong Oray Welang is one of the most popular modernized traditional dances originating from the Sundanese people. In an effort to preserve this dance, it is necessary to record the knowledge, not only in terms of descriptions and other attributes but also recording a series of dance moves along with pictures of examples of each dance movement. In this study, the ontology of the Jaipong Oray Welang dance has been built. Dance movement data was obtained from observations and interviews of dancers in a Sundanese dance studio. Ontology is implemented using the protege application and owlready2 in python, and competency questions are evaluated using SPARQL queries.

The paper investigates the possibilities of using the ontological approach in neurocognitive science and presents the results of building an ontology of cognitive functions. The developed ontology is intended for the accumulation of interdisciplinary knowledge necessary for the study of cognitive functions through which the process of rational knowledge of the world is carried out. The paper proposes a conceptual structure for understanding the relationship between patterns of brain activity and human cognitive abilities. The ontology was implemented using the Protege 5.2. The ontology accumulates knowledge about cognitive functions and methods of their assessment using neuropsychological tests and EEG methods. A distinctive feature of the proposed ontology from existing ones is the inclusion of concepts that reflect the terminology used in the study of cognitive functions from the standpoint of analyzing psychometric and neurophysiological data, as well as knowledge about combinations of electrodes and features that can be used in machine learning from EEG data to identify patterns of brain activity.

The semantic web is enabling persons to create data stores on an existing web. On the other side, a semantic web also refers to search data sources within a specified web depository. In this paper, various ontologies are created for various courses offered by different universities and institutions for handling courses and student data. Ontology is also offered students to opt-in to various courses depending on their choice using the protege alpha tool. This paper also proposed trust ontology using the concept of data provenance like PROV-DM.

The research was to identify needs on design and development of a research recommendation system for 14 southern province Thailand development. The system employs semantic search function, research system structure and scope of knowledge during January 2008 to December 2017. 3,873 entries had been gathered from Thai Library Integrated System (ThaiLIS), Thai National Research Repository (TNRR), and Southern universities research database by employing textual analysis and knowledge organization focusing on Classification Approach and categorization which main topics are sorted and categorized. To develop ontology, it applies knowledge engineering concept and using Protégé Ontology Editor version 3.5 beta and version 5.5 beta to process the data for the accurate system development according to user-centered design concept. The study findings were the developed system is able to support information exchange, information retrieval, and research search and to decrease research redundancy and unnecessary budgeting. Moreover, the system could possible enhance conducting more innovations, confirming experts in the area, showing research trends, and showing research results on related fields, strategies, and problems which leads to the Southern developments extensively. After the implementation, the users’ overall opinions and satisfaction was at a high level ( = 4.14, S.D = 0.14) and information retrieval efficiency of system was at a good level (overall = 0.70-0.88) with 0.70 accuracy, 0.78 recall, 0.88 precision, and 0.82 F-measure.

We investigated mentoring as a moderator between competitive climate and employee creative work involvement. Participants were 270 academic staff of a Nigerian federal university (male = 155 [57.41...

Purpose The purpose of this paper is to present a conceptual model for coding and dissemination of data associated with historical photographic archives. The model is based on Linked Open Data technology and seeks to exhaustively represent the most relevant characteristics for the tasks of contextualization of the documentary groupings and units, management, document retrieval, dissemination and sharing of data about the historical photographs. Design/methodology/approach An OWL ontology, called Ontophoto, was constructed following an adaptation of the methodology proposed by Uschold and Gruninger and Gruninger and Fox. The ontology was implemented using Protégé 5.5 software. Next a Graph DB® graph database application (Ontotext) was created to generate a query system based on the SPARQL language. To validate the consistency and effectiveness of the model and ontology, a competency questions methodology has been applied using a sample from the Skogler photographic archive. Findings The model facilitates the generation of systems for dissemination and retrieval of iconographic data for historical research, overcoming some of the limitations with respect to the design of methods of content and contextual information representation for heritage photographic archives. Research limitations/implications This study is based on a sample. Future work should consider the implementation of the model on the totality of a photographic collection. Originality/value This paper presents a comprehensive ontological model that allows the creation of distributed systems of knowledge representation, which can be queried through SPARQL language.

A summer scholars institute to introduce urban underrepresented minority (URM) high school students to applied geosciences at Rutgers University in Newark, New Jersey, had the unanticipated effect ...

Being a teacher is a truly noble job. He is responsible not only to make the intelligent human beings in the field of science, but also good moral in this life. A human child who at first did not understand anything, in the presence of a teacher educated to understand life better and get to know the world. On the shoulders there are tasks and responsibilities for the future of a smarter and more intelligent generation. So noble work of a teacher as well as how heavy the duties and responsibilities of being a teacher. This is why not everyone can be a successful teacher. Only certain people who have a sense of love for children or learners and dedicated to the world of education are able to become a teacher. This is the person of a teacher who successfully teaches and educates in front of his students, the figure of a favorite teacher loved by his protege. The main capital to be a favorite teacher for students that is as follows: 1. Close to students, 2. Build a fun atmosphere, 3. Can play as a second parent, 4. Become a friend in learning, 5. Personality worth imitating, 6. Be affectionate, 7. Patience in teaching, 8. Not arrogant.

PurposeAlthough studies have improved understanding of the relation between external career mentoring and mentor work outcomes, an important question remains regarding whether this mentoring function influences mentor turnover intentions. The purpose of this paper is to investigate the impact of career mentoring outside the workplace on mentor turnover intentions.Design/methodology/approachData were collected from 101 working business professionals in the southeastern USA at two points in time who provided career mentoring to business student protégés in an eight-month university sponsored mentoring program.FindingsAs hypothesized, moderated mediation analysis indicated that amount of external career mentoring negatively related to mentor turnover intentions and that the indirect effect of external career mentoring on mentor turnover intentions via mentor work engagement was stronger when both mentor protégé satisfaction and meeting frequency were high vs low. A two-way interaction revealed that mentors reporting higher protégé satisfaction had lower turnover intentions when meeting frequency was high vs low.Originality/valueThe findings help clarify the external career mentoring and mentor turnover intentions relation and have valuable theoretical implications for research on the benefits external mentoring can provide mentors. They also have practical implications for using external mentoring to enhance mentor work engagement and reduce mentor turnover intentions.

This study explores the dynamics of developmental networks – the set of relationships a protégé names as taking an active interest in and action to advance his/her career. Although prior research has demonstrated the benefits of developmental networks, we know relatively little about how these networks change over time or the antecedents of developmental network dynamics. As research on career and adult development theory has suggested, professional development occurs within a dynamic, relational context; therefore, exploring network dynamics may enable future research to gain greater insight into how career trajectories unfold. In a 10-year, four-wave prospective longitudinal survey study of 136 U.S. business school students and their over 1600 relationships, we explore the dynamics of developmental networks, including the starting points (intercepts) and the rates of change (slopes) of the content of help provided (average career and psychosocial support) and the networks’ structure (network density, tie closeness, and communication frequency). Our multilevel longitudinal analyses show how these network characteristics change over time and how the content and structure of the support provided covary. Further, we explore individual-level and organizational/industry-level antecedents of network change trajectories. We conclude with implications of our discoveries for future theory-building and research on developmental networks, mentoring, and careers, and offer suggestions for consideration for practice.

Safety risk identification of metro construction is a knowledge-intensive process involving various stakeholders and communities. Currently, safety risk information related to decision making in metro construction is ill-structurally stored in various disordered formats, which hinders knowledge sharing and reuse. This study develops a domain ontology (SRI-Onto) to formalize safety risk knowledge in metro construction to support safety risk identification. An ontology development method with five steps is adopted. The SRI-Onto organizes safety risk knowledge into seven unified classes (i.e. project, construction activity, risk factor, risk, risk grade, risk consequence, and risk prevention measure). Defined classes, together with corresponding properties and relations, are coded using the Protege platform. Finally, the SRI-Onto is evaluated theoretically and practically, using criteria-based and application-based evaluations respectively. Results indicate that the SRI-Onto possesses the necessary and essential criteria to serve the purpose of knowledge sharing and reuse. Further, the SRI-Onto is predicted to be generally applicable to safety risk identification of metro construction.