Ontology Engineering Tools Research Articles

A knowledge-based decision support system for inferring supportive treatment recommendations for diabetes mellitus.

Diabetes Mellitus (DM) is a significant risk, mostly causing blindness, kidney failure, heart attack, stroke, and lower limb amputation. A Clinical Decision Support System (CDSS) can assist healthcare practitioners in their daily effort and can improve the quality of healthcare provided to DM patients and save time. In this study, a CDSS that can predict DM risk at an early stage has been developed for use by health professionals, general practitioners, hospital clinicians, health educators, and other primary care clinicians. The CDSS infers a set of personalized and suitable supportive treatment suggestions for patients. Demographic data (e.g., age, gender, habits), body measurements (e.g., weight, height, waist circumference), comorbid conditions (e.g., autoimmune disease, heart failure), and laboratory data (e.g., IFG, IGT, OGTT, HbA1c) were collected from patients during clinical examinations and used to deduce a DM risk score and a set of personalized and suitable suggestions for the patients with the ontology reasoning ability of the tool. In this study, OWL ontology language, SWRL rule language, Java programming, Protégé ontology editor, SWRL API and OWL API tools, which are well known Semantic Web and ontology engineering tools, are used to develop the ontology reasoning module that provides to deduce a set of appropriate suggestions for a patient evaluated. After our first-round of tests, the consistency of the tool was obtained as 96.5%. At the end of our second-round of tests, the performance was obtained as 100.0% after some necessary rule changes and ontology revisions were done. While the developed semantic medical rules can predict only Type 1 and Type 2 DM in adults, the rules do not yet make DM risk assessments and deduce suggestions for pediatric patients. The results obtained are promising in demonstrating the applicability, effectiveness, and efficiency of the tool. It can ensure that necessary precautions are taken in advance by raising awareness of society against the DM risk.

Унифицированное применение методов онтологического инжиниринга в задачах обработки текстовых данных

Unified application issues of ontological engineering methods and tools for text data processing automation in 2 problems classes solving are considered. The first class is the relational database applications construction automation based on the necessary facts extracting directly from unstructured text documents collections in natural language. The second class is the text data processing automation in artificial languages in the program code verifying process for database applications. The information systems designing and developing problems, same as program code verifying problems, are complex for non-professional programmers. The text data processing problem solving automation is also relevant for professional programmers, because it significantly reduces the database applications development time. The ontologically controlled solution concept is proposed for these problems. An unified approach for problems solution and the tools demos implementation are described.

Mining Cardinality Restrictions in OWL

Abstract We present an approach to mine cardinality restriction axioms from an existing knowledge graph, in order to extend an ontology describing the graph. We compare frequency estimation with kernel density estimation as approaches to obtain the cardinalities in restrictions. We also propose numerous strategies for filtering obtained axioms in order to make them more available for the ontology engineer. We report the results of experimental evaluation on DBpedia 2016-10 and show that using kernel density estimation to compute the cardinalities in cardinality restrictions yields more robust results that using frequency estimation. We also show that while filtering is of limited usability for minimum cardinality restrictions, it is much more important for maximum cardinality restrictions. The presented findings can be used to extend existing ontology engineering tools in order to support ontology construction and enable more efficient creation of knowledge-intensive artificial intelligence systems.

ПРОЕКТИРОВАНИЕ СИСТЕМ ПРОГРАММНОГО ОБЕСПЕЧЕНИЯ ПОД УПРАВЛЕНИЕМ ОНТОЛОГИЙ: МОДЕЛИ, МЕТОДЫ, РЕАЛИЗАЦИИ

Ontology-driven software engineering is the scope of the paper. A retrospective analysis of the approaches, models and methods is carried out. In the first section, a brief overview of "classical" technologies, approaches and methods for software engineering is presented. It is shown that the emphasis of research and development is currently shifting from the field of technologies of programming towards the modeling of the software design processes, as well as towards the specifications and testing of the developed systems. It is outlined that the general trend in the domain is the use of methods and tools of ontology modeling of both the design processes per se and the specifications of the developed systems. The second section is devoted to a review of publications in the field of ontology-based software engineering. Such paradigms for modeling software development processes as Software Product Lines, plug-and-play software development - Component-Based Development, model-driven software engineering - Model-Driven Engineering, etc. are discussed. It is shown that "programming through generation", i.e. Generative Programming, is a general approach supporting the considered paradigms. It is shown that R&D in the domain of the semantic models of software engineering is currently focused on a new approach - Ontology-Based (-Driven) Software Engineering. Within the framework of this area, ontology engineering tools are developed along with modeling the software development processes. The scientific and technical perspectives of ontology driven software engineering are specified and discussed in the final part of the paper. In particular, it is outlined that the theoretical foundations of ontology-based modeling of software design processes form the solid basis for shifting the focus from the models of compiling the modules to their pattern-based generation from internal specifications. It is noted that the next trend in the field of OBSE-ODSE will be the usage of machine learning methods and tools to generate ontological models of software design.

Comparing ontology authoring workflows with Protégé: In the laboratory, in the tutorial and in the ‘wild’

The development of ontology engineering tools has traditionally lacked a user-centred perspective, instead being guided by the need to address particular gaps indicated by anecdotal evidence. This has typically resulted in prototypes that do not obtain traction beyond a narrow scope. Understanding the authoring patterns of ontology engineers is crucial to informing the development of ontology engineering tools that cater for the activity workflows of the users and, consequently, boosting the adoption of these tools. We report evidence about how Protégé is used across three different authoring settings, addressing the threats to validity of relying on a single user study. These settings address the continuum of expertise (from intermediate to expert users), the type of tasks (whether they are free-form or prescriptive) and the effect of the location (laboratory, tutorial or on their own) and how the studies are administered (whether or not there is a close supervision). While there are activity workflows that are particular to settings, the results indicate a number of core workflows that are common to all of them. We discuss actionable recommendations for ontology engineering tools in light of these results.

Comparing Ontology Authoring Workflows with Protege: In the Laboratory, in the Tutorial and in the ‘Wild’

The development of ontology engineering tools has traditionally lacked a user-centred perspective, instead being guided by the need to address particular gaps indicated by anecdotal evidence. This has typically resulted in prototypes that do not obtain traction beyond a narrow scope. Understanding the authoring patterns of ontology engineers is crucial to informing the development of ontology engineering tools that cater for the activity workflows of the users and, consequently, boosting the adoption of these tools. We report evidence about how Protege is used across three different authoring settings, addressing the threats to validity of relying on a single user study. These settings address the continuum of expertise (from intermediate to expert users), the type of tasks (whether they are free-form or prescriptive) and the effect of the location (laboratory, tutorial or on their own) and how the studies are administered (whether or not there is a close supervision). While there are activity workflows that are particular to settings, the results indicate a number of core workflows that are common to all of them. We discuss actionable recommendations for ontology engineering tools in light of these results.

Detecting User Profiles in Collaborative Ontology Engineering Using a User’s Interactions

Collaborative ontology-engineering methods usually prescribe a set of processes, activities, stakeholders, and the roles each stakeholder plays in these activities. We, however, believe that (a) the stakeholder community of each ontology-engineering project is different, and (b) one can observe different types of user behavior. It may thus very well be that the prescribed set of stakeholder types and roles do not suffice. If one were able to identify these user behavior types, which we will call user profiles, one can compliment or revisit those predefined roles. For instance, those user profiles can be used to provide customized interfaces for optimizing activities in certain ontology-engineering projects. We present a method for discovering different user profiles based on the interactions users have with each other on a collaborative ontology-engineering environment. Our approach clusters users based on the types of interactions they perform, which are retrieved from datasets that were annotated with an interaction ontology—built on top of SIOC—that we have developed. We demonstrate our method using the database of two instances of the GOSPL ontology-engineering tool. The databases contain the interactions of two distinct ontology-engineering projects involving, respectively, 42 and 36 users. For each dataset, we discuss the findings by analyzing the different clusters. We found that we are able to discover different user profiles, indicating that the approach we have taken is viable, though more experiments are needed to validate the results and to discover patterns across ontology-engineering projects.

Ontology Engineering and Development Aspects: A Survey

Ontology can be defined as hierarchical representation of classes, sub classes, their properties and instances. It has led to understanding the concepts of given domain, deriving relationships and representing them in machine interpretable language. Ontologies are associated with different languages that are used in mapping of multiple ontologies. Several applications of ontologies have led towards realization of semantic web. The current web (2.0) is approaching towards semantic web (3.0) that performs intelligent search and stores results in distributed databases. The paper makes readers aware of various aspects of ontology like types of ontology, ontology development life cycle phases, activities involved in ontology development and ontology engineering tools. Ontology engineering contributes to meaningful search and provides with open source tools for deploying and building ontologies.

Research on Functional Analysis Useful for Utilizing TRIZ

The functional analysis viewpoint is essential in ensuring that the customer has a voice in product design plans. Functional analysis is, therefore, very important in TRIZ, quality function deployment (QFD) and value engineering (VE), all of which are frequently used in design activities. People who are not used to conducting functional analysis may spend a great deal of time identifying a product's necessary functions, and this can have an adverse effect on the speed of product development and improvement activities. In light of this, this paper proposes a new methodology for effectively identifying—or “defining”—necessary functions (hereinafter referred to as “definition of functions”), based on Function and Behavior Representation Language (FBRL), which is a tool for ontology engineering. The paper also proposes a method for utilizing a functional diagram, which is used in functional analysis, in selecting various natural science effects in an Effects database, as well as in selecting features in a contradiction matrix. The latter part of this paper introduces a new method for definition of function and a method for using functional diagrams by examining their application in the field of agricultural machinery.

Using a Method and Tool for Hybrid Ontology Engineering: an Evaluation in the Flemish Research Information Space

We report on the results of the application of a method and tool for ontology construction in the research information domain, held in the context of an open data initiative of Flanders. The method emphasizes the use of natural language descriptions of concepts next to formal descriptions, and uses - for the formal definitions - a fact-oriented formalism grounded in natural language. In this experiment, a group of 36 participants were divided into different groups to build ontologies to establish semantic interoperability between autonomously developed research information systems and to annotate the data of an existing system provided by a public administration. User satisfaction of the tool was measured with the Post-Study System Usability Questionnaire. The result of that survey was that the participants were generally pleased with the platform, with its usefulness scoring best. As for the developed ontologies, their use was demonstrated by the applications developed by the participants. The experiment showed that having a formalism grounded in natural language leverages the ontology construction process for the stakeholders. The experiment also shows that a method needs to take into account the collaborative building of workflows within ontology projects, as not all ontology-engineering projects are alike.

PragmatiX

With the emergence of tools for collaborative ontology engineering, more and more data about the creation process behind collaborative construction of ontologies is becoming available. Today, collaborative ontology engineering tools such as Collaborative Protégé offer rich and structured logs of changes, thereby opening up new challenges and opportunities to study and analyze the creation of collaboratively constructed ontologies. While there exists a plethora of visualization tools for ontologies, they have primarily been built to visualize aspects of the final product (the ontology) and not the collaborative processes behind construction (e.g. the changes made by contributors over time). To the best of our knowledge, there exists no ontology visualization tool today that focuses primarily on visualizing the history behind collaboratively constructed ontologies. Since the ontology engineering processes can influence the quality of the final ontology, we believe that visualizing process data represents an important stepping-stone towards better understanding of managing the collaborative construction of ontologies in the future. In this application paper, we present a tool - PragmatiX - which taps into structured change logs provided by tools such as Collaborative Protégé to visualize various pragmatic aspects of collaborative ontology engineering. The tool is aimed at managers and leaders of collaborative ontology engineering projects to help them in monitoring progress, in exploring issues and problems, and in tracking quality-related issues such as overrides and coordination among contributors. The paper makes the following contributions: (i) we present PragmatiX, a tool for visualizing the creation process behind collaboratively constructed ontologies (ii) we illustrate the functionality and generality of the tool by applying it to structured logs of changes of two large collaborative ontology-engineering projects and (iii) we conduct a heuristic evaluation of the tool with domain experts to uncover early design challenges and opportunities for improvement. Finally, we hope that this work sparks a new line of research on visualization tools for collaborative ontology engineering projects.

Personalized Knowledge Mining in Large Text Sets

The paper starts with a discussion of the concept of knowledge engineering, in particular ontological engineering. Consequently, the paper presents assumptions accepted as a basis for a group research on a radically personalized system of ontological knowledge mining, relying on the perspective of human centered computing and combining ontological concepts of the user with an ontology resulting from an automatic classification of a given set of textual data. The paper presents a pilot system PrOnto that supports research work in two aspects: searching for information interesting for a user according to her/his personalized ontological profile, and supporting research cooperation in a group of users (Virtual Research Community) according, e.g., to a comparison of such personalized ontological profiles. The paper concludes with suggestions concerning diverse applications of ontological engineering tools and future work.

Supporting Domain Experts to Construct Conceptual Ontologies: A Holistic Approach

A recent trend in ontology engineering research aims at encouraging the active participation of domain experts in the ontology creation process. Ontology construction methodologies together with appropriate tools and technologies, such as controlled natural languages, semantic wikis, intelligent user interfaces and social computing, are being proposed to enable the direct input from domain experts and to minimize the dependency on knowledge engineers at every step of ontology development. The time is ripe for consolidating methodological and technological advancements to create intuitive ontology engineering tools which can make Semantic Web technologies usable by a wide variety of people without formal knowledge engineering skills. A novel, holistic approach to facilitate the involvements of domain experts in the ontology authoring process is presented here. It integrates (i) an ontology construction methodology, (ii) the use of a controlled natural language, and (iii) appropriate tool support. The integrated approach is illustrated with the design, implementation and evaluation of ROO - a unique ontology authoring tool which combines intelligent techniques to assist domain experts in constructing ontologies. The benefits and limitations of the proposed approach are analyzed based on user studies with ROO. A broader discussion is provided pointing at issues to be taken into account when assisting the involvement of domain experts in ontology construction.

Supporting domain experts to construct conceptual ontologies: A holistic approach

A recent trend in ontology engineering research aims at encouraging the active participation of domain experts in the ontology creation process. Ontology construction methodologies together with appropriate tools and technologies, such as controlled natural languages, semantic wikis, intelligent user interfaces and social computing, are being proposed to enable the direct input from domain experts and to minimize the dependency on knowledge engineers at every step of ontology development. The time is ripe for consolidating methodological and technological advancements to create intuitive ontology engineering tools which can make Semantic Web technologies usable by a wide variety of people without formal knowledge engineering skills. A novel, holistic approach to facilitate the involvements of domain experts in the ontology authoring process is presented here. It integrates (i) an ontology construction methodology, (ii) the use of a controlled natural language, and (iii) appropriate tool support. The integrated approach is illustrated with the design, implementation and evaluation of ROO – a unique ontology authoring tool which combines intelligent techniques to assist domain experts in constructing ontologies. The benefits and limitations of the proposed approach are analyzed based on user studies with ROO. A broader discussion is provided pointing at issues to be taken into account when assisting the involvement of domain experts in ontology construction.

An Extension of the Environment for Building/Using Ontologies "Hozo" toward Practical Ontology Engineering - Focused on Practical Issues

Recently, ontology has attracted attention as an important technology for knowledge infrastructure and semantic processing, and a lot of ontologies have been constructed in various domains. At the same time, ontological theories, technologies, and ontology engineering tools have been developed by not only researchers but also practitioners. We also have been investigating ontological theories and developed a computer environment for building/using ontologies named ``Hozo'' which is based on the ontological theory of roles. Hozo has been used for practical ontology construction in various domains such as clinical medicine, bioinformatics, environmental engineering and so on. These practices of ontology development have raised many issues of ontology construction and utilization in both theoretical and technical points of view. We have solved them by extending our theories and functions of the system. It means we refined usability and reliability of Hozo through these practical experiences. In this paper, we focus on theoretical issues of ontology construction and discuss some extensions of ontological theories concerning representation of multiple inheritance and instances. First, we introduce IS-A relation which represents a relation weaker than is-a relation in the sense that it prohibits inheritance of identity, and we allow users to represent multiple inheritance using not usual strong is-a relation but IS-A relation. Then we investigate the validity of the representation using IS-A through ontological analysis of three utilization patterns of it. Next, we introduce two kinds of new representation of instances: ``simplified instance representation'' and ``#-(species) operator''. Users can use these representations for referring to instances in concept (class) definitions. These theoretical extensions would contribute to well-organized construction of ontologies in practical ontology engineering.

An Extension of the Environment for Building/Using Ontologies Hozo'' toward Practical Ontology Engineering - Focused on Theoretical Issues

Recently, ontology has attracted attention as an important technology for knowledge infrastructure and semantic processing, and a lot of ontologies have been constructed in various domains. At the same time, ontological theories, technologies, and ontology engineering tools have been developed by not only researchers but also practitioners. We also have been investigating ontological theories and developed a computer environment for building/using ontologies named ``Hozo'' which is based on the ontological theory of roles. Hozo has been used for practical ontology construction in various domains such as clinical medicine, bioinformatics, environmental engineering and so on. These practices of ontology development have raised many issues of ontology construction and utilization in both theoretical and technical points of view. We have solved them by extending our theories and functions of the system. It means we refined usability and reliability of Hozo through these practical experiences. In this paper, we focus on theoretical issues of ontology construction and discuss some extensions of ontological theories concerning representation of multiple inheritance and instances. First, we introduce IS-A relation which represents a relation weaker than is-a relation in the sense that it prohibits inheritance of identity, and we allow users to represent multiple inheritance using not usual strong is-a relation but IS-A relation. Then we investigate the validity of the representation using IS-A through ontological analysis of three utilization patterns of it. Next, we introduce two kinds of new representation of instances: ``simplified instance representation'' and ``#-(species) operator''. Users can use these representations for referring to instances in concept (class) definitions. These theoretical extensions would contribute to well-organized construction of ontologies in practical ontology engineering.

TOWARDS PATTERN-BASED REASONING FOR FRIENDLY ONTOLOGY DEBUGGING

Reasoning with ontologies is a challenging task specially for non-logic experts. When checking whether an ontology contains rules that contradict each other, current description logic reasoners can only provide a list of the unsatisfiable concepts. Figuring out why these concepts are unsatisfiable, which rules cause conflicts, and how to resolve these conflicts, is all left to the ontology modeler himself. The problem becomes even more challenging in case of large or medium size ontologies, because an unsatisfiable concept may cause many of its neighboring concepts to be unsatisfiable. The goal of this article is to empower ontology engineering with a user-friendly reasoning mechanism. We propose a pattern-based reasoning approach, which offers 9 patterns of constraint contradictions that lead to unsatisfiability in Object-role (ORM) models. The novelty of this approach is not merely that constraint contradictions are detected, but mainly that it provides the causes and suggestions to resolve contradictions. The approach is implemented in the DogmaModeler ontology engineering tool, and tested in building the CCFORM ontology. We discuss that, although this pattern-based reasoning covers most of contradictions in practice, compared with description logic based reasoning, it is not complete. We argue and illustrate both approaches, pattern-based and description logic-based, their implementation in the DogmaModeler, and conclude that both complement each other from a methodological perspective.

Bridging the gap between the model-driven architecture and ontology engineering

Software engineers have many robust commercial tools available to them for creating and manipulating models. Due to the widespread adoption of the Object Management Group (OMG) standards for metamodel definition, model serialisation and programmatic access to models, many of these tools are interoperable. Currently this is not the case for ontology engineering tools. This paper discusses the potential benefits of making the OMG's model-driven architecture (MDA) technology applicable to ontology engineering, and in particular, describes a technique for converting ontologies serialised using the XML metadata interchange (XMI) format to an equivalent representation using the resource description framework (RDF), without any loss of information. The resulting models can then be analysed and transformed using existing RDF tools. The technique is applicable to any ontology modelling language that has its abstract syntax defined using the OMG's meta-object facility (MOF) model. This research helps to bridge the gap between the MDA and ontology engineering by providing a technique based on the familiar RDF language for defining transformations between other types of model (such as UML) and ontologies, between different ontology modelling languages, or to modify ontologies without changing the language.

Ontology Learning for Chinese Information Organization and Knowledge Discovery in Ethnology and Anthropology

This paper presents an ontology learning architecture that reflects the interaction between ontology learning and other applications such as ontology-engineering tools and information systems. Based on this architecture, we have developed a prototype system CHOL: a Chinese ontology learning tool. CHOL learns domain ontology from Chinese domain specific texts. On the one hand, it supports a semi-automatic domain ontology acquisition and dynamic maintenance, and on the other hand, it supports an auto-indexing and auto-classification of Chinese scholarly literature. CHOL has been applied in ethnology and anthropology for Chinese information organization and knowledge discovery.

MDA-based Automatic OWL Ontology Development

This paper presents an eXtensible Stylesheet Language Transformation (XSLT)-based approach for automatic generation of the Web Ontology Language (OWL) from a UML model. Similar solutions that treat this problem are mostly partial since they do not use full metamodeling potentials. Although they emphasize the notion of the use UML for ontology development and propose necessary transformations into Semantic Web languages (e.g., RDF Schema, DAML, DAML+OIL), their UML models must be further refined using ontology-specialized tool. None of these approaches enables instance modeling and generation of OWL ontologies. In our efforts to make ontological and software engineering techniques closer, we have firstly defined ontology metamodeling architecture using Model Driven Architecture (MDA) concepts. This architecture consists of the Ontology Definition Metamodel defined using Meta Object Facility (MOF) and based on the OWL, as well as the related Ontology UML Profile (OUP). A transformation, that we present here, extends this metamodeling architecture and transforms an ontology from its OUP definition (i.e., XML Metadata Interchange – XMI) into the OWL description. Accordingly, we illustrate how an OUP-developed ontology can be shared with ontological engineering tools (i.e., Protege).