Ontology Development Methodology Research Articles

More Effective Ontology Authoring with Test-Driven Development and the TDDonto2 Tool

Ontology authoring is a complex process, where commonly the automated reasoner is invoked for verification of newly introduced changes, therewith amounting to a time-consuming test-last approach. Test-Driven Development (TDD) for ontology authoring is a recent test-first approach that aims to reduce authoring time and increase authoring efficiency. Current TDD testing falls short on coverage of OWL features and possible test outcomes, the rigorous foundation thereof, and evaluations to ascertain its effectiveness. We aim to address these issues in one instantiation of TDD for ontology authoring. We first propose a succinct, logic-based specification of TDD testing and present novel TDD algorithms so as to cover also any OWL 2 class expression for the TBox and for the principal ABox assertions, and prove their correctness. The algorithms use methods from the OWL API directly such that reclassification is not necessary for test execution, therewith reducing ontology authoring time. The algorithms were implemented in TDDonto2, a Protégé plugin. TDDonto2 was evaluated by users, which demonstrated that modellers make significantly fewer errors with TDDonto2 compared to the standard Protégé interface and complete their tasks better using less time. Thus, the results indicate that TDD is a promising approach in an ontology development methodology.

Salaat Ontology: A Domain Ontology for Modeling Information Related to Prayers in Islam

Objectives: This work is directed towards development of a domain ontology and a semantic tool for Muslim’s prayer called Salaat. Methods/Statistical Analysis: The proposed ontology has been developed on Protégé tool based on TODE, a test driven ontology development methodology. A prototype application has been developed on JENA semantic web toolkit for the utilization of Salaat ontology. Findings: The proposed ontology comprises 113 concepts and 85 properties. A set of 40 queries were run to analyze the accuracy of proposed ontology. All the queries were successfully executed and extracted the desired information. Application/Improvements: The proposed tool can help a novice user to gain knowledge about Salaat (Islamic prayer). It becomes very easy to get the precise information through keyword based search. Keywords: Domain Ontology, Islam, Ontology, Prayer, Salaat

OntoDI: The Methodology for Ontology Development on Data Integration

The implementations of data integration in current days have many issues to be solved. Heterogeneity of data with non-standardization data, data conflicts between various data sources, data with a different representation, as well as semantic aspects problems are among the challenges and still open to research. Semantic data integration using ontology approach is considered as an appropriate solution to deal with semantic aspects problem in data integration. However, most methodologies for ontology development are developed to cover specific purpose and less suitable for common data integration implementation. This research offers an improved methodology for ontology development on data integration to deal with semantic aspects problem, called OntoDI. It is a continuation and improvement of the previous work about ontology development methods on agent system. OntoDI consists of three main parts, namely the pre-development, core-development and post-development, in which every part contains several phases. This paper describes the experiment of OntoDI in the electronic learning system domain. Using OntoDI, the development of ontology knowledge gives simpler phases, complete steps, and clear documentation for the ontology client. In addition, this ontology knowledge is also capable to overcome semantic aspect issues that happen in the sharing and integration process in education area.

Ontology Development Guide Using Protégé: BCS3263SQA at FSKKP

Ontology is a collection of formal terms that allows the communication between a machine and humans. It contains formal naming, definitions of types, properties and interrelations within a specific domain. Ontology allows knowledge visualisation of selected domain. However, developing an ontology requires a huge effort including designing its structure and the actual ontology development process. Software Quality Assurance (SQA) is a process that assure the reliability of a software and reduce its maintenance effort. Therefore, it is important for a computer science students to have a basic understanding on every aspect of SQA process. However, to master the SQA is a challenging task due to its wide coverage in the subject. To improve the learning process of the students in Universiti Malaysia Pahang, an ontology has been developed to provide an overview about the structure of the courses and help the students to visualise the entire course structure. In this paper, we discussed about the steps require for developing an ontology using Protege. We focus on the ontology development methodology and how to use Protege as an ontology development tools. As the result of the SQA ontology development, there are 5 classes and 40 terms. These terms help SQA class’s students in understanding the entire course structure.

Towards a common and semantic representation of e-portfolios

PurposeSince the early 1980s, a paradigm shift, caused by the work undertaken in the field of cognitive psychology, has occurred. This shift is known as the move from teacher-centered instruction to learner-centered or learning-centered instruction, and emphasizes the importance of building new knowledge on previous ones, interacting with peers, making meaningful and reflective learning and being engaged in his own path to foster learning. This new vision of teaching has created a need for new learning and assessment instruments that are better adapted to these pedagogical realities. In this context, the electronic portfolio or e-portfolio is one of the most versatile and effective tools that have been proposed for this purpose. More specifically, the interest in e-portfolios has grown considerably with the emergence of the competency-based approach and portfolio-based competency assessments. The purpose of this paper is to describe a semantic-based representation of e-portfolios, defined on the basis of official e-portfolio standards and specifications. Moreover, a comparative study of several well-known e-portfolio solutions has been carried out based on different facets, such as functional features, technical and organizational features. The objective is to identify those features that are mostly supported by e-portfolio solution providers and accordingly to gain a fairly accurate idea of the common structure of e-portfolios. In addition, the authors take advantage of an already implemented ontological model describing competency-related characteristics of learners and learning objects and combine it with the e-portfolio ontology, with a view to support a more reliable and authentic competency assessment.Design/methodology/approachThe proposed e-portfolio ontology was built following the ontology development methodology Methontology (Fernandez et al., 1997). In addition, it was constructed using the Protégé ontology environment (Protégé, 2007) and was implemented in OWL (Web Ontology Language) (Antoniou and Harmelen, 2004).FindingsThe proposed e-portfolio ontology provides humans with a shared vocabulary that enables capturing the most important elements in e-portfolios and serves as the basis for the semantic interoperability for machines.Originality/valueThe main advantage of the e-portfolio ontology lies in its ability to provide a common and semantically enriched representation of e-portfolio artifacts, thus facilitating the interoperability and exchange of competency evidences between different learning systems and platforms. In addition, capturing the semantics of e-portfolios helps to make them utilizable by intelligent applications.

A document-centric approach for developing the tolAPC ontology

BackgroundThere are many challenges associated with ontology building, as the process often touches on many different subject areas; it needs knowledge of the problem domain, an understanding of the ontology formalism, software in use and, sometimes, an understanding of the philosophical background. In practice, it is very rare that an ontology can be completed by a single person, as they are unlikely to combine all of these skills. So people with these skills must collaborate. One solution to this is to use face-to-face meetings, but these can be expensive and time-consuming for teams that are not co-located. Remote collaboration is possible, of course, but one difficulty here is that domain specialists use a wide-variety of different “formalisms” to represent and share their data – by the far most common, however, is the “office file” either in the form of a word-processor document or a spreadsheet.Here we describe the development of an ontology of immunological cell types; this was initially developed by domain specialists using an Excel spreadsheet for collaboration. We have transformed this spreadsheet into an ontology using highly-programmatic and pattern-driven ontology development. Critically, the spreadsheet remains part of the source for the ontology; the domain specialists are free to update it, and changes will percolate to the end ontology.ResultsWe have developed a new ontology describing immunological cell lines built by instantiating ontology design patterns written programmatically, using values from a spreadsheet catalogue.ConclusionsThis method employs a spreadsheet that was developed by domain experts. The spreadsheet is unconstrained in its usage and can be freely updated resulting in a new ontology. This provides a general methodology for ontology development using data generated by domain specialists.

A Systematic Analysis of Term Reuse and Term Overlap across Biomedical Ontologies.

Reusing ontologies and their terms is a principle and best practice that most ontology development methodologies strongly encourage. Reuse comes with the promise to support the semantic interoperability and to reduce engineering costs. In this paper, we present a descriptive study of the current extent of term reuse and overlap among biomedical ontologies. We use the corpus of biomedical ontologies stored in the BioPortal repository, and analyze different types of reuse and overlap constructs. While we find an approximate term overlap between 25-31%, the term reuse is only <9%, with most ontologies reusing fewer than 5% of their terms from a small set of popular ontologies. Clustering analysis shows that the terms reused by a common set of ontologies have >90% semantic similarity, hinting that ontology developers tend to reuse terms that are sibling or parent-child nodes. We validate this finding by analysing the logs generated from a Protégé plugin that enables developers to reuse terms from BioPortal. We find most reuse constructs were 2-level subtrees on the higher levels of the class hierarchy. We developed a Web application that visualizes reuse dependencies and overlap among ontologies, and that proposes similar terms from BioPortal for a term of interest. We also identified a set of error patterns that indicate that ontology developers did intend to reuse terms from other ontologies, but that they were using different and sometimes incorrect representations. Our results stipulate the need for semi-automated tools that augment term reuse in the ontology engineering process through personalized recommendations.

A framework to represent, capture, and trace ontology development processes

This article presents OntoTracED, a comprehensive framework to represent, capture and trace ontology development processes. It has three components: (i) a conceptual model that defines the framework foundations, (ii) an ontological engineering domain model (OEDM), which specifies and describes design objects, as well as those operations that are particular to a specific ontology development methodology, and (iii) a computational support environment, named TracED(aaS). This contribution first offers an overview of the ontology development process characteristics and then describes the main features of each OntoTracED component. The framework capabilities are illustrated by means of a case study addressing the use of TracED(aaS) throughout the development of an ontology of industrial interest. It is shown that this proposal makes a strong contribution in the ontological engineering field since the whole ontology development process, its history, rationale, and all the intermediate products can be captured in an integrated fashion.

ManuService ontology: a product data model for service-oriented business interactions in a cloud manufacturing environment

The ever-increasing distributed, networked and crowd-sourced cloud environment imposes the need of a service-oriented product data model for explicit representation of service requests in global manufacturing-service networks. The work in this paper aims to develop such a description framework for products based on semantic web technologies to facilitate the make-to-individual production strategy in a cloud manufacturing environment. A brief discussion on the requirements of a product data model in cloud manufacturing and research on product data modelling is given in the first part. A systematic ontology development methodology is then proposed and elaborated. The ontology called ManuService has been developed, consisting of all necessary concepts for description of products in a service-oriented business environment. These concepts include product specifications, quality constraints, manufacturing processes, organisation information, cost expectations, logistics requirements, and etcetera. ManuService ontology provides a module-based, reconfigurable, privacy-enhanced and standardised approach to modelling customised manufacturing service requests. An industrial case is presented to demonstrate possible applications using ManuService ontology. Comprehensive discussions are given thereafter, including a pilot application of a software package for semantic-based product design and a semantic web-based module for intelligent knowledge-based decision-making based on ManuService. ManuService forms the basis for collaborative service-oriented business interactions, intelligent and secure service provision in cloud manufacturing environment.

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

BackgroundThe Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies.Construction and contentRecent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class ‘cell in vitro’ have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning.Utility and discussionThe CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies—for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs.ConclusionsThe ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.

Proposal of an Hybrid Methodology for Ontology Development by Extending the Process Models of Software Engineering

Proposal of an Hybrid Methodology for Ontology Development by Extending the Process Models of Software Engineering

The Methodology for Ontology Development in Lesson Plan Domain

Ontology has been recognized as a knowledge representation mechanism that supports a semantic web application. The semantic web application that supports lesson plan construction is crucial for teachers to deal with the massive information sources from various domains on the web. Thus, knowledge in lesson plan domain needs to be represented accordingly so that the search on the web will retrieve relevant materials only. Essentially, such retrieval needs an appropriate representation of the domain problem. The emergence of semantic web technology provides a promising solution to improve the representation, sharing, and re-use of information to support decision making. Thus, the knowledge of lesson plan domain needs to be represented ontologically to support efficient retrieval of semantic web application in the domain of lesson plan. This paper presents a new methodology for ontology development representation of lesson plan domain to support semantic web application. The methodology is focused on the important model, tools, and techniques in each phase of the development. The methodology consists of four phases, namely requirements analysis, development, implementation, evaluation and maintenance.

A New Fuzzy Ontology Development Methodology (FODM) Proposal

There is an upsurge in applying fuzzy ontologies to represent vague information in the knowledge representation field. Current research in the fuzzy ontologies paradigm mainly focuses on developing formalism languages to represent fuzzy ontologies, designing fuzzy ontology editors, and building fuzzy ontology applications in different domains. Less focus falls on establishing a formal methodological approach for building fuzzy ontologies. Existing fuzzy ontology development methodologies, such as the IKARUS-Onto methodology and fuzzy ontomethodology, provide formalized schedules for the conversion from crisp ontologies into fuzzy ones. However, a formal guidance on how to build fuzzy ontologies from scratch still lacks in this paper. Therefore, this paper presents the first methodology, named fuzzy ontology development methodology (FODM), for developing fuzzy ontologies from scratch. The proposed FODM can provide a very good guideline for formally constructing fuzzy ontologies in terms of completeness, comprehensiveness, generality, efficiency, and accuracy. To explain how the FODM works and demonstrate its usefulness, a fuzzy seabed characterization ontology is built based on the FODM and described step by step.

A Study Investigating Knowledge-based Engineering Methodologies Analysis

now commonly accepted that building ontology is a key step in the development of knowledge based systems. A quite number of methodologies for ontology development have been proposed in the literature. However, this field still lacks mature methodologies which provide a clear vision for how to build ontologies. Most methodologies provide insufficient details about their adopted techniques and activities. This paper gives a preliminary guide which analysis and discusses some selected methodologies for ontology building. The important criteria and guidelines resulting from current literature have been adapted to perform this discussion and analysis. The performed analysis showed as outcomes that the existing methodology needs and additional hard work to be mature.

YAMO: Yet Another Methodology for large-scale faceted Ontology construction

Purpose – This paper aims to propose a brand new ontology development methodology, called Yet Another Methodology for Ontology (YAMO) and demonstrate, step by step, the building of a formally defined large-scale faceted ontology for food. Design/methodology/approach – YAMO is motivated by facet analysis and an analytico-synthetic classification approach. The approach ensures quality of the system precisely; it makes the system flexible, hospitable, extensible, sturdy, dense and complete. YAMO consists of two-way approaches: top-down and bottom-up. Based on YAMO, domain food, formally defined as large-scale ontology, is designed. To design the ontology and to define the scope and boundary of the domain, a group of people were interviewed to get a practical overview, which provided more insight to the theoretical understanding of the domain. Findings – The result obtained from evaluating the ontology is a very impressive one. Based on the study, it was found that 94 per cent of the user’s queries were successfully met. This shows the efficiency and effectiveness of the YAMO methodology. An evaluator opined that the ontology is very deep and exhaustive. Practical implications – The authors envision that the current work will have great implications on ontology developers and practitioners. YAMO will allow ontologists to construct a very deep, high-quality and large-scale ontology. Originality/value – This paper illustrates a brand new ontology development methodology and demonstrates how the methodology can be applied to build a large-scale high-quality domain ontology.

OMIT: dynamic, semi-automated ontology development for the microRNA domain.

As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

A Comparative Study on Ontology Development Methodologies towards Building Semantic Conflicts Detection Ontology for Heterogeneous Web Services

Semantic conflicts detection is considered to be one of the essential steps that should be carried out effectively, in order to pave the way towards establishing semantic interoperability between heterogeneous Web services. To achieve that, ontology plays the backbone of the detection process, which required to be implemented in a high quality manner. However, choosing a methodology to build this ontology is very difficult, since a considerable number of methodologies have been emerged to guide the ontology development process. Therefore, this study aims at reviewing and comparing the most accepted and used methodologies, with the aim of choosing an effective methodology from ontology engineering perspective to be recommended and used for building semantic conflicts detection ontology. Furthermore, to provide some useful insights for both theoretical and practical purposes to help ontology developers to choose the right methodology and to advance the state of the art. The comparison was performed against the common ontology development life cycle. The result of this survey and comparison recommend a methodology called METHONTOLOGY to be used for implementing semantic conflicts detection ontology.

Development of an Educational Ontology for Java Programming (JLEO) with a Hybrid Methodology Derived from Conventional Software Engineering Process Models

Semantic refers to W3C's vision of future web. It aims at a web of data, where information is linked up in such a way to be processable by devices and agents. In a wider canvas, semantic web can be seen as a huge engineering solution. Ontologies are playing the vital role in Semantic Web vision for its full-fledged implementation. Though lot of developments happened in this arena of ontology development in line with the implementation of semantic web, the standardization of process models, tools and methodologies are yet to be saturated. Researches in ontology engineering had pointed out that an effective ontology application development methodology with integrated tool support is a mandatory for its success. The researcher in his previous publication, proposed a hybrid methodology for ontology development by leveraging the well proven process models and methods of software engineering. This paper explains the philosophical, engineering aspects of the newly derived methodology and applies the same for the development of a Java Learning Educational Ontology (JLEO). JLEO organizes the learning hierarchy of Java Programming Language suitable to the related modules spread across the curriculum of Middle East College. An appropriate ontology editing tool has been used for the practical development of ontology.

Reuse existing ontologies in an ontology development process - an integration-oriented ontology development methodology

Ontologies are the building block of the Semantic Web and a diverse range of ontologies of different domains have been constructed and shared by the ontology community. In this regard it is not impractical to reuse existing ontologies that are available publicly instead of constructing ontology from scratch each time. This paper proposes and develops guidelines on how to select ontology merging and integration in an ontology development process. The paper aims to address the gap in literature where little information and guidance are available in determining how to reuse ontology through the process of ontology merging and integration. In addition the paper also proposes a semi-automatic way of performing ontology integration. An application scenario has been presented to illustrate how the proposed methodology is applied.

Grounding the Process of Ontology Concept Formulation in a Multi-perspective Social Context: Developing Ontology to Support Enhanced Collaboration in Community Tourism Event Management

Ontology development methodologies have hitherto failed to support rigorous concept formulation in social settings. This paper presents a method for concept formulation that is based on systematically analysing text describing social processes. The paper also illustrates the process using a textual fragment from a case study. We have found that by using grounded theory, general ontological theory, and a lexicon, we can find terms, definitions of terms, relations between terms, and hierarchies of terms in the text, which commonly exist in the social process of event management. We have also found that perspectives enable semantic ontology modularisation as an important tool in ontology concept formulation through partly clarifying terms emerging from the text, where misinterpretation may exist and where a more general, common ontology would detract from conceptual understanding of the domain. Copyright © 2013, Common Ground.