Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

a survey

Building ontologies in a collaborative and increasingly community-driven fashion has become a central paradigm of modern ontology engineering. This understanding of ontologies and ontology engineering processes is the result of intensive theoretical and empirical research within the Semantic Web community, supported by technology developments such as Web 2.0. Over 6 years after the publication of the first methodology for collaborative ontology engineering, it is generally acknowledged that, in order to be useful, but also economically feasible, ontologies should be developed and maintained in a community-driven manner, with the help of fully-fledged environments providing dedicated support for collaboration and user participation. Wikis, and similar communication and collaboration platforms enabling ontology stakeholders to exchange ideas and discuss modeling decisions are probably the most important technological components of such environments. In addition, process-driven methodologies assist the ontology engineering team throughout the ontology life cycle, and provide empirically grounded best practices and guidelines for optimizing ontology development results in real-world projects. The goal of this article is to analyze the state of the art in the field of collaborative ontology engineering. We will survey several of the most outstanding methodologies, methods and techniques that have emerged in the last years, and present the most popular development environments, which can be utilized to carry out, or facilitate specific activities within the methodologies. A discussion of the open issues identified concludes the survey and provides a roadmap for future research and development in this lively and promising field

Collaborative ontology engineering: a survey

Building ontologies in a collaborative and increasingly community-driven fashion has become a central paradigm of modern ontology engineering. This understanding of ontologies and ontology engineering processes is the result of intensive theoretical and empirical research within the Semantic Web community, supported by technology developments such as Web 2.0. Over 6 years after the publication of the first methodology for collaborative ontology engineering, it is generally acknowledged that, in order to be useful, but also economically feasible, ontologies should be developed and maintained in a community-driven manner, with the help of fully-fledged environments providing dedicated support for collaboration and user participation. Wikis, and similar communication and collaboration platforms enabling ontology stakeholders to exchange ideas and discuss modeling decisions are probably the most important technological components of such environments. In addition, process-driven methodologies assist the ontology engineering team throughout the ontology life cycle, and provide empirically grounded best practices and guidelines for optimizing ontology development results in real-world projects. The goal of this article is to analyze the state of the art in the field of collaborative ontology engineering. We will survey several of the most outstanding methodologies, methods and techniques that have emerged in the last years, and present the most popular development environments, which can be utilized to carry out, or facilitate specific activities within the methodologies. A discussion of the open issues identified concludes the survey and provides a roadmap for future research and development in this lively and promising fiel

An ontological framework for the formal representation and management of human stress knowledge

There is a great deal of information on the topic of human stress which is embedded within numerous papers across various databases. However, this information is stored, retrieved, and used often discretely and dispersedly. As a result, discovery and identification of the links and interrelatedness between different aspects of knowledge on stress is difficult. This restricts the effective search and retrieval of desired information. There is a need to organize this knowledge under a unifying framework, linking and analysing it in mutual combinations so that we can obtain an inclusive view of the related phenomena and new knowledge can emerge. Furthermore, there is a need to establish evidence-based and evolving relationships between the ontology concepts.Previous efforts to classify and organize stress-related phenomena have not been sufficiently inclusive and none of them has considered the use of ontology as an effective facilitating tool for the abovementioned issues.There have also been some research works on the evolution and refinement of ontology concepts and relationships. However, these fail to provide any proposals for an automatic and systematic methodology with the capacity to establish evidence-based/evolving ontology relationships.In response to these needs, we have developed the Human Stress Ontology (HSO), a formal framework which specifies, organizes, and represents the domain knowledge of human stress. This machine-readable knowledge model is likely to help researchers and clinicians find theoretical relationships between different concepts, resulting in a better understanding of the human stress domain and its related areas. The HSO is formalized using OWL language and Protégé tool.With respect to the evolution and evidentiality of ontology relationships in the HSO and other scientific ontologies, we have proposed the Evidence-Based Evolving Ontology (EBEO), a methodology for the refinement and evolution of ontology relationships based on the evidence gleaned from scientific literature. The EBEO is based on the implementation of a Fuzzy Inference System (FIS).Our evaluation results showed that almost all stress-related concepts of the sample articles can be placed under one or more category of the HSO. Nevertheless, there were a number of limitations in this work which need to be addressed in future undertakings.The developed ontology has the potential to be used for different data integration and interoperation purposes in the domain of human stress. It can also be regarded as a foundation for the future development of semantic search engines in the stress domain

Ontology-based information standards development

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Standards may be argued to be important enablers for achieving interoperability as they aim to provide unambiguous specifications for error-free exchange of documents and information. By implication, therefore, it is important to model and represent the concept of a standard in a clear, precise and unambiguous way. Although standards development organisations usually provide guidelines for the process of developing and approving standards, they are usually more concerned with administrative aspect of the process. As a consequence, the state-of-the-art lacks practical support for developing the structure and content of a standard specification. In short, there is no systematic development method currently available: (a) For developing the conceptual model underpinning a standard; and/or (b) to guide a group of stakeholders to develop a standard specification. Semantic interoperability is considered to be an essential factor for effective interoperation – the ability to achieve semantic interoperability effectively and efficiently being strongly equated with quality by some. Semantics require that the meaning of terms, their relationships and also the restrictions and rules in the standards should be clearly defined in the early stages of standard development and act as a basis for the latter stages. This research proposes that ontology can help standards developers and stakeholders to address the issues of improving conceptual models and providing a robust and shared understanding of the domain. This thesis presents OntoStanD, a comprehensive ontology-based standards development methodology, which utilises the best practices of the existing ontology creation methods. The potential value of OntoStanD is in providing a comprehensive, clear and unambiguous method for developing robust information standards, which are more test friendly and of higher quality. OntoStanD also facilitates standards conformance testing and change management, impacts interoperability and also assists in improved communication among the standards development team. Last, OntoStanD provides an approach that is repeatable, teachable and potentially general enough for creating any kinds of information standard.Fujitsu Laboratories of Europe Ltd, Google Anitaborg Memorial Scholarshi

Collaborative Ontology Engineering Methodologies for the Development of Decision Support Systems: Case Studies in the Healthcare Domain

New models and technological advances are driving the digital transformation of healthcare systems. Ontologies and Semantic Web have been recognized among the most valuable solutions to manage the massive, various, and complex healthcare data deriving from different sources, thus acting as backbones for ontology-based Decision Support Systems (DSSs). Several contributions in the literature propose Ontology engineering methodologies (OEMs) to assist the formalization and development of ontologies, by providing guidelines on tasks, activities, and stakeholders' participation. Nevertheless, existing OEMs differ widely according to their approach, and often lack of sufficient details to support ontology engineers. This paper performs a meta-review of the main criteria adopted for assessing OEMs, and major issues and shortcomings identified in existing methodologies. The key issues requiring specific attention (i.e., the delivery of a feasibility study, the introduction of project management processes, the support for reuse, and the involvement of stakeholders) are then explored into three use cases of semantic-based DSS in health-related fields. Results contribute to the literature on OEMs by providing insights on specific tools and approaches to be used when tackling these issues in the development of collaborative OEMs supporting DSS

Problem Solving Evolutionary Method for Ontology Knowledge Representation with Protégé-2000

This paper studies the knowledge representation with ontology method in the Protégé 2000 system. We first analyzed the various ontological methods for knowledge representation. Then we described the OWL method used in Protégé 2000 for knowledge representation. We proposed the new method named problem-solving evolutionary method (PSEM) for knowledge representation in which it is based the OWL of Protégé 2000. Then we design the interface between the Racer inference engine and the Protégé 2000. Based on the interface built, we can use the Racer inferring engine to reasoning the knowledge. We use the PSEM to experiment the professional domain knowledge of MIS in which it is based undergraduate level. Experiments have shown that PSEM based on the Protégé 2000 is able to represent some domain knowledge well and built knowledge with OWL can be inferred by the Racer

A novel and validated agile Ontology Engineering methodology for the development of ontology-based applications

The goal of this Thesis is to investigate the status of Ontology Engineering, underlining the main key issues still characterizing this discipline. Among these issues, the problem of reconciling macro-level methodologies with authoring techniques is pivotal in supporting novel ontology engineers. The latest approach characterizing ontology engineering methodologies leverages the agile paradigm to support collaborative ontology development and deliver efficient ontologies. However, so far, the investigations in the current support provided by these methodologies and the delivery of efficient ontologies have not been investigated. Thus, this work proposes a novel framework for the investigation of agile methodologies, with the objective of identifying the strong point of each agile methodology and their limitations. Leveraging on the findings of this analysis, the Thesis introduces a novel agile methodology – AgiSCOnt – aimed at tackling some of the key issues characterizing Ontology Engineering and weaknesses identified in existing agile approaches. The novel methodology is then put to the test as it is adopted for the development of two new domain ontologies in the field of health: the first is dedicated to patients struggling with dysphagia, while the second addresses patients affected by Chronic obstructive pulmonary disease.The goal of this Thesis is to investigate the status of Ontology Engineering, underlining the main key issues still characterizing this discipline. Among these issues, the problem of reconciling macro-level methodologies with authoring techniques is pivotal in supporting novel ontology engineers. The latest approach characterizing ontology engineering methodologies leverages the agile paradigm to support collaborative ontology development and deliver efficient ontologies. However, so far, the investigations in the current support provided by these methodologies and the delivery of efficient ontologies have not been investigated. Thus, this work proposes a novel framework for the investigation of agile methodologies, with the objective of identifying the strong point of each agile methodology and their limitations. Leveraging on the findings of this analysis, the Thesis introduces a novel agile methodology – AgiSCOnt – aimed at tackling some of the key issues characterizing Ontology Engineering and weaknesses identified in existing agile approaches. The novel methodology is then put to the test as it is adopted for the development of two new domain ontologies in the field of health: the first is dedicated to patients struggling with dysphagia, while the second addresses patients affected by Chronic obstructive pulmonary disease

A Creative Data Ontology for the Moving Image Industry

The moving image industry produces an extremely large amount of data and associated metadata for each media creation project, often in the range of terabytes. The current methods used to organise, track, and retrieve the metadata are inadequate, with metadata often being hard to find. The aim of this thesis is to explore whether there is a practical use case for using ontologies to manage metadata in the moving image industry and to determine whether an ontology can be designed for such a purpose and can be used to manage metadata more efficiently to improve workflows. It presents a domain ontology, hereby referred to as the Creative Data Ontology, engineered around a set of metadata fields provided by Evolutions, Double Negative (DNEG), and Pinewood Studios, and four use cases. The Creative Data Ontology is then evaluated using both quantitative methods and qualitative methods (via interviews) with domain and ontology experts.Our findings suggest that there is a practical use case for an ontology-based metadata management solution in the moving image industry. However, it would need to be presented carefully to non-technical users, such as domain experts, as they are likely to experience a steep learning curve. The Creative Data Ontology itself meets the criteria for a high-quality ontology for the sub-sectors of the moving image industry domain that it provides coverage for (i.e. scripted film and television, visual effects, and unscripted television) and it provides a good foundation for expanding into other sub-sectors of the industry, although it cannot yet be considered a ``standard'' ontology. Finally, the thesis presents the methodological process taken to develop the Creative Data Ontology and the lessons learned during the ontology engineering process which can be valuable guidance for designers and developers of future metadata ontologies. We believe such guidance could be transferable across many domains where an ontology of metadata is required, which are unrelated to the moving image industry. Future research may focus on assisting non-technical users to overcome the learning curve, which may also also applicable to other domains that may choose to use ontologies in the future

Development of patient-practitioner assistive communications (PPAC) ontology for type 2 diabetes management

Communication in primary care is a key area of healthcare slow to adopt new technology to improve understanding between the patient and healthcare practitioner. Patients whose cultural background and regular form of dialectal communication are far removed from that of mainstream society are particularly disadvantaged by this during the patient-practitioner interview encounter (PPIE). In this paper, we present an assistive communications technology (ACT) framework for PPIE developed using a Type-2 Diabetes Management Patient-Practitioner Assistive Communications (T2DMPPAC) ontology in order to help both Aboriginal patient and non-Aboriginal practitioner optimise their pre-encounter, during-encounter and post-encounter communication. The T2DMPPAC architecture provides knowledge and presents it in a manner that is easily accessible and understood by the user (patients and practitioners) as well as accompanying carers, and as appropriate, interpreters. An example of bi-directional mapping of concepts to language during a PPIE session is shown using the ontology