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Research on context‐aware systems design has received significant attention lately. One of the research directions on context‐aware systems is towards context‐aware frameworks adapted to domain‐specific requirements, aiming to improve their applicability in a variety of applications, which share common requirements. The purpose of this paper is to present the design of a domain‐specific context‐aware platform supporting context acquisition, presentation and rule‐based control.

The proposed platform uses a formal context model, based on ontologies description, aiming to provide a common representation of contextual information, facilitating thus integration and reusability in application domains, which embrace a common set of requirements. A context‐aware system has been built upon a well defined data model, which inherits a list of offered functionalities and/or services at the acquisition, presentation and reasoning level. The presented platform entails an event‐driven context‐based inference mechanism aiming to enable automated reasoning.

The proposed platform has been applied in two different case studies, aiming to provide a proof of concept towards the applicability of the proposed framework in different application areas through the offered integration and adaptation mechanisms. Evaluation results, in the frame of these case studies, show the ease of using the platform and its acceptable performance in practice.

As context‐aware applications within specific domains share common requirements, it becomes mandatory to offer solutions, like the proposed in this paper, which can be easily adapted to application semantics and can be reused with different levels of abstractions in order to meet specific requirements. The present paper proposes a domain‐specific platform, which applies on a variety of application types with a common set of requirements.

This study applies digital humanity tools (Gephi and Protégé) for establishing and visualizing ontologies in the cultural heritage domain. According to that, this study aims to develop a novel evaluation approach using five ontology indicators (data overview, visual presentation, highlight links, scalability and querying) to evaluate the knowledge structure presentation of cultural heritage ontology.

The researchers collected and organized 824 pieces of government’s open data (GOD), converted GOD into the resource description framework format, applied Protégé and Gephi to establish and visualize cultural heritage ontology. After ontology is built, this study recruited 60 ontology participants (30 from information and communications technology background; 30 from cultural heritage background) to operate this ontology and gather their different perspectives of visual ontology.

Based on the ontology participant’s feedback, this study discovered that Gephi is more supporting than Protégé when visualizing ontology. Especially in data overview, visual presentation and highlight links dimensions, which is supported visualization and demonstrated ontology class hierarchy and property relation, facilitated the wider application of ontology.

This study offers two contributions. First, the researchers analyzed data on East Asian architecture with novel digital humanities tools to visualize ontology for cultural heritage. Second, the study collected participant’s feedback regarding the visualized ontology to enhance its design, which can serve as a reference for future ontological development.

The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area.

An ontology for recommending learning material was integrated in the organizational learning environment based on ontology. An experiment was performed with 15 experts and 84 learners. Experts and learners were asked to classify 30 learning material related to Software Engineering area. The results obtained from experts and learners were compared with the ontology results.

Among 30 learning materials evaluated, 24 learning materials got closer to the expert classification using the ontology than using the learners’ manual classification. The learners had difficulties in correctly classifying the learning materials according to the knowledge area applied.

In an autonomous collaborative environment without a tutor responsible for organizing the learning materials shared by collaborators, an ontology may be an auxiliary mechanism to support automatic learning material classification. The proposed ontology uses recommendations given by the collaborators to get the correct knowledge area classification. The correct classification may support retrieval of appropriate learning materials according to the learners’ needs.

The purpose of this paper is to examine the integration of digital library (DL) technologies with ontology‐based knowledge representation in providing semantic rich information access (IA) in e‐learning. DL technologies have powerful and flexible content management and access functionalities, whereas ontology helps teachers and students to link content materials to their learning objectives. This paper demonstrates that the integration provides a powerful and meaningful e‐learning environment.

DiLight is designed as an interactive e‐learning system that integrates DL and ontology technologies. By conducting comparative experiments involving DiLight in students' actual learning process, the authors examined the advantages and limitations of DiLight in e‐learning.

Compared to a widely used e‐learning environment, DiLight can provide significantly better support for students' complex IA tasks because DiLight is more useful for relationship discovery and problem solving. DiLight is also effective even when students were either less familiar with tasks or felt that they were more difficult. There is no single best access method for all learning situations. Therefore, multiple IA methods should be built into e‐learning systems. Although most of time the search was the first choice of the students, ontology‐based methods were useful in supporting them to complete their tasks too.

This is a comparative empirical study using an interactive e‐learning system called DiLight to explore the usage of integrated DL and ontology in e‐learning. The experiment results demonstrate the value of the multiple IA methods provided by DL, and the usefulness of integrating DL with ontology.

The paper shows how access to knowledge can be enhanced by using a set of innovative approaches and technologies based on the semantic web.

Emerging trends in knowledge access are considered followed by a description of how ontologies and semantics can contribute. A set of tools is then presented which is based on semantic web technology. For each of these tools a detailed description of the approach is given together with an analysis of related and future work as appropriate.

The tools presented are at the prototype stage but can already show how knowledge access can be improved by allowing users to more precisely express what they are looking for and by presenting to them in a form that is appropriate to their current context.

The tools show promising results in improving access to knowledge which will be further evaluated within a practical setting. The tools will be integrated and trialled as part of case studies within the SEKT project. This will allow their usability and practical applicability to be measured.

Ontologies as a form of knowledge representation are increasing in importance. Knowledge management, and in particular knowledge access, will benefit from their widespread acceptance. The use of open standards and compatible tools in this area will be important to support interoperability and widespread access to disparate knowledge repositories.

The paper presents research in an emerging but increasingly important field, i.e. semantic web‐based knowledge technology. It describes how this technology can satisfy the demand for improved knowledge access, including providing knowledge delivery to users at the right time and in the correct form.

There is an increasing interest in using information and communication technologies to support health services. But the adoption and development of even basic ICT communications services in many health services is limited, leaving enormous gaps in the broad understanding of its role in health care delivery. The purpose of this paper is to address a specific (intercultural) area of healthcare communications consumer disadvantage; and it examines the potential for ICT exploitation through the lens of a conceptual framework. The opportunity to pursue a new solutions pathway has been amplified in recent times through the development of computer-based ontologies and the resultant knowledge from ontologist activity and consequential research publishing.

A specific intercultural area of patient disadvantage arises from variations in meaning and understanding of patient and clinician words, phrases and non-verbal expression. Collection and localization of data concepts, their attributes and individual instances were gathered from an Aboriginal trainee nurse focus group and from a qualitative gap analysis (QGA) of 130 criteria-selected sources of literature. These concepts, their relationships and semantic interpretations populate the computer ontology. The ontology mapping involves two domains, namely, Aboriginal English (AE) and Type II diabetes care guidelines. This is preparatory to development of the Patient Practitioner Assistive Communications (PPAC) system for Aboriginal rural and remote patient primary care.

The combined QGA and focus group output reported has served to illustrate the call for three important drivers of change. First, there is no evidence to contradict the hypothesis that patient-practitioner interview encounters for many Australian Aboriginal patients and wellbeing outcomes are unsatisfactory at best. Second, there is a potent need for cultural competence knowledge and practice uptake on the part of health care providers; and third, the key contributory component to determine success or failures within healthcare for ethnic minorities is communication. Communication, however, can only be of value in health care if in practice it supports shared cognition; and mutual cognition is rarely achievable when biopsychosocial and other cultural worldview differences go unchallenged.

There has been no direct engagement with remote Aboriginal communities in this work to date. The authors have initially been able to rely upon a cohort of both Indigenous and non-Indigenous people with relevant cultural expertise and extended family relationships. Among these advisers are health care practitioners, academics, trainers, Aboriginal education researchers and workshop attendees. It must therefore be acknowledged that as is the case with the QGA, the majority of the concept data is from third parties. The authors have also discovered that urban influences and cultural sensitivities tend to reduce the extent of, and opportunity to, witness AE usage, thereby limiting the ability to capture more examples of code-switching. Although the PPAC system concept is qualitatively well developed, pending future work planned for rural and remote community engagement the authors presently regard the work as mostly allied to a hypothesis on ontology-driven communications. The concept data population of the AE home talk/health talk ontology has not yet reached a quantitative critical mass to justify application design model engineering and real-world testing.

Computer ontologies avail us of the opportunity to use assistive communications technology applications as a dynamic support system to elevate the pragmatic experience of health care consultations for both patients and practitioners. The human-machine interactive development and use of such applications is required just to keep pace with increasing demand for healthcare and the growing health knowledge transfer environment. In an age when the worldwide web, communications devices and social media avail us of opportunities to confront the barriers described the authors have begun the first construction of a merged schema for two domains that already have a seemingly intractable negative connection. Through the ontology discipline of building syntactically and semantically robust and accessible concepts; explicit conceptual relationships; and annotative context-oriented guidance; the authors are working towards addressing health literacy and wellbeing outcome deficiencies of benefit to the broader communities of disadvantage patients.

This study proposes a framework for Earthwork Ontology (EW-Onto) to support and enhance data exchange in the project and the efficient decision-making in the planning and execution phases.

The development of EW-Onto started from defining the concepts and building taxonomies for earthwork operations and equipment following the METHONTOLOGY approach. In addition, several rules have been extracted from safety codes and implemented as SWRL rules. The ontology has been implemented using Protégé. The consistency of EW-Onto has been checked and it has been evaluated using a survey.

The assessment of EW-Onto by experts indicates an adequate level of consensus with the framework, as an initial step for explicit knowledge exchanges within the earthwork domain.

The use of an ontology within the earthwork domain can help: (1) link and identify the relationships between concepts, define earthwork semantics, and classify knowledge in a hierarchical way accepted by experts and end-users; (2) facilitate the management of earthwork operations and simplify information exchange and interoperability between currently fragmented systems; and (3) increase the stakeholders' knowledge of earthwork operations through the provision of the information, which is structured in the context of robust knowledge.

This paper proposes a framework for Earthwork Ontology (EW-Onto) to support and enhance data exchange in the project and the efficient decision-making in the planning and execution phases. EW-Onto represents the semantic values of the entities and the relationships, which are identified and formalized based on the basic definitions available in the literature and outlined by experts.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

The purpose of this study is to convey lessons learned from a long-term research project and present a coherent approach for researching relevant areas, ranging from ontology to quality.

A PhD process is used as a case to present conceptual ideas on performing research in logistics/supply chain management (SCM).

The research integrates different views on knowledge and the world and how to perform research in logistics/SCM. Models explaining micro and macro abduction, and the relationship between research, the context and researcher subjectivity are suggested.

Knowledge on why and how critical realism can be used in logistics/SCM research is advanced. Abduction is presented as a micro/macro process, which should not have any specific “finish line”, and is supported with both ontological and epistemological arguments.

Research in logistics/SCM can be improved by connecting different aspects of viewing and creating knowledge. Reflecting on how exactly a publication is related to a project, researchers can better describe how they contribute to knowledge creation, and also understand the relationship between micro and macro abduction.

Through presenting an approach to knowledge creation in the context of a PhD thesis, this research distinguishes itself in a field with a growing need to define its own views of the world and of knowledge. The paper advances current understanding of knowledge creation in logistics/SCM, expanding on earlier models and presenting a broader view of the research process and the associated dilemmas. The paper also contains novel considerations of the differences between publication types and how these affect the presentation of the research.

The purpose of this study is to propose a framework for extracting medical information from the Web using domain ontologies. Patient–Doctor conversations have become prevalent on the Web. For instance, solutions like HealthTap or AskTheDoctors allow patients to ask doctors health-related questions. However, most online health-care consumers still struggle to express their questions efficiently due mainly to the expert/layman language and knowledge discrepancy. Extracting information from these layman descriptions, which typically lack expert terminology, is challenging. This hinders the efficiency of the underlying applications such as information retrieval. Herein, an ontology-driven approach is proposed, which aims at extracting information from such sparse descriptions using a meta-model.

A meta-model is designed to bridge the gap between the vocabulary of the medical experts and the consumers of the health services. The meta-model is mapped with SNOMED-CT to access the comprehensive medical vocabulary, as well as with WordNet to improve the coverage of layman terms during information extraction. To assess the potential of the approach, an information extraction prototype based on syntactical patterns is implemented.

The evaluation of the approach on the gold standard corpus defined in Task1 of ShARe CLEF 2013 showed promising results, an F-score of 0.79 for recognizing medical concepts in real-life medical documents.

The originality of the proposed approach lies in the way information is extracted. The context defined through a meta-model proved to be efficient for the task of information extraction, especially from layman descriptions.