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There is an increasing recognition of the value of effective information and knowledge management (KM) in the construction project delivery process. Many architecture, engineering and construction (AEC) organisations have invested heavily in information technology and KM systems that help in this regard. While these have been largely successful in supporting intra‐organisational business processes, interoperability problems still persist at the project organisation level due to the heterogeneity of the systems used by the different organisations involved. Ontologies are seen as an important means of addressing these problems. The purpose of this paper is to explore the role of ontologies in the construction project delivery process, particularly with respect to information and KM.

A detailed technical review of the fundamental concepts and related work has been undertaken, with examples and case studies of ontology‐based information and KM presented to illustrate the key concepts. The specific issues and technical difficulties in the design and construction context are highlighted, and the approaches adopted in two ontology‐based applications for the AEC sector are presented.

The paper concludes that there is considerable merit in ontology‐based approaches to information and KM, but that significant technical challenges remain. Middleware applications, such as semantic web‐based information management system, are contributing in this regard but more needs to be done particularly on integrating or merging ontologies.

The value of the paper lies in the detailed exploration of ontology‐based information and KM within a design and construction context, and the use of appropriate examples and applications to illustrate the key issues.

Ontologies are prone to wide semantic variability due to subjective points of view of their composers. The purpose of this paper is to propose a new approach for maximal unification of diverse ontologies for controversial domains by their relations.

Effective matching or unification of multiple ontologies for a specific domain is crucial for the success of many semantic web applications, such as semantic information retrieval and organization, document tagging, summarization and search. To this end, numerous automatic and semi-automatic techniques were proposed in the past decade that attempt to identify similar entities, mostly classes, in diverse ontologies for similar domains. Apparently, matching individual entities cannot result in full integration of ontologies’ semantics without matching their inter-relations with all other-related classes (and instances). However, semantic matching of ontological relations still constitutes a major research challenge. Therefore, in this paper the authors propose a new paradigm for assessment of maximal possible matching and unification of ontological relations. To this end, several unification rules for ontological relations were devised based on ontological reference rules, and lexical and textual entailment. These rules were semi-automatically implemented to extend a given ontology with semantically matching relations from another ontology for a similar domain. Then, the ontologies were unified through these similar pairs of relations. The authors observe that these rules can be also facilitated to reveal the contradictory relations in different ontologies.

To assess the feasibility of the approach two experiments were conducted with different sets of multiple personal ontologies on controversial domains constructed by trained subjects. The results for about 50 distinct ontology pairs demonstrate a good potential of the methodology for increasing inter-ontology agreement. Furthermore, the authors show that the presented methodology can lead to a complete unification of multiple semantically heterogeneous ontologies.

This is a conceptual study that presents a new approach for semantic unification of ontologies by a devised set of rules along with the initial experimental evidence of its feasibility and effectiveness. However, this methodology has to be fully automatically implemented and tested on a larger dataset in future research.

This result has implication for semantic search, since a richer ontology, comprised of multiple aspects and viewpoints of the domain of knowledge, enhances discoverability and improves search results.

To the best of the knowledge, this is the first study to examine and assess the maximal level of semantic relation-based ontology unification.

Large terminologies usually contain a mix of terms that are either generic or domain specific, which makes the use of the terminology itself a difficult task that may limit the positive effects of these systems. The purpose of this paper is to systematically evaluate the degree of domain specificity of the AGROVOC controlled vocabulary terms as a representative of a large terminology in the agricultural domain and discuss the generic/specific boundaries across its hierarchy.

A user-oriented study with domain-experts in conjunction with quantitative and systematic analysis. First an in-depth analysis of AGROVOC was carried out to make a proper selection of terms for the experiment. Then domain-experts were asked to classify the terms according to their domain specificity. An evaluation was conducted to analyse the domain-experts’ results. Finally, the resulting data set was automatically compared with the terms in SUMO, an upper ontology and MILO, a mid-level ontology; to analyse the coincidences.

Results show the existence of a high number of generic terms. The motivation for several of the unclear cases is also depicted. The automatic evaluation showed that there is not a direct way to assess the specificity degree of a term by using SUMO and MILO ontologies, however, it provided additional validation of the results gathered from the domain-experts.

The “domain-analysis” concept has long been discussed and it could be addressed from different perspectives. A resume of these perspectives and an explanation of the approach followed in this experiment is included in the background section.

The authors propose an approach to identify the domain specificity of terms in large domain-specific terminologies and a criterion to measure the overall domain specificity of a knowledge organisation system, based on domain-experts analysis. The authors also provide a first insight about using automated measures to determine the degree to which a given term can be considered domain specific. The resulting data set from the domain-experts’ evaluation can be reused as a gold standard for further research about these automatic measures.

The purpose of this paper is to propose a graph-based representation approach for evolutionary knowledge under the big data circumstance, aiming to gradually build conceptual models from data.

A semantic data model named meaning graph (MGraph) is introduced to represent knowledge concepts to organize the knowledge instances in a graph-based knowledge base. MGraph uses directed acyclic graph–like types as concept schemas to specify the structural features of knowledge with intention variety. It also proposes several specialization mechanisms to enable knowledge evolution. Based on MGraph, a paradigm is introduced to model the evolutionary concept schemas, and a scenario on video semantics modeling is introduced in detail.

MGraph is fit for the evolution features of representing knowledge from big data and lays the foundation for building a knowledge base under the big data circumstance.

The representation approach based on MGraph can effectively and coherently address the major issues of evolutionary knowledge from big data. The new approach is promising in building a big knowledge base.

This paper describes a software architecture that automatically adds semantic capabilities to data services. The proposed architecture, called OntoGenesis, is able to semantically enrich data services, so that they can dynamically provide both semantic descriptions and data representations.

The enrichment approach is designed to intercept the requests from data services. Therefore, a domain ontology is constructed and evolved in accordance with the syntactic representations provided by such services in order to define the data concepts. In addition, a property matching mechanism is proposed to exploit the potential data intersection observed in data service representations and external data sources so as to enhance the domain ontology with new equivalences triples. Finally, the enrichment approach is capable of deriving on demand a semantic description and data representations that link to the domain ontology concepts.

Experiments were performed using real-world datasets, such as DBpedia, GeoNames as well as open government data. The obtained results show the applicability of the proposed architecture and that it can boost the development of semantic data services. Moreover, the matching approach achieved better performance when compared with other existing approaches found in the literature.

This work only considers services designed as data providers, i.e., services that provide an interface for accessing data sources. In addition, our approach assumes that both data services and external sources – used to enhance the domain ontology – have some potential of data intersection. Such assumption only requires that services and external sources share particular property values.

Unlike most of the approaches found in the literature, the architecture proposed in this paper is meant to semantically enrich data services in such way that human intervention is minimal. Furthermore, an automata-based index is also presented as a novel method that significantly improves the performance of the property matching mechanism.

The purpose of this paper is to report on research that aims to make knowledge, and in particular know-how, more easily accessible to both academic and industrial communities, as well as to the general public. The paper proposes a novel approach to map out know-how information, so all knowledge stakeholders are able to contribute to the knowledge and expertise accumulation, as well as using that knowledge for research and applying expertise to address problems.

This research followed a design science approach in which mapping of the know-how information was done by the research team and then tested with graduate students. During this research, the mapping approach was continuously evaluated and refined, and mapping guidelines and a prototype tool were developed.

Following an evaluation with graduate students, it was found that the know-how maps produced were easy to follow, allowed continuous evolution, facilitated easy modification through provided modularity capabilities, further supported reasoning about know-how and overall provided adequate expressiveness. Furthermore, we applied the approach with various domains and found that it was a good fit for its purpose across different knowledge domains.

This paper argues that mapping out know-how within research and industry communities can further improve resource (knowledge) utilization, reduce the phenomena of “re-inventing the wheel” and further create linkage across communities.

With the qualities mentioned above, know-how maps can both ease and support the increase of access to expert knowledge to various communities, and thus, promote re-use and expansion of knowledge for various purposes. Having an explicit representation of know-how further encourages innovation, as knowledge from various domains can be mapped, searched and reasoned, and gaps can be identified and filled.

The purpose of this article is to present a tool for assessing the sustainability knowledge of an undergraduate population.

Multiple-choice questions were developed through soliciting expert input, focus groups, pilot testing, distribution via a large-scale online survey and analysis using item response theory.

The final assessment consists of 16 questions from the environmental, economic and social domains, covering foundational concepts within the topic of sustainability.

This assessment represents an initial effort to quantify knowledge of the broad and abstract concept of sustainability. The authors plan to continue refining these questions to better differentiate between students with higher levels of knowledge and to replace those with answers that may change over time.

With knowledge of sustainability concepts becoming increasingly included in institution-wide learning objectives, there is a growing demand for a way to measure progress in this area. Our assessment tool can easily be used (via a campus-wide survey or distributed at the classroom level) by institutions to gauge current levels of knowledge and track changes over time, as well as assess the effectiveness of courses and curricula at meeting sustainability knowledge goals.

This assessment of sustainability knowledge is the first of its kind to include all three separate domains of sustainability, and we expect it to be useful across a variety of college and university contexts.

This paper aims to present a common body of knowledge (CBK) for the field of information privacy, titled InfoPrivacy CBK. The purpose of the proposed CBK is to guide internet users to better understand the concept of information privacy and associate information privacy-related concepts. The InfoPrivacy CBK was created with an educational orientation to provide the basis for designing privacy awareness and training programs and organizing relevant educational material.

The proposed CBK for information privacy was developed conceptually and includes five domains and four levels of analysis. It is illustrated with conceptual maps. The authors identified a variety of concepts related to information privacy and created a set of categories to categorize the concepts. They used, as inclusion criteria, both theoretical and practical information privacy aspects, so that the developed CBK can address the challenges of modern technologies for preserving information privacy.

To validate and refine the conceptually developed CBK, the authors conducted an empirical research, in which seven information privacy experts participated. The experts commented largely positively for the structure and content of InfoPrivacy CBK, as well as for the extent to which it achieves the intended educational goals.

The proposed InfoPrivacy CBK was validated by a limited number of information privacy experts, mainly due to the lengthy and in-depth participation that was required.

The InfoPrivacy CBK can be used primarily by privacy awareness and training programs developers, such as organizations, data protection officers, the state, educational policy makers and teachers.

Internet users will benefit from InfoPrivacy CBK by acquiring knowledge and skills from theoretically grounded training programs, which can enhance their awareness and critical thinking on issues related to the protection of their information privacy. This will lead to more privacy-aware online societies, communities, networks, etc.

This work intends to bridge the existing gap in the literature through the creation of a novel CBK for information privacy; information privacy is a field for which no such research effort has been recorded. This paper offers important knowledge in the field of information privacy, which could be useful to both technological education designers and learners (students, employees, etc.).

The purpose of this paper is to clarify which knowledge, skills and behaviors are used to describe excellent performance in professional communication. As the demand for talented communication professionals increases, organizations and educators need an empirically defined set of performance criteria to guide the development of (potentially) excellent communication professionals (ECPs). This research aimed to render a competence profile which could assist in the development of recruitment, training and development to develop relevant programs for high-potential communication practitioners.

This mixed-method research was approached in two phases: first, a series of focus groups (n=16) were held to explore work field perspectives resulting in a concept profile, and second, a series of expert panels (n=30) following the Delphi method were conducted to determine the extent of agreement with the findings.

Participants clarified that excellent performance is characterized by competences which transcend normative technical skills or practical communication knowledge. The five domains, 16 item “SEEDS” competence profile describes that ECPs are distinguished by their compounded ability to be strategic, empathic, expressive, and decisive and to see patterns and interrelationships.

Although a broad range of relevant professionals were involved in both phases, the study could be considered limited in size and scope. Research was conducted in one national setting therefore further research would be necessary to confirm generalizability of the results to other cultural contexts.

Although many competence frameworks exist which describe normative performance in this profession, specific criteria which illustrate excellent performance have not yet been identified. This competence profile clarifies characteristics which typify excellent performance in professional communication and can be helpful to educators and employers who wish to identify and create suitable training programs for ECPs.

The purpose of this paper is to highlight the difficulty of applying faceted classification outside of library contexts and also to indicate that faceted approaches are poorly expressed to non‐experts.

The faceted approach is being applied outside of its “home” community, with mixed results. The approach is based in part on examination of a broad base of literature and in part on results and reflections on a case study applying faceted notions to “real world” engineering documentation.

The paper comes across a number of pragmatic and theoretical issues namely: differing interpretations of the facet notion; confusion between faceted analysis and faceted classification; lack of methodological guidance; the use of simplistic domains as exemplars; description verses analysis; facet recognition is unproblematic; and is the process purely top‐down or bottom‐up.

That facet analysis is not inherently associated with a particular epistemology; that greater guidance about the derivation is needed, that greater realism is needed when teaching faceted approaches.

Experiences of applying faceted classifications are presented that can be drawn upon to guide future work in the area.

No previous work has reflected on the actual empirical experience used to create a faceted description, especially with reference to engineering documents.