F-ONTOCOM: A Fuzzified Cost Estimation Approach for Ontology Engineering

Estimating effort is an essential prerequisite for the wide-scale dispersal of ontologies. Not much attention has yet been paid to this essential aspect of ontology building. To date, ONTOCOM is the most prominent model for ontology cost estimation. Many factors influencing the building cost of an ontology are depicted by linguistic terms like Very High, High, . . . and so on; making them vague and indistinct. This fuzziness is quite uncertain and must be taken into consideration. The available effort estimation models do not consider the uncertainty of fuzziness. In this work, we propose an effort estimation methodology for ontology engineering using Fuzzy Logic i.e. F-ONTOCOM (Fuzzy-ONTOCOM) to overcome of uncertainty and imprecision. We have defined the corresponding Fuzzy sets for each effort multiplier and its associated linguistic value, and represented the same by triangular membership functions. F-ONTOCOM is applied to a dataset of 148 ontology projects and evaluated over various evaluation criteria. FONTOCOM outperforms the existing effort-estimation models; it has been concluded that F-ONTOCOM improves the cost estimation accuracy and estimated cost is very close to actual cost.

Ontologies: a revamped cross-disciplinary buzzword or a truly promising interdisciplinary research topic?

The following article provides an introductory overview of the different research domains (computational linguistics, termino graphy, artificial intelligence (AI), philosophy and database semantics) for which ontologies and the emerging field of the Semantic Web have become a main point of interest. It will be pointed out that each of these domains uses a different definition for an ontology. A specific ontology engineering methodology (VUB STAR Lab DOGMA) will be presented and emphasis will be put on the specific role and contribution of (multilingual) terminography in this ontology. In addition, we will explain what ontologies might offer to advance the state of the art of linguistics and terminography.

Ontologies in human–computer interaction: A systematic literature review

Human–Computer Interaction (HCI) is a multidisciplinary area that involves a diverse body of knowledge and a complex landscape of concepts, which can lead to semantic problems, hampering communication and knowledge transfer. Ontologies have been successfully used to solve semantics and knowledge-related problems in several domains. This paper presents a systematic literature review that investigated the use of ontologies in the HCI domain. The main goal was to find out how HCI ontologies have been used and developed. 35 ontologies were identified. As a result, we noticed that they cover different HCI aspects, such as user interface, interaction phenomenon, pervasive computing, user modeling / profile, HCI design, interaction experience and adaptive interactive system. Although there are overlaps, we did not identify reuse among the 35 analyzed ontologies. The ontologies have been used mainly to support knowledge representation and reasoning. Although ontologies have been used in HCI for more than 25 years, their use became more frequent in the last decade, when ontologies address a higher number of HCI aspects and are represented as both conceptual and computational models. Concerning how ontologies have been developed, we noticed that some good practices of ontology engineering have not been followed. Considering that the quality of an ontology directly influences the quality of the solution built based on it, we believe that there is an opportunity for HCI and ontology engineering professionals to get closer to build better and more effective ontologies, as well as ontology-based solutions.

Web Interoperability for Ontology Development and Support with crowd 2.0

In this work, we treat web interoperability in terms of interchanging ontologies (as knowledge models) within user-centred ontology engineering environments, involving visual and serialised representations of ontologies. To do this, we deal with the tool interoperability problem by re-using an enough expressive ontology-driven metamodel, named KF, proposed as a bridge for interchanging both knowledge models. We provide an extensible web framework, named crowd 2.0, unifying the standard conceptual data modelling languages for generating OWL 2 ontologies from semantic visualisations. Visual models are designed as UML, ER or ORM 2 diagrams, represented as KF instances, and finally, formalised as DL-based models. Reasoning results may be newly incorporated into the shared KF instance to be visualised in any of the provided languages.

CargO-S: A pattern-based well-founded legal domain ontology for the traceability of goods in logistic sea corridors

Building legal domain ontologies is a prominent challenge in the ontology engineering community. The ontology builders confront issues such as the complexity of the legal domain, the difficulty of applying existing ontology engineering approaches, and the intention of developing legal models faithful to realities. In this paper, we discuss constructing a well-founded legal domain ontology, named CargO-S, for the traceability of goods in logistic sea corridors. For building CargO-S, a pattern-oriented approach is applied, supported by ontology-driven conceptual modeling, ontology layering, and ontology reuse processes. CargO-S is grounded in the unified foundational ontology UFO by using the ontology-driven conceptual modeling language OntoUML. Besides, ontology layering is proposed to simplify the development process by dividing CargO-S into three layers located at different granularity levels: upper, core, and domain. For building the upper and core layers, conceptual ontology patterns are reused from the foundational ontology UFO and the legal core ontology UFO-L. These patterns are applied, either by extension or analogy with legal rules, for building the domain layer. CargO-S is then validated by implementing the ontology as OWL and SWRL rules. Finally, the performance and the semantic accuracy of CargO-S are evaluated using a dual evaluation approach.

An approach to creating freeform spreadsheet ontology

The use of semantic technologies including ontologies is a widespread practice in modern intelligent system engineering. Spreadsheets are one of the most accessible and common ways of representing and storing information which are characterized by a wide variety and heterogeneity of layouts, styles and content while remaining a valuable source of domain knowledge. The paper proposes to automate the process of ontology engineering based on the analysis and transformation of spreadsheets with an arbitrary layout. For this purpose a new approach is presented that provides the restoration of the semantics of tabular data, conceptualization, and formalization of tabular content in the form of ontology. The main stages of the proposed approach and a description of the software are presented. The developed software was used to solve the practical problem of ontology engineering for diagnosing and assessing the technical condition of petrochemical equipment. Spreadsheets extracted from reports on industrial safety inspection of petrochemical complexes were used as the initial data. Based on the results of approbation, it was concluded that it is advisable to use the proposed approach when prototyping subject ontologies.