Method for Reusing and Re-engineering Non-ontological Resources for Building Ontologies

This thesis is focused on the reuse and possible subsequent re-engineering of knowledge resources, as opposed to custom-building new ontologies from scratch. The deep analysis of the state of the art has revealed that there are some methods and tools in the literature for transforming non-ontological resources into ontologies, but with some limitations: _ Most of the methods presented are based on ad-hoc transformations for the resource type, and the resource implementation. _ Only a few take advantage of the resource data model, an important artifact for the re-engineering process [GGPSFVT08]. _ There is no any integrated framework, method or corresponding tool, that considers the resources types, data models and implementations identified in an unified way. _ With regard to the transformation approach, the majority of the methods perform a TBox transformation, many others perform an ABox transformation and some perform a population. However, no method includes the possibility to perform the three transformation approaches. _ Regarding to the degree of automation, almost all the methods perform a semi-automatic transformation of the resource. _ According to the explicitation of the hidden semantics in the relations of the resource components, we can state that the methods that perform a TBox transformation make explicit the semantics in the relations of the resource components. Most of those methods identify subClassOf relations, others identify ad-hoc relations, and some identify partOf relations. However, only a few methods make explicit the three types of relations. _ With respect to how the methods make explicit the hidden semantics in the relations of the resource terms, we can say that three methods rely on the domain expert for making explicit the semantics, and two rely on an external resource, e.g., DOLCE ontology. Moreover, there are two methods that rely on external resources but not for making explicit the hidden semantics, but for finding out a proper ontology for populating it. _ According to the provision of the methodological guidelines, almost all the methods provide methodological guidelines for the transformation. However these guidelines are not finely detailed; for instance, they do not provide information about who is in charge of performing a particular activity/task, nor when that activity/task has to be carried out. _ With regard to the techniques employed, most of the methods do not mention them at all. Only a few methods specify techniques as transformation rules, lexico-syntactic patterns, mapping rules and natural language techniques. In this thesis we have provided a method and its technological support that rely on re-engineering patterns in order to speed up the ontology development process by reusing and re-engineering as much as possible available non-ontological resources. To achieve this overall goal, we have decomposed it in the following objectives: (1) the definition of methodological aspects related with the reuse of non-ontolo-gical resource for building ontologies; (2) the definition of methodological aspects related with the re-engineering of non-ontological resources for building ontologies; (3) the creation of a library of patterns for re-engineering nonontological resources into ontologies; and (4) the development of a software library that implements the suggestions given by the re-engineering patterns. Having in mind these goals, in this chapter we present how the open research problems identified in Chapter 2 are solved by the main thesis contributions. Then, we discuss the verification of our hypotheses, and finally we provide an outlook for the future work in those topics

A Pattern Based Approach for Re-engineering Non-Ontological Resources into Ontologies

With the goal of speeding up the ontology development process, ontology engineers are starting to reuse as much as possible available ontologies and non-ontological resources such as classification schemes, thesauri, lexicons and folksonomies, that already have some degree of consensus. The reuse of such non-ontological resources necessarily involves their re-engineering into ontologies. Non-ontological resources are highly heterogeneous in their data model and contents: they encode different types of knowledge, and they can be modeled and implemented in different ways. In this paper we present (1) a typology for non-ontological resources, (2) a pattern based approach for re-engineering non-ontological resources into ontologies, and (3) a use case of the proposed approach

A network of ontology networks for building e-employment advanced systems

This paper presents the development of a network of ontology networks that enables data mediation between the Employment Services (ESs) participating in a semantic interoperability platform for the exchange of Curricula Vitae (CVs) and job offers in different languages. Such network is formed by (1) a set of local ontology networks that are language dependent, in which each network represents the local and particular view that each ES has of the employment market; and (2) a reference ontology network developed in English that represents a standardized and agreed upon terminology of the European employment market. In this network each local ontology network is aligned with the reference ontology network so that search queries, CVs, and job offers can be mediated through these alignments from any ES. The development of the ontologies has followed the methodological guidelines issued by the NeOn Methodology and is focused mainly on scenarios that involve reusing and re-engineering knowledge resources already agreed upon by employment experts and standardization bodies. This paper explains how these methodological guidelines have been applied for building e-employment ontologies. In addition, it shows that the approach to building ontologies by reusing and re-engineering agreed upon non-ontological resources speeds the ontology development, reduces development costs, and retrieves knowledge already agreed upon by a community of people in a more formal representation

Essentials In Ontology Engineering: Methodologies, Languages, And Tools

In the beginning of the 90s, ontology development was similar to an art: ontology developers did not have clear guidelines on how to build ontologies but only some design criteria to be followed. Work on principles, methods and methodologies, together with supporting technologies and languages, made ontology development become an engineering discipline, the so-called Ontology Engineering. Ontology Engineering refers to the set of activities that concern the ontology development process and the ontology life cycle, the methods and methodologies for building ontologies, and the tool suites and languages that support them. Thanks to the work done in the Ontology Engineering field, the development of ontologies within and between teams has increased and improved, as well as the possibility of reusing ontologies in other developments and in final applications. Currently, ontologies are widely used in (a) Knowledge Engineering, Artificial Intelligence and Computer Science, (b) applications related to knowledge management, natural language processing, e-commerce, intelligent information integration, information retrieval, database design and integration, bio-informatics, education, and (c) the Semantic Web, the Semantic Grid, and the Linked Data initiative. In this paper, we provide an overview of Ontology Engineering, mentioning the most outstanding and used methodologies, languages, and tools for building ontologies. In addition, we include some words on how all these elements can be used in the Linked Data initiative

Semantics for incident identification and resolution reports

In order to achieve a safe and systematic treatment of security protocols, organizations release a number of technical briefings describing how to detect and manage security incidents. A critical issue is that this document set may suffer from semantic deficiencies, mainly due to ambiguity or different granularity levels of description and analysis. An approach to face this problem is the use of semantic methodologies in order to provide better Knowledge Externalization from incident protocols management. In this article, we propose a method based on semantic techniques for both, analyzing and specifying (meta)security requirements on protocols used for solving security incidents. This would allow specialist getting better documentation on their intangible knowledge about them.Ministerio de Economía y Competitividad TIN2013-41086-

An ontology roadmap for crowdsourcing innovation intermediaries

Ontologies have proliferated in the last years, essentially justified by the need of achieving a consensus in the multiple representations of reality inside computers, and therefore the accomplishment of interoperability between machines and systems. Ontologies provide an explicit conceptualization that describes the semantics of the data. Crowdsourcing innovation intermediaries are organizations that mediate the communication and relationship between companies that aspire to solve some problem or to take advantage of any business opportunity with a crowd that is prone to give ideas based on their knowledge, experience and wisdom, taking advantage of web 2.0 tools. Various ontologies have emerged, but at the best of our knowledge, there isn’t any ontology that represents the entire process of intermediation of crowdsourcing innovation. In this paper we present an ontology roadmap for developing crowdsourcing innovation ontology of the intermediation process. Over the years, several authors have proposed some distinct methodologies, by different proposals of combining practices, activities, languages, according to the project they were involved in. We start making a literature review on ontology building, and analyse and compare ontologies that propose the development from scratch with the ones that propose reusing other ontologies. We also review enterprise and innovation ontologies known in literature. Finally, are presented the criteria for selecting the methodology and the roadmap for building crowdsourcing innovation intermediary ontology.(undefined

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

Reusing Ontology Design Patterns in a Context Ontology Network

Reusing knowledge resources, specifically Ontology Design Patterns (ODPs), has became a popular technique within the ontology engineering field. Such a reuse allows speeding up the ontology development process, saving time and money, and promoting the application of good practices. Recently methods and tools to support the reuse of ODPs have emerged. In addition, the existence of detailed examples of real use cases that reuse ODPs favours the adoption and application of such methods. Thus, our objective in this paper is to show an example of how to apply a method for reusing ODPs during the development of a context ontology network to model context-related knowledge that allows adapting applications based on user context. Besides, in this paper we present the main drawbacks found during the application of the reuse method as well as some proposals to overcome them

Creation and extension of ontologies for describing communications in the context of organizations

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer ScienceThe use of ontologies is nowadays a sufficiently mature and solid field of work to be considered an efficient alternative in knowledge representation. With the crescent growth of the Semantic Web, it is expectable that this alternative tends to emerge even more in the near future. In the context of a collaboration established between FCT-UNL and the R&D department of a national software company, a new solution entitled ECC – Enterprise Communications Center was developed. This application provides a solution to manage the communications that enter, leave or are made within an organization, and includes intelligent classification of communications and conceptual search techniques in a communications repository. As specificity may be the key to obtain acceptable results with these processes, the use of ontologies becomes crucial to represent the existing knowledge about the specific domain of an organization. This work allowed us to guarantee a core set of ontologies that have the power of expressing the general context of the communications made in an organization, and of a methodology based upon a series of concrete steps that provides an effective capability of extending the ontologies to any business domain. By applying these steps, the minimization of the conceptualization and setup effort in new organizations and business domains is guaranteed. The adequacy of the core set of ontologies chosen and of the methodology specified is demonstrated in this thesis by its effective application to a real case-study, which allowed us to work with the different types of sources considered in the methodology and the activities that support its construction and evolution