Validating an approach to formalize use cases with ontologies

Use case driven development methodologies put use cases at the center of the software development process. However, in order to support automated development and analysis, use cases need to be appropriately formalized. This will also help guarantee consistency between requirements specifications and developed solutions. Formal methods tend to suffer from take up issues, as they are usually hard to accept by industry. In this context, it is relevant not only to produce languages and approaches to support formalization, but also to perform their validation. In previous works we have developed an approach to formalize use cases resorting to ontologies. In this paper we present the validation of one such approach. Through a three stage study, we evaluate the acceptance of the language and supporting tool. The first stage focusses on the acceptance of the process and language, the second on the support the tool provides to the process, and finally the third one on the tool's usability aspects. Results show test subjects found the approach feasible and useful and the tool easy to use.This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project "POCI-01-0145-FEDER-006961", and by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013

OntoMathPROOntoMath^{PRO} Ontology: A Linked Data Hub for Mathematics

In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.Comment: 15 pages, 6 images, 1 table, Knowledge Engineering and the Semantic Web - 5th International Conferenc

Ontology Evolution Using Ontology Templates

Evolving ontologies by domain experts is difficult and typically cannot be performed without the assistance of an ontology engineer. This process takes long time and often recurrent modeling errors have to be resolved. This paper proposes a technique for creating controlled ontology evolution scenarios that ensure consistency of the possible ontology evolution and give guarrantees to the domain expert that his/her updates do not cause inconsistency. We introduce ontology templates that formalize the notion of controlled evolution and define ontology template consistency checking service together with a consistency checking algorithm. We prove correctness and demonstate the practical use of the techniques in two scenarios

SMART Protocols: seMAntic represenTation for experimental protocols

Two important characteristics of science are the ?reproducibility? and ?clarity?. By rigorous practices, scientists explore aspects of the world that they can reproduce under carefully controlled experimental conditions. The clarity, complementing reproducibility, provides unambiguous descriptions of results in a mechanical or mathematical form. Both pillars depend on well-structured and accurate descriptions of scientific practices, which are normally recorded in experimental protocols, scientific workflows, etc. Here we present SMART Protocols (SP), our ontology-based approach for representing experimental protocols and our contribution to clarity and reproducibility. SP delivers an unambiguous description of processes by means of which data is produced; by doing so, we argue, it facilitates reproducibility. Moreover, SP is thought to be part of e-science infrastructures. SP results from the analysis of 175 protocols; from this dataset, we extracted common elements. From our analysis, we identified document, workflow and domain-specific aspects in the representation of experimental protocols. The ontology is available at http://purl.org/net/SMARTprotoco

An ontology-based content management system for a dynamic operating context: issues and prototype evaluation

Content management systems are very useful tools for organizing and sharing information resources and may considerably benefit from using ontology-based description schemes. Ontologies set a common ground for resource acquisition, enabling different users to share a common view of a knowledge domain, and may considerably enhance the search paradigms by exploiting semantic relationships between concepts. However, ontologies may evolve since they reflect knowledge schemes that are by nature dynamic. Moreover this evolution should be the result of a collaborative process of ontology maintenance. These and other issues are addressed in the present work and some practical solutions are proposed. Also, a very simple prototype implementation of an ontology-based content management system is described. Finally, the results of a short experimentation of this prototype within a small community are presented

Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving

To take into account the experience feedback on solving complex problems in business is deemed as a way to improve the quality of products and processes. Only a few academic works, however, are concerned with the representation and the instrumentation of experience feedback systems. We propose, in this paper, a model of experiences and mechanisms to use these experiences. More specifically, we wish to encourage the reuse of already performed expert analysis to propose a priori analysis in the solving of a new problem. The proposal is based on a representation in the context of the experience of using a conceptual marker and an explicit representation of the analysis incorporating expert opinions and the fusion of these opinions. The experience feedback models and inference mechanisms are integrated in a commercial support tool for problem solving methodologies. The results obtained to this point have already led to the definition of the role of ‘‘Rex Manager’’ with principles of sustainable management for continuous improvement of industrial processes in companies