Towards a Formalization of a Framework to Express and Reason about Software Engineering Methods

Software Engineering is considered a knowledge-intensive discipline, in which knowledge creation, collection and sharing is an uninterrupted process. However, a large part of this knowledge exists in a tacit form and depends on practitioners. Therefore defining a mechanism to transform tacit knowledge into explicit one is of upmost importance. This paper presents a formalization approach to represent Software Engineering practitioners' tacit knowledge, which is related to their ways of working, as a set of explicit statements. The formalization is based on KUALI-BEH, which is a normative kernel extension of ESSENCE formal specification, and consists of three parts: an ontology to share a common representation of knowledge as a set of concepts; a Situational Method Engineering based algebra that represents well-defined method properties and operations; and a knowledge representation of the ontology and algebra using Description Logics. The main objectives of this initial formalization are to improve communication among humans and machines, computational inference and reuse of knowledge

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 co-design method for the co-creation of a continuous care ontology

Ontology engineering methodologies tend to emphasize the role of the knowledge engineer or require a very active role of domain experts. In this paper, a participatory ontology engineering method is described that holds the middle ground between these two 'extremes'. After thorough ethnographic research, an interdisciplinary group of domain experts closely interacted with ontology engineers and social scientists in a series of workshops. Once a preliminary ontology was developed, a dynamic care request system was built using the ontology. Additional workshops were organized involving a broader group of domain experts to ensure the applicability of the ontology across continuous care settings. The proposed method successfully actively engaged domain experts in constructing the ontology, without overburdening them. Its applicability is illustrated by presenting the co-created continuous care ontology. The lessons learned during the design and execution of the approach are also presented

OntoAna: Domain Ontology for Human Anatomy

Today, we can find many search engines which provide us with information which is more operational in nature. None of the search engines provide domain specific information. This becomes very troublesome to a novice user who wishes to have information in a particular domain. In this paper, we have developed an ontology which can be used by a domain specific search engine. We have developed an ontology on human anatomy, which captures information regarding cardiovascular system, digestive system, skeleton and nervous system. This information can be used by people working in medical and health care domain.Comment: Proceedings of 5th CSI National Conference on Education and Research. Organized by Lingayay University, Faridabad. Sponsored by Computer Society of India and IEEE Delhi Chapter. Proceedings published by Lingayay University Pres

Exploiting conceptual spaces for ontology integration

The widespread use of ontologies raises the need to integrate distinct conceptualisations. Whereas the symbolic approach of established representation standards – based on first-order logic (FOL) and syllogistic reasoning – does not implicitly represent semantic similarities, ontology mapping addresses this problem by aiming at establishing formal relations between a set of knowledge entities which represent the same or a similar meaning in distinct ontologies. However, manually or semi-automatically identifying similarity relationships is costly. Hence, we argue, that representational facilities are required which enable to implicitly represent similarities. Whereas Conceptual Spaces (CS) address similarity computation through the representation of concepts as vector spaces, CS rovide neither an implicit representational mechanism nor a means to represent arbitrary relations between concepts or instances. In order to overcome these issues, we propose a hybrid knowledge representation approach which extends FOL-based ontologies with a conceptual grounding through a set of CS-based representations. Consequently, semantic similarity between instances – represented as members in CS – is indicated by means of distance metrics. Hence, automatic similarity detection across distinct ontologies is supported in order to facilitate ontology integration

SNOMED CT standard ontology based on the ontology for general medical science

Background: Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is acomprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic healthdata. Some efforts have been made to capture the contents of SCT as Web Ontology Language (OWL), but theseefforts have been hampered by the size and complexity of SCT. Method: Our proposal here is to develop an upper-level ontology and to use it as the basis for defining the termsin SCT in a way that will support quality assurance of SCT, for example, by allowing consistency checks ofdefinitions and the identification and elimination of redundancies in the SCT vocabulary. Our proposed upper-levelSCT ontology (SCTO) is based on the Ontology for General Medical Science (OGMS). Results: The SCTO is implemented in OWL 2, to support automatic inference and consistency checking. Theapproach will allow integration of SCT data with data annotated using Open Biomedical Ontologies (OBO) Foundryontologies, since the use of OGMS will ensure consistency with the Basic Formal Ontology, which is the top-levelontology of the OBO Foundry. Currently, the SCTO contains 304 classes, 28 properties, 2400 axioms, and 1555annotations. It is publicly available through the bioportal athttp://bioportal.bioontology.org/ontologies/SCTO/. Conclusion: The resulting ontology can enhance the semantics of clinical decision support systems and semanticinteroperability among distributed electronic health records. In addition, the populated ontology can be used forthe automation of mobile health applications