DTD2OWL2: A New Approach for the Transformation of the DTD to OWL

AbstractThe expansion of data sources existed in the web affects on the quality of research information. The correct answer (answer specific) of a request is all depend terms selected for their construction. Such as these terms sometimes mean more sense, the intended meaning may not be found. Fort this need, the Semantic Web has come to cover the semantic level, it proposed an ontological representation of data sources. This representation is implemented by OWL (Web Ontology Language). The current challenge of the Semantic Web is the transformation of data formats exist (SQL, XML ...) to the form of ontology (RDF, OWL ...), in order to facilitate the integration of data sources exist in the semantic web. Our target is to provide a series of extension concepts of DTD2OWL method, a simple and effective method for transforming XML documents into OWL ontologies

Precise use cases in a context-aware model-checking approach

International audienceFormal verification exhibits well known benefits but comes at the price of formalising precise and sound requirements, what often remains a challenging task for engineers. We propose a high-level formalism for expressing requirements based on interaction overview diagrams, which orchestrate activity diagrams that we automatically derived from use cases. Informal requirements are transformed into scenarios which fuel a context-aware model-checking approach. The approach assumes the availability of a formal model of the system, such as concurrent and communicating automata and a set of requirements specified in the form of contexts, which point out boundaries between the system and its environment. The requirement specification approach blends elaboration and transformation phases. Thanks to this blending, the semantic gap between informal and formal requirements is reduced, while model-checking is improved by contexts modelling. As a consequence, engineers gain support for moving towards formal verification

A High-level Formalism to Elaborate Context for a Context-aware Verification Approach

International audienceSpecification of precise requirement is a key element to realize effectively the model-checking verification. In a context-aware framework, the technique is considered through a set of specific environmental conditions in the form of contexts. A DSL, called CDL, has been proposed to facilitate the specification of requirement by context elaboration. However, it still low-level, error prone, difficult to grasp on complex models and its usability is mitigated. In this paper, we propose a high level formalism of CDL to assist the specification process by describing the system requirements using interaction overview diagrams. The objective is to generate CDL models through such intermediate formalism by orchestrating activity diagrams transformed from informal use cases. Thus, the semantic gap between informal and formal requirements is reduced and engineers are helped towards formal verification

An Automated Transformation Approach for Requirement Specification

International audienceUse cases are often useful in capturing requirements by defining goal-oriented set of interactions between the system and its environment. Formalization of precise requirement is then important for context-aware verification based on use cases scenarios in the form of contexts. In this paper, we propose a high-level formalism for expressing requirements based on interaction overview diagrams that orchestrate activity diagrams automatically transformed from textual use cases. Our approach is qualified as context-aware model-checking, it supposes the availability of a model of the system as concurrent communicating automata and a specification language for describing requirements. Specification of requirements is performed through transformation phases to generate intermediate artefacts able to reduce the semantic gap between informal and informal requirement. The transformation is based on meta-models implemented on Ecore environment, algorithm and rules are defined using QVT Relational language, and primarily illustrated on an academic example

Enhancing dependability through profiling in the collaborative internet of things

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Minimization of the disagreements in clustering aggregation

International audienceAbstract: Several experiences proved the impact of the choice of the parts of documents selected on the result of the classification and consequently on the number of requests which can answer these clusters. The process of aggregation gives a very natural method of data classification and considers then m produced classifications by them m attributes and tries to produce a classification called "optimal" which is the most close possible of m classifications. The optimization consists in minimizing the number of pairs of objects (u, v) such as a C classification place them in the same cluster whereas another C' classification place them in different clusters. This number corresponds to the concept of disagreements. We propose an approach which exploits the various elements of an XML document participating in various views to give different classifications. These classifications are then aggregated in the only one classification minimizing the number of disagreements. Our approach is divided into two steps: the first consists in applying the K-means algorithm on the collection of XML documents by considering every time a different element from the document. Second step aggregates the various classifications obtained previously to produce the one that minimizes the number of disagreements

A*: a new algebra for an extended object/relational model

International audienceIn this paper, an algebra A consisting of first order logic operators has been defined to express various classes of queries in object relational database. To contribute to the improvement of relational/object models and agebra this paper presents an extension of object relational model to new types generated by operators and the related algebra A*. These operators, called Op, offer a means to specify domains as functions and permit consequently to increase the data model expressiveness. To support this extension, we propose a new data query language, or more precisely a logical data calculation A* as an adapatation of the algebra A. A* Algebra contains algebraic operators which are able to support this new extension