An ontology of agile aspect oriented software development

Both agile methods and aspect oriented programming (AOP) have emerged in recent years as new paradigms in software development. Both promise to free the process of building software systems from some of the constraints of more traditional approaches. As a software engineering approach on the one hand, and a software development tool on the other, there is the potential for them to be used in conjunction. However, thus far, there has been little interplay between the two. Nevertheless, there is some evidence that there may be untapped synergies that may be exploited, if the appropriate approach is taken to integrating AOP with agile methods. This paper takes an ontological approach to supporting this integration, proposing ontology enabled development based on an analysis of existing ontologies of aspect oriented programming, a proposed ontology of agile methods, and a derived ontology of agile aspect oriented development

Rule-based information integration

In this report, we show the process of information integration. We specifically discuss the language used for integration. We show that integration consists of two phases, the schema mapping phase and the data integration phase. We formally define transformation rules, conversion, evolution and versioning. We further discuss the integration process from a data point of view

Detecting Ontological Conflicts in Protocols between Semantic Web Services

The task of verifying the compatibility between interacting web services has traditionally been limited to checking the compatibility of the interaction protocol in terms of message sequences and the type of data being exchanged. Since web services are developed largely in an uncoordinated way, different services often use independently developed ontologies for the same domain instead of adhering to a single ontology as standard. In this work we investigate the approaches that can be taken by the server to verify the possibility to reach a state with semantically inconsistent results during the execution of a protocol with a client, if the client ontology is published. Often database is used to store the actual data along with the ontologies instead of storing the actual data as a part of the ontology description. It is important to observe that at the current state of the database the semantic conflict state may not be reached even if the verification done by the server indicates the possibility of reaching a conflict state. A relational algebra based decision procedure is also developed to incorporate the current state of the client and the server databases in the overall verification procedure

A Peer-to-Peer Architecture for Distributed Knowledge Management.

Most of the knowledge management systems of complex organizations are based on technological architectures that are in contradiction with the social processes of knowledge creation. In particular, centralized architectures are adopted to manage a process that is intrinsically distributed. In this paper, assuming a Distributed approach to Knowledge Management (DKM), is proposed that technological and social architectures must be reciprocally consistent. Moreover, in the domain of Knowledge Management, technological architectures should be designed in order to support the interplay between two qualitatively different processes: the autonomous management of knowledge of individuals and groups - here called Knowledge Nodes (KNs) -, and the coordination required in order to exchange knowledge among them. Finally a peer to peer architecture to support knowledge exchange across distributed and autonomous KNs is presented

Semantic Constraints Satisfaction Based Improved Quality of Ontology Alignment

Development of informative and telecommunication technologies have caused to create much dissimilar information. As well with growing different information resources in ontology designs, the importance of management these dissimilar resources has increased. In spite of most matchers use diverse measures for discovery the mappings, some semantic inconsistencies in final alignment are unavoidable. So it is essential to enhance a post-processing phase to training error patterns in the final alignment. The impartial of this research was refining the ontology semantic constraints over defining semantic constraints by a different measure for suitable weighting to the constraints. The outcomes indicated that the standard evaluation measures better in the suggestive method and comparing with other top ranked matchers the used method can create enhanced outcomes

Semantic Constraints Satisfaction Based Improved Quality of Ontology Alignment

Development of informative and telecommunication technologies have caused to create much dissimilar information. As well with growing different information resources in ontology designs, the importance of management these dissimilar resources has increased. In spite of most matchers use diverse measures for discovery the mappings, some semantic inconsistencies in final alignment are unavoidable. So it is essential to enhance a post-processing phase to training error patterns in the final alignment. The impartial of this research was refining the ontology semantic constraints over defining semantic constraints by a different measure for suitable weighting to the constraints. The outcomes indicated that the standard evaluation measures better in the suggestive method and comparing with other top ranked matchers the used method can create enhanced outcomes

Hybrid mappings of complex questions over an integrated semantic space

We address the issue of measuring semantic similarity between ontologies and text by means of applying Latent Semantic Analysis. This method allows ranking of vector representations describing semantic relations according to their cosine similarity with a particular query. Our work is expected to make contributions including the introduction of reasoning about uncertainty when mapping between ontologies, an algorithm that can perform automatic mapping between concepts or relations derived from text and concepts or relations belonging to different ontologies, and the capability to infer implicit similarity between concepts or relations

Towards composing and benchmarking ontology alignments

euzenat2003iInternational audienceNo abstract available