An Ontology Model to Support the Automated Evaluation of Software

Even though previous research has tried to model Software Engineering knowledge, focusing either on the entire discipline or on parts of it, we lack an integrated conceptual model for representing software evaluations, and we also lack the information related to them that supports their definition and enables their automation and reproducibility. This paper presents an extensible ontology model for representing software evaluations and evaluation campaigns, i.e., worldwide activities where a group of tools is evaluated according to a certain evaluation specification using common test data. During the development of the ontologies, we have reused current standards and models and have linked these ontologies with some renowned ones

OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories

In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The Apache Maven approach has proven its success in distributed collaborative Software Engineering by its widespread adoption. The contribution of this paper is a new design artifact called OntoMaven. OntoMaven adopts the Maven-based development methodology and adapts its concepts to knowledge engineering for Maven-based ontology development and management of ontology artifacts in distributed ontology repositories.Comment: Pre-print submission to 9th International Workshop on Semantic Web Enabled Software Engineering (SWESE2013). Berlin, Germany, December 2-5, 201

Ontology of core data mining entities

In this article, we present OntoDM-core, an ontology of core data mining entities. OntoDM-core defines themost essential datamining entities in a three-layered ontological structure comprising of a specification, an implementation and an application layer. It provides a representational framework for the description of mining structured data, and in addition provides taxonomies of datasets, data mining tasks, generalizations, data mining algorithms and constraints, based on the type of data. OntoDM-core is designed to support a wide range of applications/use cases, such as semantic annotation of data mining algorithms, datasets and results; annotation of QSAR studies in the context of drug discovery investigations; and disambiguation of terms in text mining. The ontology has been thoroughly assessed following the practices in ontology engineering, is fully interoperable with many domain resources and is easy to extend

Semantic model-driven development of web service architectures.

Building service-based architectures has become a major area of interest since the advent of Web services. Modelling these architectures is a central activity. Model-driven development is a recent approach to developing software systems based on the idea of making models the central artefacts for design representation, analysis, and code generation. We propose an ontology-based engineering methodology for semantic model-driven composition and transformation of Web service architectures. Ontology technology as a logic-based knowledge representation and reasoning framework can provide answers to the needs of sharable and reusable semantic models and descriptions needed for service engineering. Based on modelling, composition and code generation techniques for service architectures, our approach provides a methodological framework for ontology-based semantic service architecture

Flexible coordination techniques for dynamic cloud service collaboration

The provision of individual, but also composed services is central in cloud service provisioning. We describe a framework for the coordination of cloud services, based on a tuple‐space architecture which uses an ontology to describe the services. Current techniques for service collaboration offer limited scope for flexibility. They are based on statically describing and compositing services. With the open nature of the web and cloud services, the need for a more flexible, dynamic approach to service coordination becomes evident. In order to support open communities of service providers, there should be the option for these providers to offer and withdraw their services to/from the community. For this to be realised, there needs to be a degree of self‐organisation. Our techniques for coordination and service matching aim to achieve this through matching goal‐oriented service requests with providers that advertise their offerings dynamically. Scalability of the solution is a particular concern that will be evaluated in detail

A Personalized Framework for Trust Assessment

The number of computational trust models has been increasing quickly in recent years yet their applications for automating trust evaluation are still limited. The main obstacle is the difficulties in selecting a suitable trust model and adapting it for particular trust modeling requirements, which varies greatly due to the subjectivity of human trust. The Personalized Trust Framework (PTF) presented in this paper aims to address this problem by providing a mechanism for human users to capture their trust evaluation process in order for it to be replicated by computers. In more details, a user can specify how he selects a trust model based on information about the subject whose trustworthiness he needs to evaluate and how that trust model is configured. This trust evaluation process is then automated by the PTF making use of the trust models flexibly plugged into the PTF by the user. By so doing, the PTF enable users reuse and personalize existing trust models to suit their requirements without having to reprogram those models

Transitioning Applications to Semantic Web Services: An Automated Formal Approach

Semantic Web Services have been recognized as a promising technology that exhibits huge commercial potential, and attract significant attention from both industry and the research community. Despite expectations being high, the industrial take-up of Semantic Web Service technologies has been slower than expected. One of the main reasons is that many systems have been developed without considering the potential of the web in integrating services and sharing resources. Without a systematic methodology and proper tool support, the migration from legacy systems to Semantic Web Service-based systems can be a very tedious and expensive process, which carries a definite risk of failure. There is an urgent need to provide strategies which allow the migration of legacy systems to Semantic Web Services platforms, and also tools to support such a strategy. In this paper we propose a methodology for transitioning these applications to Semantic Web Services by taking the advantage of rigorous mathematical methods. Our methodology allows users to migrate their applications to Semantic Web Services platform automatically or semi-automatically