FP6-ist INFRAWEBS European Research Project

Project Focus: The main INFRAWEBS project focus and objective is the development of an application-oriented software toolset for creating, maintaining and executing WSMO-based Semantic Web Services (SWS) within their whole life cycle. This next generation of tools and systems will enable software and service providers to build open and extensible development platforms for web service applications. These services will run on open standards and specifications, such as BPEL4WS, WSMO, WSMX, WSML, SPARQL, RDF, etc. In particular, they will be compliant with WSMO (Web Services Modelling Ontology), a W3C initiative in Semantic Web services

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

Requirements for model server enabled collaborating on building information models

The application of Building Information Modelling (BIM) has demonstrated enormous potential to deliver consistency in the construction collaboration process. BIM can define an explicit configuration for digitized information exchange, however the technology to collaborate on models has not yet delivered the industry requirements for BIM collaboration. This research project is intended to provide a fresh review of industry requirements for BIM collaboration and will analyse how these requirements can be supported using a model server as a collaboration platform. This paper presents a review of existing collaboration platforms, with a particular focus to evaluate the research and development efforts on model servers as a collaboration platform. This paper also reports on the findings of three focus group sessions with industry practitioners to identify any problems in the available collaboration systems. The focus group findings identify a number of issues in current collaboration environments which help to understand the main domains of user requirements for BIM collaboration. These requirement domains will be further analysed to identify functional and technical specifications for a model server enabled collaboration platform

iTETRIS: An Integrated Wireless and Traffic Platform for Real-Time Road Traffic Management Solutions

Wireless vehicular cooperative systems have been identified as an attractive solution to improve road traffic management, thereby contributing to the European goal of safer, cleaner, and more efficient and sustainable traffic solutions. V2V-V2I communication technologies can improve traffic management through real-time exchange of data among vehicles and with road infrastructure. It is also of great importance to investigate the adequate combination of V2V and V2I technologies to ensure the continuous and costefficient operation of traffic management solutions based on wireless vehicular cooperative solutions. However, to adequately design and optimize these communication protocols and analyze the potential of wireless vehicular cooperative systems to improve road traffic management, adequate testbeds and field operational tests need to be conducted. Despite the potential of Field Operational Tests to get the first insights into the benefits and problems faced in the development of wireless vehicular cooperative systems, there is yet the need to evaluate in the long term and large dimension the true potential benefits of wireless vehicular cooperative systems to improve traffic efficiency. To this aim, iTETRIS is devoted to the development of advanced tools coupling traffic and wireless communication simulators

Towards a Community Framework for Agent-Based Modelling

Agent-based modelling has become an increasingly important tool for scholars studying social and social-ecological systems, but there are no community standards on describing, implementing, testing and teaching these tools. This paper reports on the establishment of the Open Agent-Based Modelling Consortium, www.openabm.org, a community effort to foster the agent-based modelling development, communication, and dissemination for research, practice and education.Replication, Documentation Protocol, Software Development, Standardization, Test Beds, Education, Primitives

Probabilistic insertion, deletion and substitution error correction using Markov inference in next generation sequencing reads

Error correction of noisy reads obtained from high-throughput DNA sequencers is an important problem since read quality significantly affects downstream analyses such as detection of genetic variation and the complexity and success of sequence assembly. Most of the current error correction algorithms are only capable of recovering substitution errors. In this work, Pindel, an algorithm that simultaneously corrects insertion, deletion and substitution errors in reads from next generation DNA sequencing platforms is presented. Pindel corrects insertion, deletion and substitution errors by modelling the sequencer output as emissions of an appropriately defined Hidden Markov Model (HMM). Reads are corrected to the corresponding maximum likelihood paths using an appropriately modified Viterbi algorithm. When compared with Karect and Fiona, the top two current algorithms capable of correcting insertion, deletion and substitution errors, Pindel exhibits superior accuracy across a range of datasets

E-access, e-maturity, e-safety: a learner survey

The report explored young people's access to technology in school and at home and the skills, knowledge and confidence of learners when using technology for learning.In addition, the project has sought to identify any links between learner attitudes, school characteristics, and learners' technological skills, e-confidence and levels of e-maturity. The NFER conducted a large-scale national survey with primary and secondary school learners in England. The survey was administered between November and December 2008, and was completed by over 4,000 learners: 1,990 learners in primary schools (in Year 6) and 2,061 learners in secondary schools (in Year 10)

StochKit-FF: Efficient Systems Biology on Multicore Architectures

The stochastic modelling of biological systems is an informative, and in some cases, very adequate technique, which may however result in being more expensive than other modelling approaches, such as differential equations. We present StochKit-FF, a parallel version of StochKit, a reference toolkit for stochastic simulations. StochKit-FF is based on the FastFlow programming toolkit for multicores and exploits the novel concept of selective memory. We experiment StochKit-FF on a model of HIV infection dynamics, with the aim of extracting information from efficiently run experiments, here in terms of average and variance and, on a longer term, of more structured data.Comment: 14 pages + cover pag