Supporting text mining for e-Science: the challenges for Grid-enabled natural language processing

Over the last few years, language technology has moved rapidly from 'applied research' to 'engineering', and from small-scale to large-scale engineering. Applications such as advanced text mining systems are feasible, but very resource-intensive, while research seeking to address the underlying language processing questions faces very real practical and methodological limitations. The e-Science vision, and the creation of the e-Science Grid, promises the level of integrated large-scale technological support required to sustain this important and successful new technology area. In this paper, we discuss the foundations for the deployment of text mining and other language technology on the Grid - the protocols and tools required to build distributed large-scale language technology systems, meeting the needs of users, application builders and researchers

Towards a Security, Privacy, Dependability, Interoperability Framework for the Internet of Things

A popular application of ambient intelligence systems constitutes of assisting living services on smart buildings. As intelligence is imported in embedded equipment, the system becomes able to provide smart services (e.g. control lights, airconditioning, provide energy management services etc.). IoT is the main enabler of such environments. However, the interconnection of these cyber-physical systems and the processing of personal data raise serious security and privacy issues. In this paper we present a framework that can guarantee Security, Privacy, Dependability and Interoperability (SPDI) in IoT. Taking advantage of the underlying IoT deployment, the proposed framework not only implements the requested smart functionality but also provide modelling and administration that can guarantee those SPDI properties. Moreover, we provide an application example of the framework in a smart building scenario

Management of Scientific Experiments in Computational Modeling: Challenges and Perspectives

Currently the computer is essential to the success in conducting scientific research. In this context, e-Science appears as science performed with computer support aiming efficiency. The challenge, “Computational Modeling of artificial, naturals and socio-cultural complex systems and man-nature interaction” from SBC Great Challenges is strongly related to the e-Science context. The goal of this challenge is to create, evaluate, modify, compose, manage and exploit computer models in fields related to complex, artificial, natural, socio-cultural and human-nature systems. Technologies like semantic web service composition, data provenance, peer to peer networks and scientific software product line can be used as basis for the specification and development of an e-Science infrastructure to handle challenges and solve problems. This paper discusses the main challenges involved in developing an eScience infrastructure, presenting research challenges for the next years

Process Oriented Collaboration in Grid-Environments: A Case Study in the Construction Industry

This paper addresses the process-oriented collaboration based on a grid-based platform for the support of virtual organizations (VO), illustrated on the example of the construction industry. Distributed, organizational and IT-structures of teams involved in vintage complex projects cannot be managed with conventional methods in an appropriate manner. Both using a grid platform and grid-based services, in conjunction with semantic methods for consistency saving and goal-oriented process management can increase the efficiency of collaboration processes in large-scale projects. A hybrid grid- and web service-based architecture for the next generation of VO service and a gateway solution was developed integrating the process-oriented perspective and prototypically implemented. The problem, as well as the solution on the basis of the hybrid system architecture combing the benefits of the cutting-edge technologies, the methodical concept for modeling VO processes and their automated execution on a grid platform are discussed in detail

CYCLONE Unified Deployment and Management of Federated, Multi-Cloud Applications

Various Cloud layers have to work in concert in order to manage and deploy complex multi-cloud applications, executing sophisticated workflows for Cloud resource deployment, activation, adjustment, interaction, and monitoring. While there are ample solutions for managing individual Cloud aspects (e.g. network controllers, deployment tools, and application security software), there are no well-integrated suites for managing an entire multi cloud environment with multiple providers and deployment models. This paper presents the CYCLONE architecture that integrates a number of existing solutions to create an open, unified, holistic Cloud management platform for multi-cloud applications, tailored to the needs of research organizations and SMEs. It discusses major challenges in providing a network and security infrastructure for the Intercloud and concludes with the demonstration how the architecture is implemented in a real life bioinformatics use case

A Semantic IoT Early Warning System for Natural Environment Crisis Management

This work was supported in part by the European FP7 Funded Project TRIDEC under Grant 258723, the other project partners in helping to deliver the complete project Syste, in particular, GFZ, and the German Research Centre for Geosciences, Potsdam, Germany. The work of R. Tao was supported by the Queen Mary University of London for a Ph.D. studentship

A Semantic loT Early Warning System for Natural Environment Crisis Management

An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model.We use lightweight semantics for metadata to enhance rich sensor data acquisition.We use heavyweight semantics for top level W3CWeb Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a reployed EWS infrastructure

Web-Scale Workflow: Integrating Distributed Services

Modular applications, components, and services are all ways of describing the product of an organization\u27s efforts to embody its capabilities in autonomous software modules. In fact, the integration of services using well-established workflow paradigms could amplify an organization\u27s capabilities with the creation of a full-blown, inter-organizational system of systems. This is the essence of Web-scale workflows. Considering the recent popularity and acceptance of service-oriented technologies, the application of such distributed systems is only limited by imagination, but it\u27s also important to understand existing research challenges and their implications to various Web-scale workflow domains