Analyzing and Modeling Medical Data on Distributed Computing Infrastructures

Researchers want to analyse Health Care data which may requires large pools of compute and data resources. To have them they need access to Distributed Computing Infrastructures (DCI). To use them it requires expertise which researchers may not have. Workflows can hide infrastructures. There are many workflow systems but they are not interoperable. To learn a workflow system and create workflows in a workflow system may require significant effort. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows of other workflow systems. As a result, the lack of interoperability prevents workflow sharing and a vast amount of research efforts is wasted. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed the Coarse-Grained Interoperability (CGI) to enable workflow sharing. The project created the SHIWA Simulation Platform (SSP) to support CGI as a production-level service. The paper describes how the CGI approach can be used for analysis and simulation in Health Care.

Networked learning ten years on: the rise of the virtual graduate school

The aim of this paper is to reflect on how conceptions of networked learning have changed, particularly in relation to educational practices and uses of technology, that can nurture new ideas of networked learning to sustain multiple and diverse communities of practice in institutional settings. Our work is framed using two theoretical frameworks: Giddens's (1984) structuration theory and Callon & Latour's (1981) Actor Network Theory as critiqued by Fox (2005) in relation to networked learning. We use these frameworks to analyse and critique ideas of networked learning embodied in both cases. We investigate three questions: (a) the role of individual agency in the development of networked learning; (b) the impact of technological developments on approaches to supporting students within institutional infrastructures; and (c) designing networked learning to incorporate Web 2.0 practices that sustain multiple communities and foster engagement with knowledge in new ways. We use an interpretivist approach by drawing on experiential knowledge of the Masters programme in Networked Collaborative Learning and the decision making process of designing the virtual graduate schools. At this early stage, we have limited empirical data related to the student experience of networked learning in current and earlier projects. Our findings indicate that the use of two different theoretical frameworks provided an essential tool in illuminating, situating and informing the process of designing networked learning that involves supporting multiple and diverse communities of practice in institutional settings. These theoretical frameworks have also helped us to analyze our existing projects as case studies and to problematize and begin to understand the challenges we face in facilitating the participation of research students in networked learning communities of practice and the barriers to that participation. We have also found that this process of theorizing has given us a way of reconceptualizing communities of practice within research settings that have the potential to lead to new ideas of networked learning.

Commercial Use of WS-PGRADE/gUSE

Although originally an academic and research product, the WS-PGRADE/gUSE framework is increasingly applied by commercial institutions too. Within the SCI-BUS project, several commercial gateways have been developed by various companies. WS-PGRADE/gUSE is also intensively used within another European research project, CloudSME (Cloud-based Simulation Platform for Manufacturing and Engineering). This chapter provides an overview and de-scribes in detail some commercial WS-PGRADE/gUSE based gateway implemen-tations. Two representative case studies from the SCI-BUS project, the Build and Test portal and the eDOX Archiver Gateway are introduced. An overview of WS-PGRADE/gUSE based gateways for running simulation applications in the cloud within the CloudSME project is also provided.

WS-PGRADE/gUSE in European Projects

Besides core project partners, the SCI-BUS project also supported several external user communities in developing and setting up customized science gateways. The focus was on large communities typically represented by other European research projects. However, smaller local efforts with the potential of generalizing the solution to wider communities were also supported. This chapter gives an overview of support activities related to user communities external to the SCI-BUS project. A generic overview of such activities is provided followed by the detailed description of three gateways developed in collaboration with European projects: the agINFRA Science Gateway for Workflows for agricultural research, the VERCE Science Gateway for seismology, and the DRIHM Science Gateway for weather research and forecasting.

Developing Science Gateways at Various Levels of Granularity Using WS-PGRADE/gUSE

Science gateways can provide access to distributed computing resources and applications at very different levels of granularity. Some gateways do not even hide the details of the underlying infrastructure, while on the other end some provide completely customized high-level interfaces to end-users. In this chapter the different granularity levels at which science gateways can be developed with WS-PGRADE/gUSE are analysed. The differences between these various granu-larity levels are also illustrated via the example of a molecular docking gateway and its four different implementations.

Sharing science gateway artefacts through repositories

Researchers want to run scientific experiments focusing on their disciplines. They do not want to know how and where the experiments are executed. Science gateways hide details by coordinating the execution of experiments using different infrastructures and workflow systems. ER-flow/SHIWA and SCI-BUS project developed repositories to share artefacts such as applications, portlets, workflows, etc. inside and among research communities. Sharing artefacts in re-positories enable gateway developers to reuse them when building a new gateway and/or creating a new application.

Enabling Scientific Workflow Sharing through Coarse-Grained Interoperability

E-scientists want to run their scientific experiments on Distributed Computing Infrastructures (DCI) to be able to access large pools of resources and services. To run experiments on these infrastructures requires specific expertise that e-scientists may not have. Workflows can hide resources and services as a virtualization layer providing a user interface that e-scientists can use. There are many workflow systems used by research communities but they are not interoperable. To learn a workflow system and create workflows in this workflow system may require significant efforts from e-scientists. Considering these efforts it is not reasonable to expect that research communities will learn new workflow systems if they want to run workflows developed in other workflow systems. The solution is to create workflow interoperability solutions to allow workflow sharing. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed two interoperability solutions to support workflow sharing: Coarse-Grained Interoperability (CGI) and Fine-Grained Interoperability (FGI). The project created the SHIWA Simulation Platform (SSP) to implement the Coarse-Grained Interoperability approach as a production-level service for research communities. The paper describes the CGI approach and how it enables sharing and combining existing workflows into complex applications and run them on Distributed Computing Infrastructures. The paper also outlines the architecture, components and usage scenarios of the simulation platform.

Regional collaborations and indigenous innovation capabilities in China: A multivariate method for the analysis of regional innovation systems

In this study we analyse the emerging patterns of regional collaboration for innovation projects in China, using official government statistics of 30 Chinese regions. We propose the use of Ordinal Multidimensional Scaling and Cluster analysis as a robust method to study regional innovation systems. Our results show that regional collaborations amongst organisations can be categorised by means of eight dimensions: public versus private organisational mindset; public versus private resources; innovation capacity versus available infrastructures; innovation input (allocated resources) versus innovation output; knowledge production versus knowledge dissemination; and collaborative capacity versus collaboration output. Collaborations which are aimed to generate innovation fell into 4 categories, those related to highly specialised public research institutions, public universities, private firms and governmental intervention. By comparing the representative cases of regions in terms of these four innovation actors, we propose policy measures for improving regional innovation collaboration within China.

Housing market trend and rail transport investments in the city of Naples

Rail transport investments can influence housing market trends, as demonstrated in the literature. However many empirical researches highlight that different results can derive from different urban context applications and that each case should be threaten separately. It is for this reason that this paper is focused on the single case of the city of Naples, where many rail transport investments have been carried out in the last decades. The aim of this study is to give an interpretation of the housing values changes due to the opening of new metro stations. This study applies GIS tools in order to show the spatial distribution and the intensity of rail impacts in different areas of the urban system from 1994 to 2004. This study shows that the extent of the impacts varies from place to place and the effects intensity requires the presence of several complementary factors such as central location of the new stations and the presence of urban planning policies in the transit corridors. This again testifies how housing market is strictly related to the infrastructures investments planning and urban design.

Extending Science Gateway Frameworks to Support Big Data Applications in the Cloud

Cloud computing offers massive scalability and elasticity required by many scien-tific and commercial applications. Combining the computational and data handling capabilities of clouds with parallel processing also has the potential to tackle Big Data problems efficiently. Science gateway frameworks and workflow systems enable application developers to implement complex applications and make these available for end-users via simple graphical user interfaces. The integration of such frameworks with Big Data processing tools on the cloud opens new oppor-tunities for application developers. This paper investigates how workflow sys-tems and science gateways can be extended with Big Data processing capabilities. A generic approach based on infrastructure aware workflows is suggested and a proof of concept is implemented based on the WS-PGRADE/gUSE science gateway framework and its integration with the Hadoop parallel data processing solution based on the MapReduce paradigm in the cloud. The provided analysis demonstrates that the methods described to integrate Big Data processing with workflows and science gateways work well in different cloud infrastructures and application scenarios, and can be used to create massively parallel applications for scientific analysis of Big Data.

Policy mixes for resource efficiency – conceptual issues, design and assessment challenges

Since the 1950s the global consumption of natural resources has skyrocketed, both in magnitude and in the range of resources used. Closely coupled with emissions of greenhouse gases, land consumption, pollution of environmental media, and degradation of ecosystems, as well as with economic development, increasing resource use is a key issue to be addressed in order to keep the planet Earth in a safe and just operating space. This requires thinking about absolute reductions in resource use and associated environmental impacts, and, when put in the context of current re-focusing on economic growth at the European level, absolute decoupling, i.e., maintaining economic development while absolutely reducing resource use and associated environmental impacts. Changing behavioural, institutional and organisational structures that lock-in unsustainable resource use is, thus, a formidable challenge as existing world views, social practices, infrastructures, as well as power structures, make initiating change difficult. Hence, policy mixes are needed that will target different drivers in a systematic way. When designing policy mixes for decoupling, the effect of individual instruments on other drivers and on other instruments in a mix should be considered and potential negative effects be mitigated. This requires smart and time-dynamic policy packaging. This Special Issue investigates the following research questions: What is decoupling and how does it relate to resource efficiency and environmental policy? How can we develop and realize policy mixes for decoupling economic development from resource use and associated environmental impacts? And how can we do this in a systemic way, so that all relevant dimensions and linkages—including across economic and social issues, such as production, consumption, transport, growth and wellbeing­—are taken into account? In addressing these questions, the overarching goals of this Special Issue are to: address the challenges related to more sustainable resource-use; contribute to the development of successful policy tools and practices for sustainable development and resource efficiency (particularly through the exploration of socio-economic, scientific, and integrated aspects of sustainable development); and inform policy debates and policy-making. The Special Issue draws on findings from the EU and other countries to offer lessons of international relevance for policy mixes for more sustainable resource-use, with findings of interest to policy makers in central and local government and NGOs, decision makers in business, academics, researchers, and scientists.

Sustainability and Community Networks

Community networks are IP-based computer networks that are operated by a community as a common good. In Europe, the most well-known community networks are Guifi in Catalonia, Freifunk in Berlin, Ninux in Italy, Funkfeuer in Vienna and the Athens Wireless Metropolitan Network in Greece. This paper deals with community networks as alternative forms of Internet access and alternative infrastructures and asks: What does sustainability and unsustainability mean in the context of community networks? What advantages do such networks have over conventional forms of Internet access and infrastructure provided by large telecommunications corporations? In addition what disadvantages do they face at the same time? This article provides a framework for thinking dialectically about the un/sustainability of community networks. It provides a framework of practical questions that can be asked when assessing power structures in the context of Internet infrastructures and access. It presents an overview of environmental, economic, political and cultural contradictions that community networks may face as well as a typology of questions that can be asked in order to identify such contradictions.