69,815 research outputs found

    Mining Knowledge in Astrophysical Massive Data Sets

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    Modern scientific data mainly consist of huge datasets gathered by a very large number of techniques and stored in very diversified and often incompatible data repositories. More in general, in the e-science environment, it is considered as a critical and urgent requirement to integrate services across distributed, heterogeneous, dynamic "virtual organizations" formed by different resources within a single enterprise. In the last decade, Astronomy has become an immensely data rich field due to the evolution of detectors (plates to digital to mosaics), telescopes and space instruments. The Virtual Observatory approach consists into the federation under common standards of all astronomical archives available worldwide, as well as data analysis, data mining and data exploration applications. The main drive behind such effort being that once the infrastructure will be completed, it will allow a new type of multi-wavelength, multi-epoch science which can only be barely imagined. Data Mining, or Knowledge Discovery in Databases, while being the main methodology to extract the scientific information contained in such MDS (Massive Data Sets), poses crucial problems since it has to orchestrate complex problems posed by transparent access to different computing environments, scalability of algorithms, reusability of resources, etc. In the present paper we summarize the present status of the MDS in the Virtual Observatory and what is currently done and planned to bring advanced Data Mining methodologies in the case of the DAME (DAta Mining & Exploration) project.Comment: Pages 845-849 1rs International Conference on Frontiers in Diagnostics Technologie

    Towards data grids for microarray expression profiles

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    The UK DTI funded Biomedical Research Informatics Delivered by Grid Enabled Services (BRIDGES) project developed a Grid infrastructure through which research into the genetic causes of hypertension could be supported by scientists within the large Wellcome Trust funded Cardiovascular Functional Genomics project. The BRIDGES project had a focus on developing a compute Grid and a data Grid infrastructure with security at its heart. Building on the work within BRIDGES, the BBSRC funded Grid enabled Microarray Expression Profile Search (GEMEPS) project plans to provide an enhanced data Grid infrastructure to support richer queries needed for the discovery and analysis of microarray data sets, also based upon a fine-grained security infrastructure. This paper outlines the experiences gained within BRIDGES and outlines the status of the GEMEPS project, the open challenges that remain and plans for the future

    Summary of the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1)

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    Challenges related to development, deployment, and maintenance of reusable software for science are becoming a growing concern. Many scientists’ research increasingly depends on the quality and availability of software upon which their works are built. To highlight some of these issues and share experiences, the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1) was held in November 2013 in conjunction with the SC13 Conference. The workshop featured keynote presentations and a large number (54) of solicited extended abstracts that were grouped into three themes and presented via panels. A set of collaborative notes of the presentations and discussion was taken during the workshop. Unique perspectives were captured about issues such as comprehensive documentation, development and deployment practices, software licenses and career paths for developers. Attribution systems that account for evidence of software contribution and impact were also discussed. These include mechanisms such as Digital Object Identifiers, publication of “software papers”, and the use of online systems, for example source code repositories like GitHub. This paper summarizes the issues and shared experiences that were discussed, including cross-cutting issues and use cases. It joins a nascent literature seeking to understand what drives software work in science, and how it is impacted by the reward systems of science. These incentives can determine the extent to which developers are motivated to build software for the long-term, for the use of others, and whether to work collaboratively or separately. It also explores community building, leadership, and dynamics in relation to successful scientific software

    Contemporary Innovation Policy and Instruments: Challenges and Implications

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    In this paper we review major theoretical (neoclassical economics, evolutionary, systemic and knowledge-based) insights about innovation and we analyse their implications for the characteristics of contemporary innovation policy and instruments. We show that the perspectives complement each other but altogether reveal the need to redefine the current general philosophy as well as the modes of operationalisation of contemporary innovation policy. We argue that systemic instruments ensuring proper organisation of innovation systems give a promise of increased rates and desired (more sustainable) direction of innovation.systemic instruments, innovation policy, innovation theory, policy mix, innovation system, sustainability

    Report on the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2)

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    This technical report records and discusses the Second Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE2). The report includes a description of the alternative, experimental submission and review process, two workshop keynote presentations, a series of lightning talks, a discussion on sustainability, and five discussions from the topic areas of exploring sustainability; software development experiences; credit & incentives; reproducibility & reuse & sharing; and code testing & code review. For each topic, the report includes a list of tangible actions that were proposed and that would lead to potential change. The workshop recognized that reliance on scientific software is pervasive in all areas of world-leading research today. The workshop participants then proceeded to explore different perspectives on the concept of sustainability. Key enablers and barriers of sustainable scientific software were identified from their experiences. In addition, recommendations with new requirements such as software credit files and software prize frameworks were outlined for improving practices in sustainable software engineering. There was also broad consensus that formal training in software development or engineering was rare among the practitioners. Significant strides need to be made in building a sense of community via training in software and technical practices, on increasing their size and scope, and on better integrating them directly into graduate education programs. Finally, journals can define and publish policies to improve reproducibility, whereas reviewers can insist that authors provide sufficient information and access to data and software to allow them reproduce the results in the paper. Hence a list of criteria is compiled for journals to provide to reviewers so as to make it easier to review software submitted for publication as a “Software Paper.

    Research and Education in Computational Science and Engineering

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    Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

    Ancient and historical systems

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