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.

Governing Big Data: The Political Economy of Power, Knowledge and Consumer Finance in the Digital Age

This dissertation offers a critical international political economy (IPE) analysis of the ways in which consumer information has been governed throughout the formal history of consumer finance (1840 – present). Drawing primarily on the United States, this project problematizes the notion of consumer financial big data as a ‘new era’ by tracing its roots historically from late nineteenth century through to the present. Using a qualitative case study approach, this project applies a unique theoretical framework to three instances of governance in consumer credit big data. Throughout, the historically specific means used to govern consumer credit data are rooted in dominant ideas, institutions and material factors.

Big Money is Moving in, Docklands Community Poster Project and posters from the East London Health Project

The exhibition took as its departure the rediscovery of the experience of the working photographer from 1920-1930, and the new intellectual context that emerged subsequent to 1968, that was marked by a new form of urban resistance.

A World without Causation: Big Data and the Coming of Age of Posthumanism

Advocates of Big Data assert that we are in the midst of an epistemological revolution, promising the displacement of the modernist methodological hegemony of causal analysis and theory generation. It is alleged that the growing ‘deluge’ of digitally generated data, and the development of computational algorithms to analyse them, has enabled new inductive ways of accessing everyday relational interactions through their ‘datafication’. This paper critically engages with these discourses of Big Data and complexity, particularly as they operate in the discipline of International Relations, where it is alleged that Big Data approaches have the potential for developing self-governing societal capacities for resilience and adaptation through the real-time reflexive awareness and management of risks and problems as they arise. The epistemological and ontological assumptions underpinning Big Data are then analysed to suggest that critical and posthumanist approaches have come of age through these discourses, enabling process-based and relational understandings to be translated into policy and governance practices. The paper thus raises some questions for the development of critical approaches to new posthuman forms of governance and knowledge production.

How the World Learned to Stop Worrying and Love Failure: Big Data, Resilience and Emergent Causality

In modernity, failure was the discourse of critique, today, it is increasingly the discourse of power: failure has changed its allegiances. Over the last two decades, failure has been enfolded into discourses of power, facilitating the development of new policy approaches. Foremost among governing approaches that seek to include and to govern through failure is that of resilience. This article seeks to reflect upon how the understanding of failure has become transformed in this process, particularly linking this transformation to the radical appreciation of contingency and of the limits to instrumental cause-and-effect approaches to rule. Whereas modernity was shaped by a contestation over failure as an epistemological boundary, under conditions of contingency and complexity there appears to be a new consensus on failure as an ontological necessity. This problematic ‘ontological turn’ is illustrated using examples of changing approaches to risks, especially anthropogenic understandings of environmental threats, formerly seen as ‘natural’.

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains.

Big Data Analytics for Earth Sciences: the EarthServer approach

Big Data Analytics is an emerging field since massive storage and computing capabilities have been made available by advanced e-infrastructures. Earth and Environmental sciences are likely to benefit from Big Data Analytics techniques supporting the processing of the large number of Earth Observation datasets currently acquired and generated through observations and simulations. However, Earth Science data and applications present specificities in terms of relevance of the geospatial information, wide heterogeneity of data models and formats, and complexity of processing. Therefore, Big Earth Data Analytics requires specifically tailored techniques and tools. The EarthServer Big Earth Data Analytics engine offers a solution for coverage-type datasets, built around a high performance array database technology, and the adoption and enhancement of standards for service interaction (OGC WCS and WCPS). The EarthServer solution, led by the collection of requirements from scientific communities and international initiatives, provides a holistic approach that ranges from query languages and scalability up to mobile access and visualization. The result is demonstrated and validated through the development of lighthouse applications in the Marine, Geology, Atmospheric, Planetary and Cryospheric science domains.

Supernova 2013fc in a circumnuclear ring of a luminous infrared galaxy: The big brother of SN 1998S

We present photometric and spectroscopic observations of SN 2013fc, a bright type II supernova (SN) in a circumnuclear star-forming ring in the luminous infrared galaxy ESO 154-G010, observed as part of the Public ESO Spectroscopic Survey of Transient Objects. SN 2013fc is both photometrically and spectroscopically similar to the well-studied type IIn SN 1998S and to the bright type II-L SN 1979C. It exhibits an initial linear decline, followed by a short plateau phase and a tail phase with a decline too fast for ⁵⁶Co decay with full γ -ray trapping. Initially, the spectrum was blue and featureless. Later on, a strong broad (~8000 km s^-1) H α emission profile became prominent. We apply a STARLIGHT stellar population model fit to the SN location (observed when the SN had faded) to estimate a high extinction of A_V = 2.9 ± 0.2 mag and an age of 10⁺³ _-2 Myr for the underlying cluster.We compare the SN to SNe 1998S and 1979C and discuss its possible progenitor star considering the similarities to these events. With a peak brightness of B = -20.46 ± 0.21 mag, SN 2013fc is 0.9 mag brighter than SN 1998S and of comparable brightness to SN 1979C.We suggest that SN 2013fc was consistent with a massive red supergiant (RSG) progenitor. Recent mass loss probably due to a strong RSG wind created the circumstellar matter illuminated through its interaction with the SN ejecta. We also observe a near-infrared excess, possibly due to newly condensed dust.

The Changing Face of Neolithic and Bronze Age Ireland: A Big Data Approach to the Settlement and Burial Records

This paper synthesizes and discusses the spatial and temporal patterns of archaeological sites in Ireland, spanning the Neolithic period and the Bronze Age transition (4300–1900 cal BC), in order to explore the timing and implications of the main changes that occurred in the archaeological record of that period. Large amounts of new data are sourced from unpublished developer-led excavations and combined with national archives, published excavations and online databases. Bayesian radiocarbon models and context- and sample-sensitive summed radiocarbon probabilities are used to examine the dataset. The study captures the scale and timing of the initial expansion of Early Neolithic settlement and the ensuing attenuation of all such activity—an apparent boom-and-bust cycle. The Late Neolithic and Chalcolithic periods are characterised by a resurgence and diversification of activity. Contextualisation and spatial analysis of radiocarbon data reveals finer-scale patterning than is usually possible with summed-probability approaches: the boom-and-bust models of prehistoric populations may, in fact, be a misinterpretation of more subtle demographic changes occurring at the same time as cultural change and attendant differences in the archaeological record.

Black Night At Big Thunder Mountain

Novel

Ten Questions for Future Regulation of Big Data: A Comparative and Empirical Legal Study

Much has been written about Big Data from a technical, economical, juridical and ethical perspective. Still, very little empirical and comparative data is available on how Big Data is approached and regulated in Europe and beyond. This contribution makes a first effort to fill that gap by presenting the reactions to a survey on Big Data from the Data Protection Authorities of fourteen European countries and a comparative legal research of eleven countries. This contribution presents those results, addressing 10 challenges for the regulation of Big Data.

Troca de informação e ações conjuntas desenvolvidas pelo grupo de big bands Movimento Elefantes

Este trabalho visou a identificação das trocas de informações e ações conjuntas realizadas por participantes do Movimento Elefantes (ME), grupo constituído por 10 Big Bands formado em 2009. Buscou-se também identificar quais são os objetivos do grupamento, conforme são entendidos pelos participantes, e as dificuldades enfrentas pelo ME, por eles apontadas. A pesquisa de campo teve natureza exploratória, tendo sido aplicado aos músicos questionário via internet, com questões abertas. Os resultados obtidos, com base em análise de conteúdo, apontam que as trocas estão relacionadas predominantemente com questões estéticas, sendo também relevantes as indicações profissionais. Os objetivos considerados pelos respondentes são criar mais espaços para apresentação e promover integração entre os músicos. Embora estes objetivos sejam atingidos, o grupamento enfrenta dificuldades significativas, devido ao baixo comprometimento dos músicos e estrutura organizacional precária. São sugeridas medidas visando melhorar os resultados deste grupamento, que está inserido na chamada indústria criativa.

Troca de informação e ações conjuntas desenvolvidas pelo grupo de Big Bands Movimento Elefantes

Este trabalho visou a identificação das trocas de informações e ações conjuntas realizadas por participantes do Movimento Elefantes (ME), grupo constituído por 10 Big Bands formado em 2009. Buscou-se também identificar quais são os objetivos do grupamento, conforme são entendidos pelos participantes, e as dificuldades enfrentas pelo ME, por eles apontadas. A pesquisa de campo teve natureza exploratória, tendo sido aplicado aos músicos questionário via internet, com questões abertas. Os resultados obtidos, com base em análise de conteúdo, apontam que as trocas estão relacionadas predominantemente com questões estéticas, sendo também relevantes as indicações profissionais. Os objetivos considerados pelos respondentes são criar mais espaços para apresentação e promover integração entre os músicos. Embora estes objetivos sejam atingidos, o grupamento enfrenta dificuldades significativas, devido ao baixo comprometimento dos músicos e estrutura organizacional precária. São sugeridas medidas visando melhorar os resultados deste grupamento, que está inserido na chamada indústria criativa.