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.

The Big Crunch : A Mapping of the Swedish Party System from 1991 to 2010

Previous research claims that there has been a narrowing of distance between the Swedish political parties. Typically, such research into political distance has primarily focused on studying voters rather than the political parties themselves. In this article, the author conducts a longitudinal analysis of Comparative Manifesto Project data to determine if, and to what extent, the political parties have converged ideologically on a Left-Right continuum in the period 1991-2010. After first unraveling the concept of political distance, the author moves on to explain why the ideological dispersion of political parties is an important and consequential characteristic within party systems. Furthermore, the author argues that the Left-Right ideological scale continues to be a highly useful model with which to conceptualize and study this characteristic. The author then discusses the methodological approach and explains why quantitative manifesto data, often overlooked in favor of voter interview data, is deemed a valid and reliable material for measuring the ideological positions of political parties. The findings are that there indeed have been over all tendencies of ideological convergence between the blocs and that, in terms of how political parties are dispersed on a Left- Right ideological continuum, by 2010, the Swedish party system (the Sweden Democrats excluded) had become much less polarized than it had been in 1991.

Big Data Analysis in Social Networks : Extracting Food Preferences of Vegans from Twitter

Market research is often conducted through conventional methods such as surveys, focus groups and interviews. But the drawbacks of these methods are that they can be costly and timeconsuming. This study develops a new method, based on a combination of standard techniques like sentiment analysis and normalisation, to conduct market research in a manner that is free and quick. The method can be used in many application-areas, but this study focuses mainly on the veganism market to identify vegan food preferences in the form of a profile. Several food words are identified, along with their distribution between positive and negative sentiments in the profile. Surprisingly, non-vegan foods such as cheese, cake, milk, pizza and chicken dominate the profile, indicating that there is a significant market for vegan-suitable alternatives for such foods. Meanwhile, vegan-suitable foods such as coconut, potato, blueberries, kale and tofu also make strong appearances in the profile. Validation is performed by using the method on Volkswagen vehicle data to identify positive and negative sentiment across five car models. Some results were found to be consistent with sales figures and expert reviews, while others were inconsistent. The reliability of the method is therefore questionable, so the results should be used with caution.

Data Science Seminar: Generic Big Data Processing for Advancing Situation Awareness and Decision-Support

The generation of heterogeneous big data sources with ever increasing volumes, velocities and veracities over the he last few years has inspired the data science and research community to address the challenge of extracting knowledge form big data. Such a wealth of generated data across the board can be intelligently exploited to advance our knowledge about our environment, public health, critical infrastructure and security. In recent years we have developed generic approaches to process such big data at multiple levels for advancing decision-support. It specifically concerns data processing with semantic harmonisation, low level fusion, analytics, knowledge modelling with high level fusion and reasoning. Such approaches will be introduced and presented in context of the TRIDEC project results on critical oil and gas industry drilling operations and also the ongoing large eVacuate project on critical crowd behaviour detection in confined spaces.

Utilizing “Big Data” to Improve the Hotel Sector’s Energy Efficiency: Lessons from Recent Economics Research

Hotel chains have access to a treasure trove of “big data” on individual hotels’ monthly electricity and water consumption. Benchmarked comparisons of hotels within a specific chain create the opportunity to cost-effectively improve the environmental performance of specific hotels. This paper describes a simple approach for using such data to achieve the joint goals of reducing operating expenditure and achieving broad sustainability goals. In recent years, energy economists have used such “big data” to generate insights about the energy consumption of the residential, commercial, and industrial sectors. Lessons from these studies are directly applicable for the hotel sector. A hotel’s administrative data provide a “laboratory” for conducting random control trials to establish what works in enhancing hotel energy efficiency.