Moving back to the future of big data-driven research : reflecting on the social in genomics

With the advance of genomics, specific individual conditions have received increased attention in the generation of scientific knowledge. This spans the extremes of the aim of curing genetic diseases and identifying the biological basis of social behaviour. In this development, the ways knowledge is produced have gained significant relevance, as the data-intensive search for biology/sociality associations has repercussions on doing social research and on theory. This article argues that an in-depth discussion and critical reflection on the social configurations that are inscribed in, and reproduced by genomic data-intensive research is urgently needed. This is illustrated by debating a recent case: a large-scale genome-wide association study (GWAS) on sexual orientation that suggested partial genetic basis for same-sex sexual behaviour (Ganna et al. 2019b). This case is analysed from three angles: (1) the demonstration of how, in the process of genomics research, societal relations, understandings and categorizations are used and inscribed into social phenomena and outcomes; (2) the exploration of the ways that the (big) data-driven research is constituted by increasingly moving away from theory and methodological generation of theoretical concepts that foster the understanding of societal contexts and relations (Kitchin 2014a). Big Data Soc and (3) the demonstration of how the assumption of ‘free from theory’ in this case does not mean free of choices made, which are themselves restricted by data that are available. In questioning how key sociological categories are incorporated in a wider scientific debate on genetic conditions and knowledge production, the article shows how underlying classification and categorizations, which are inherently social in their production, can have wide ranging implications. The conclusion cautions against the marginalization of social science in the wake of developments in data-driven research that neglect social theory, established methodology and the contextual relevance of the social environment.peer-reviewe

The genetic history of the Southern Arc: a bridge between West Asia and Europe

By sequencing 727 ancient individuals from the Southern Arc (Anatolia and its neighbors in Southeastern Europe and West Asia) over 10,000 years, we contextualize its Chalcolithic period and Bronze Age (about 5000 to 1000 BCE), when extensive gene flow entangled it with the Eurasian steppe. Two streams of migration transmitted Caucasus and Anatolian/Levantine ancestry northward, and the Yamnaya pastoralists, formed on the steppe, then spread southward into the Balkans and across the Caucasus into Armenia, where they left numerous patrilineal descendants. Anatolia was transformed by intra–West Asian gene flow, with negligible impact of the later Yamnaya migrations. This contrasts with all other regions where Indo-European languages were spoken, suggesting that the homeland of the Indo-Anatolian language family was in West Asia, with only secondary dispersals of non-Anatolian Indo-Europeans from the steppe

Effects of cutting parameters on machinability characteristics of Ni-based superalloys: a review

Nickel based superalloys offer high strength, corrosion resistance, thermal stability and superb thermal fatigue properties. However, they have been one of the most difficult materials to machine due to these properties. Although we are witnessing improved machining strategies with the developing machining, tooling and inspection technologies, machining of nickel based superalloys is still a challenging task due to in-process strains and post process part quality demands

A Proposed Methodology for Evaluating HDR False Color Maps

Color mapping, which involves assigning colors to the individual elements of an underlying data distribution, is a commonly used method for data visualization. Although color maps are used in many disciplines and for a variety of tasks, in this study we focus on its usage for visualizing luminance maps. Specifically, we ask ourselves the question of how to best visualize a luminance distribution encoded in a high-dynamic-range (HDR) image using false colors such that the resulting visualization is the most descriptive. To this end, we first propose a definition for descriptiveness. We then propose a methodology to evaluate it subjectively. Then, we propose an objective metric that correlates well with the subjective evaluation results. Using this metric, we evaluate several false coloring strategies using a large number of HDR images. Finally, we conduct a second psychophysical experiment using images representing a diverse set of scenes. Our results indicate that the luminance compression method has a significant effect and the commonly used logarithmic compression is inferior to histogram equalization. Furthermore, we find that the default color scale of the Radiance global illumination software consistently performs well when combined with histogram equalization. On the other hand, the commonly used rainbow color scale was found to be inferior. We believe that the proposed methodology is suitable for evaluating future color mapping strategies as well