Enjeux autour de l'impact environnemental des humanités numériques

Le développement durable constitue un enjeu majeur des prochaines années, pour l’ensemble des activités humaines ; celles relatives à la recherche scientifique n’y échappent pas. Cet article se penche sur les enjeux environnementaux des humanités numériques. L’article est constitué de trois parties. La première partie de l’article expose le contexte et les enjeux autour de l’impact du monde numérique en général sur l’environnement. La deuxième partie de l’article s’intéresse plus précisément à l’impact environnemental des humanités numériques autour de trois axes : la numérisation, l’exploitation et la pérennisation des données. Enfin, la troisième partie expose brièvement quelques initiatives issues du domaine archivistique

Energy consumption in big data environments – a systematic mapping study

Big Data is a term that describes a large volume of structured and unstructured data. Big Data must be acquired, stored, analyzed and visualized by means of non-conventional methods requiring normally a big set of resources, which includes energy consumption. Although Big Data is not new as a phenomenom, its explosion of the interest in literature is recent and its study in new scenarios presents several gaps. On the other hand, Green IT is also a growing field in computing, given the increasing role of IT in energy consumption in the world. Green IT is aimed to reduce IT-related energy consumption and overall IT environmental impact. In order to investigate the reported initiatives regarding the Big Data and Green IT with a focus of energy consumption, the authors conducted a systematic mapping on the topic. The search strategy which was used resulted in 28 relevant studies which were relevant to the topic. We found that a majority of the studies performed present algorithms designed to reduce the energy consumption in data centres. The rest of the studies present benchmarks and energy measurements, reviews, proposals of hardware-based solutions, as well as studies which give an overview of one or more aspects on Big Data.publishedVersio

Towards Green Big Data at CERN

High-energy physics studies collisions of particles traveling near the speed of light. For statistically significant results, physicists need to analyze a huge number of such events. One analysis job can take days and process tens of millions of collisions. Today the experiments of the large hadron collider (LHC) create 10 GB of data per second and a future upgrade will cause a ten-fold increase in data. The data analysis requires not only massive hardware but also a lot of electricity. In this article, we discuss energy efficiency in scientific computing and review a set of intermixed approaches we have developed in our Green Big Data project to improve energy efficiency of CERN computing. These approaches include making energy consumption visible to developers and users, architectural improvements, smarter management of computing jobs, and benefits of cloud technologies. The open and innovative environment at CERN is an excellent playground for different energy efficiency ideas which can later find use in mainstream computing. (C) 2017 Elsevier B.V. All rights reserved.Peer reviewe