|
This article is cited in 2 scientific papers (total in 2 papers)
Data access challenges for data intensive research in Russia
L. A. Kalinichenkoab, A. A. Volnovac, E. P. Gordovd, N. N. Kiselyovae, D. A. Kovalevaf, O. Yu. Malkovf, I. G. Okladnikovd, N. L. Podkolodnyig, A. S. Pozanenkoc, N. V. Ponomarevah, S. A. Stupnikovb, A. Z. Fazliyevi a Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov Moscow State University, 1-52 Leninskiye Gory, GSP-1, Moscow 119991, Russian Federation
b Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian
Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
c Space Research Institute of the Russian Academy of Sciences, 84/32 Profsoyuznaya Str., Moscow 117997, Russian Federation
d Siberian Center for Environmental Research and Training, Institute of Monitoring of Climatic and Ecological Systems of the Siberian Branch of the Russian Academy of Sciences, 10/3 Akademicheski Av., Tomsk 634055, Russian Federation
e A. A. Baikov Institute of Metallurgy and Materials Science of the Russian Academy of Sciences, 49 Leninsky Av., GSP-1, Moscow 119991, Russian Federation
f Institute of Astronomy of the Russian Academy of Sciences, 48 Pyatnitskaya Str., Moscow 119017, Russian Federation
g Center for Bioinformatics, Federal Research Research Center Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, 10 Acad. Lavrentyeva Av., Novosibirsk 630090, Russian
Federation
h Research Center of Neurology, 80 Volokolamskoe Shosse, Moscow 125367, Russian Federation
i Integrated Information Systems Center, Institute of Atmospheric Optics of the Siberian Branch of the Russian Academy of Sciences, 1 Acad. Zuev Sq., Tomsk 634055, Russian Federation
Abstract:
The goal of this survey is to analyze the global trends of development of massive data collections and related infrastructures in the world aimed at the evaluation of the opportunities for the shared usage of such collections during research, decision making, and problem solving in various data intensive domains (DIDs) in Russia. The representative set of DIDs selected for the survey includes astronomy, genomics and proteomics, neuroscience (human brain investigation), materials science, and Earth sciences. For each of such DIDs, the strategic initiatives (or large projects) in the USA and Europe aimed at creation of big data collections and the respective infrastructures planned up to 2025 are briefly overviewed. The information technology projects aimed at the development of the infrastructures supporting access to and analysis of such data collections are also briefly overviewed. The set of large data collections included into the survey and expected to be created soon is planned to be used as a reference point for the design and development of the research infrastructures for data management and analysis making them compatible with the foreign open research infrastructures. In particular, the data collections considered in the survey, the goals of their creation and the researches planned to be accomplished based on them make it possible to proceed to the design and implementation of the advanced components of the research infrastructures, such as, for example, conceptualization facilities of the application domains to be investigated in data intensive research, respective metamodels, components intended for data reuse and reproducing of programs and workflows, etc.
Keywords:
fourth paradigm; data intensive domains; research infrastructures; data collections; big data.
Received: 02.12.2015
Citation:
L. A. Kalinichenko, A. A. Volnova, E. P. Gordov, N. N. Kiselyova, D. A. Kovaleva, O. Yu. Malkov, I. G. Okladnikov, N. L. Podkolodnyi, A. S. Pozanenko, N. V. Ponomareva, S. A. Stupnikov, A. Z. Fazliyev, “Data access challenges for data intensive research in Russia”, Inform. Primen., 10:1 (2016), 2–22
Linking options:
https://www.mathnet.ru/eng/ia399 https://www.mathnet.ru/eng/ia/v10/i1/p2
|
Statistics & downloads: |
Abstract page: | 467 | Full-text PDF : | 254 | References: | 62 | First page: | 14 |
|