High-energy physics: Down the petabyte highway

Brumfiel, Geoff

doi:10.1038/469282a

Cited by 66 publications

(44 citation statements)

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“…Детекторы LHC должны быть способны зафиксировать «портрет» события, определив траектории частиц, их типы, заряды, энергию. В 2010 году в общей сложности в ходе экспериментов было произведено 13 петабайт данных [15]. С 2011 года объемы данных, генерируемых LHC, увеличивались темпами, которые превышали самые смелые прогнозы.…”

Section: рис 2 большой адронный коллайдер [популярная механика 200unclassified

The Problem of Processing and Storage of Large Amounts of Scientific Data and Approaches to Its Solution

Анатольевич¹,

Вячеславович²

2013

Math.Biol.Bioinf.

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Аннотация. В статье рассматривается актуальная проблема значительного роста объёмов данных, получаемых, хранимых и обрабатываемых в ходе научной деятельности, в первую очередь в таких областях как биоинформатика и астрофизика. Рассматриваются современные программные методы и компьютерные технологии, используемые для работы со сверхбольшими объёмами данных. Проводится анализ состояния дел в институтах Пущинского научного центра РАН -Институте математических проблем биологии РАН и Пущинской радиоастрономической обсерватории Астрокосмического центра ФИАН им. Лебедева.

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Section: рис 2 большой адронный коллайдер [популярная механика 200unclassified

The Problem of Processing and Storage of Large Amounts of Scientific Data and Approaches to Its Solution

Анатольевич¹,

Вячеславович²

2013

Math.Biol.Bioinf.

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“…First collisions were observed almost exactly as the official opening started. Triggered by this coincidence, a study of exactly what happened to some of the first data recorded at the LHC was carried out by Brian Davies at RAL and reported in an article in Nature [3]. This followed data recorded by the ATLAS detector on 30 March 2010, during the first physics run.…”

Section: First Datamentioning

confidence: 99%

The Large Hadron Collider and Grid computing

Geddes

2012

Phil. Trans. R. Soc. A.

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We present a brief history of the beginnings, development and achievements of the worldwide Large Hadron Collider Computing Grid (wLCG). The wLCG is a huge international endeavour, which is itself embedded within, and directly influences, a much broader computing and information technology landscape. It is often impossible to identify true cause and effect, and they may appear very different from the different perspectives (e.g. information technology industry or academic researcher). This account is no different. It represents a personal view of the developments over the last two decades and is therefore inevitably biased towards those things in which the author has been personally involved.

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“…In particle physics, sufficient computing power is needed for analysis of results and storage of data produced by the European Organization for Nuclear Research (CERN) Large Hadron Collider, which has started to generate data since 2009 and produced 13 petabytes of data in 2010 [16]. In astronomy, by taking pictures of thesky the scientists try to virtualize space and mostly work in this virtual space rather than real one [17].…”

Section: Scientific Research Datamentioning

confidence: 99%

“…Essential differences between two are development methodologies, data modeling, and DW architecture. [5], [6], [7], [8], [9], [11], [12], [13], [14], [15] Big Data Value ChainData Generation [5], [11], [14], [16], [17], [18] Big Data Value ChainData Acquisition [19], [20] Big Data Value ChainData Storage [14], [18], [21], [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32] Big Data Value ChainBig Data Analytics [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44], [45], [46] Business Intelligence [13], [47], …”

Section: Dw Online Transactional Processing (Oltp) and Online Analymentioning

confidence: 99%

A Review on Business Intelligence and Big Data

Sirin

Karacan

2017

ijisae

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Improvement of data generating, processing, storing and networking technologies has made storing, capturing and sharing of data easier and cheaper than before and has enabled organizations to handle the huge volume of data at high velocity and variety, named as big data. Big data offers many opportunities when the associated difficulties are addressed properly. Business Intelligence (BI) basically focuses on transforming raw data into usable, valuable and actionable information for decision-making. It can be classified as a kind of data-driven decision support system. Although big data related papers have increased for last fifteen years, there are not sufficient papers that directly overviews big data impact on BI. As data is growing exponentially, storage, process, and analytics tools and technologies become more important for BI solutions. With the advent of big data, BI's concept, architecture, and capabilities are meant to be changed. Unlike decades before, BI now is to be extract value from huge data ocean by using big data tools as well as classical ones. So, an interclusion has emerged between big data and BI. This paper overviews the current state of the art of BI and big data, and discuss how big data era affects BI solutions in general context.

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High-energy physics: Down the petabyte highway

Cited by 66 publications

References 0 publications

The Problem of Processing and Storage of Large Amounts of Scientific Data and Approaches to Its Solution

The Problem of Processing and Storage of Large Amounts of Scientific Data and Approaches to Its Solution

The Large Hadron Collider and Grid computing

A Review on Business Intelligence and Big Data

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