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相关论文: The Digital Sky Project: Prototyping Virtual Obser…

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Astronomy is entering a new era as multiple, large area, digital sky surveys are in production. The resulting datasets are truly remarkable in their own right; however, a revolutionary step arises in the aggregation of complimentary…

天体物理学 · 物理学 2007-05-23 A. S. Szalay , R. J. Brunner

Astronomy has a long history of acquiring, systematizing, and interpreting large quantities of data. Starting from the earliest sky atlases through the first major photographic sky surveys of the 20th century, this tradition is continuing…

天体物理学 · 物理学 2007-05-23 Robert J. Brunner , S. George Djorgovski , Thomas A. Prince , Alex S. Szalay

All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transform the scientific practice, but also poses a number of common…

天体物理学 · 物理学 2016-11-17 S. G. Djorgovski

In the last decade a new generation of telescopes and sensors has allowed the production of a very large amount of data and astronomy has become, a data-rich science; this transition is often labeled as: "data revolution" and "data…

天体物理仪器与方法 · 物理学 2013-04-25 Stefano Cavuoti

Sky surveys represent a fundamental data basis for astronomy. We use them to map in a systematic way the universe and its constituents, and to discover new types of objects or phenomena. We review the subject, with an emphasis on the…

天体物理仪器与方法 · 物理学 2015-05-20 S. G. Djorgovski , A. A. Mahabal , A. J. Drake , M. J. Graham , C. Donalek

We review some aspects of the current state of data-intensive astronomy, its methods, and some outstanding data analysis challenges. Astronomy is at the forefront of "big data" science, with exponentially growing data volumes and data…

天体物理仪器与方法 · 物理学 2014-11-04 G. Longo , M. Brescia , S. G. Djorgovski , S. Cavuoti , C. Donalek

We review some of the scientific opportunities and technical challenges posed by the exploration of the large digital sky surveys, in the context of a Virtual Observatory (VO). The VO paradigm will profoundly change the way observational…

Traditional science searched for new objects and phenomena that led to discoveries. Tomorrow's science will combine together the large pool of information in scientific archives and make discoveries. Scienthists are currently keen to…

数据库 · 计算机科学 2007-05-23 Tanu Malik , Alex S. Szalay , Tamas Budavari , Ani R. Thakar

Over the past decade, sky surveys such as the Sloan Digital Sky Survey have proven the power of large data sets for answering fundamental astrophysical questions. This observational progress, based on a synergy of advances in telescope…

天体物理仪器与方法 · 物理学 2010-09-14 J. Anthony Tyson

Astronomy has been at the forefront of the development of the techniques and methodologies of data intensive science for over a decade with large sky surveys and distributed efforts such as the Virtual Observatory. However, it faces a new…

天体物理仪器与方法 · 物理学 2012-08-14 Matthew J. Graham , S. G. Djorgovski , Ashish Mahabal , Ciro Donalek , Andrew Drake , Giuseppe Longo

Recent and forthcoming advances in instrumentation, and giant new surveys, are creating astronomical data sets that are not amenable to the methods of analysis familiar to astronomers. Traditional methods are often inadequate not merely…

天体物理仪器与方法 · 物理学 2024-01-30 Meyer Z. Pesenson , Isaac Z. Pesenson , Bruce McCollum

Data volumes from multiple sky surveys have grown from gigabytes into terabytes during the past decade, and will grow from terabytes into tens (or hundreds) of petabytes in the next decade. This exponential growth of new data both enables…

天体物理仪器与方法 · 物理学 2009-11-04 Kirk D. Borne

Large digital sky surveys, over a broad range of wavelengths, both from the ground and from space observatories, are becoming a major source of astronomical data. Some examples include the Sloan Digital Sky Survey (SDSS) and the Digital…

天体物理学 · 物理学 2015-06-24 S. George Djorgovski , Robert J. Brunner

Astronomical datasets are growing in size and diversity, posing severe technical problems. At the same time scientific goals increasingly require the analysis of very large amounts of data, and data from multiple archives. The Virtual…

天体物理仪器与方法 · 物理学 2009-05-14 A. Lawrence

Like every other field of intellectual endeavor, astronomy is being revolutionised by the advances in information technology. There is an ongoing exponential growth in the volume, quality, and complexity of astronomical data sets, mainly…

天体物理学 · 物理学 2009-11-07 S. G. Djorgovski , A. Mahabal , R. Brunner , R. Williams , R. Granat , D. Curkendall , J. Jacob , P. Stolorz

The recent explosion of recorded digital data and its processed derivatives threatens to overwhelm researchers when analysing their experimental data or when looking up data items in archives and file systems. While current hardware…

We review some of the recent developments and challenges posed by the data analysis in modern digital sky surveys, which are representative of the information-rich astronomy in the context of Virtual Observatory. Illustrative examples…

天体物理学 · 物理学 2016-11-18 S. G. Djorgovski , C. Donalek , A. Mahabal , R. Williams , A. Drake , M. Graham , E. Glikman

Astronomy is one of the most data-intensive of the sciences. Data technology is accelerating the quality and effectiveness of its research, and the rate of astronomical discovery is higher than ever. As a result, many view astronomy as…

天体物理学 · 物理学 2007-05-23 Ray P Norris

Modern scientific data mainly consist of huge datasets gathered by a very large number of techniques and stored in very diversified and often incompatible data repositories. More in general, in the e-science environment, it is considered as…

天体物理仪器与方法 · 物理学 2010-10-20 M. Brescia , G. Longo , F. Pasian

The analysis and an efficient scientific exploration of the Digital Palomar Observatory Sky Survey (DPOSS) represents a major technical challenge. The input data set consists of 3 Terabytes of pixel information, and contains a few billion…

天体物理学 · 物理学 2015-06-24 S. G. Djorgovski , R. R. de Carvalho , S. C. Odewahn , R. R. Gal , J. Roden , P. Stolorz , A. Gray
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