Big data in astronomy: from evolution to revolution
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2019-05-05 https://doi.org/10.14419/ijaa.v7i1.18029
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Astronomical Big Data, Computational Mathematics & Statistics, Space Probes & Super Telescopes-Radio Telescopes, Machine Learning-Data Mining. -
Abstract
Big data is pushing astronomy in a new direction. Massive amounts of astronomical big data produced by the new generations of powerful instruments and simulations are exponentially gathered every day. Big data like astronomical images, infrared, microwave, ultraviolet, X-rays and gamma generated by stars, galaxies and black holes are observed by the new generations of space telescopes. It may take years to uncover the hidden signals in such data that may already hold answers to some of the fundamental questions of the universe we’re seeking. In this paper, we attempt to present a short review about the astronomical big data and how can such massive data change our understanding of the universe.
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References
[1] Yang, C., Huang, Q., Li, Z., Liu, K. and Hu, F., 2017. Big Data and cloud computing: innovation opportunities and challenges. International Journal of Digital Earth, 10(1), pp.13-53. https://doi.org/10.1080/17538947.2016.1239771.
[2] Feigelson, E.D. and Babu, G.J., 2012. Big data in astronomy. Significance, 9(4), pp.22-25. https://doi.org/10.1111/j.1740-9713.2012.00587.x.
[3] Kremer, J., Stensbo-Smidt, K., Gieseke, F., Pedersen, K.S. and Igel, C., 2017. Big universe, big data: machine learning and image analysis for astronomy. arXiv preprint arXiv:1704.04650. https://doi.org/10.1109/MIS.2017.40.
[4] LSST large telescope: https://www.lsst.org/
[5] Tsvetkov, M., 2005. Wide-field plate database: a decade of development. In Virtual Observatory: Plate Content Digitization, Archive Mining and Image Sequence Processing, iAstro workshop, Sofia, Bulgaria (pp. 10-41).
[6] Zhang, Y. and Zhao, Y., 2015. Astronomy in the big data era. Data Science Journal, 14. https://doi.org/10.5334/dsj-2015-011.
[7] Top 10 Big Data Challenges – A Serious Look at 10 Big Data V’s: https://mapr.com/blog/top-10-big-data-challenges-serious-look-10-big-data-vs/.
[8] Long, J.P. and de Souza, R.S., 2017. Statistical methods in astronomy. arXiv preprint arXiv:1707.05834.
[9] Automation offers big solution to big data in astronomy: https://phys.org/news/2015-03-automation-big-solution-astronomy.html
[10] Square Kilometre Array precursor shrinks 5TB of data to 22MB – every second! https://www.theregister.co.uk/2017/01/18/murchison_radiotelescope_opens_the_science_firehose/.
[11] Space probes: http://www.astronoo.com/en/space-probes.html.
[12] NASA-New Frontiers: https://web.archive.org/web/20150415224640/http://discoverynewfrontiers.nasa.gov/missions/missions_nh.cfml.
[13] New Atlas-ESA completes massive archive of Rosetta images and data: https://newatlas.com/esa-rosetta-philae-image-archive/55147/.
[14] Universe today: https://www.universetoday.com/135506/rise-super-telescopes-build/.
[15] Norris, R.P., 2017. Extragalactic radio continuum surveys and the transformation of radio astronomy. Nature Astronomy, 1(10), p.671. https://doi.org/10.1038/s41550-017-0233-y.
[16] The SKA Project: https://www.skatelescope.org/the-ska-project/.
[17] New Atlas-The Square Kilometre Array: How the world's biggest telescope will revolutionize astronomy: https://newatlas.com/square-kilometre-array/53498/.
[18] Mathematics for big data: https://sites.google.com/view/mathbigdata/home.
[19] Ivezić, Ž., Connolly, A.J., VanderPlas, J.T. and Gray, A., 2014. Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data. Princeton University Press. https://doi.org/10.23943/princeton/9780691151687.001.0001.
[20] Witkin, A. 1983, Proc. Int. Joint Conf. Artif. Intell., 1019.
[21] Pesenson, M., Roby, W. and McCollum, B., 2008. Multiscale astronomical image processing based on nonlinear partial differential equations. The Astrophysical Journal, 683(1), p.566. https://doi.org/10.1086/589276.
[22] Starck, J.-L., Murtagh, F., & Bijaoui, A. 1998, Image Processing and Data Analysis: The Multiscale Approach (Cambridge: Cambridge Univ. Press) https://doi.org/10.1017/CBO9780511564352.
[23] Starck, J.-L., & Murtagh, F. 2002, Astronomical Image and Data Analysis (Berlin: Springer) https://doi.org/10.1007/978-3-662-04906-8.
[24] Perona, P., & Malik, J. 1987, IEEE Trans. Pattern Analysis and Mach. Intell., 12, 629. https://doi.org/10.1109/34.56205.
[25] Pesenson, M.Z., Pesenson, I.Z. and McCollum, B., 2010. The data big bang and the expanding digital universe: High-dimensional, complex and massive data sets in an inflationary epoch. Advances in Astronomy, 2010. https://doi.org/10.1155/2010/350891.
[26] Yuzbasi, B.A.H.A.D.I.R., Arashi, M.O.H.A.M.M.A.D. and Ahmed, S.E., 2017. Big Data Analysis Using Shrinkage Strategies. arXiv preprint arXiv:1704.05074.
[27] A. A. Collister and O. Lahav. "ANNz: estimating photometric redshifts using artificial neural networks." Publications of the Astronomical Society of the Pacific 116, no.818, 2004. https://doi.org/10.1086/383254.
[28] C. J. Shallue, and A. Vanderburg. "Identifying Exoplanets with Deep Learning: A Five-planet Resonant Chain around Kepler-80 and an Eighth Planet around Kepler-90." The Astronomical Journal 155, no.2, 2018. https://doi.org/10.3847/1538-3881/aa9e09.
[29] Adrian, A. (2013). Big Data Challenges. Database Systems Journal, 4 (3), 31-40.
[30] Chaowei Yang, Qunying Huang, Zhenlong Li, Kai Liu & Fei Hu (2017) Big Data and cloud computing: innovation opportunities and challenges, International Journal of Digital Earth, 10:1, 13-53, https://doi.org/10.1080/17538947.2016.1239771.
[31] Wadhwani, K. (2017). Big Data Challenges and Solution..
[32] Garrett, M.A., 2014. Big Data analytics and cognitive computing–future opportunities for astronomical research. In IOP Conference Series: Materials Science and Engineering (Vol. 67, No. 1, p. 012017). IOP publishing https://doi.org/10.1088/1757-899X/67/1/012017.
[33] Edwards, K., Gaber, M.M.: Astronomy and Big Data: A Data Clustering Approach to Identifying Uncertain Galaxy Morphology, 1st edn. Springer, Heidelberg (2014).
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How to Cite
Khalil, M., Said, M., Osman, H., Ahmed, B., Ahmed, D., Younis, N., Maher, B., Osama, M., & Ashmawy, M. (2019). Big data in astronomy: from evolution to revolution. International Journal of Advanced Astronomy, 7(1), 11-14. https://doi.org/10.14419/ijaa.v7i1.18029Received date: 2018-08-20
Accepted date: 2019-04-18
Published date: 2019-05-05