Surveys, Catalogues, Databases and Archives of Astronomical Data

Surveys, Catalogues, Databases and Archives of Astronomical Data Irina Vavilova, Ludmila Pakuliak, Iurii Babyk, Andrii Elyiv, Daria Dobrycheva, and Olga Melnyk Main Astronomical Observatory of the National Academy of Sciences of Ukraine, 27 Akademik Zabolotny St., Kyiv 03143, Ukraine Abstract This Chapter traces the development of astronomical observational methods from visual, for decades tracking the behavior of individual objects, to modern space missions that produce data simultaneously for sev- eral hundred thousand objects in different spectral ranges. Thanks to this, astronomy has moved from the study of individual objects to the study of the Universe as a whole and has become the science of big data. The Chapter describes briefly visual, photographic, and CCD surveys of stars, galaxies and the intergalactic medium, spectral photographic and spectral CCD surveys, multiwavelength ground-based and space-born databases and archives, which made it possible to create a high-precision coordinate system, to discover new properties of celestial bodies and, as a result, to construct 3-D models of the visible parts of the Universe. We mention also the \conserved" data of photographic astroplates accumulated over the centuries, which have been actively digitized during last decades and provide a new knowledge from the comparative analysis of old and new observational material. Astronomy research is changing from being hypothesis-driven to being data-driven to being data-intensive. To cope with the various challenges and opportunities offered by the exponential growth of astronomical data volumes, rates, and complexity, the new disciplines of Astrostatistics and Astroinformatics have emerged. Keywords: astronomical surveys, catalogues, databases, archives; astroplates; multiwavelength astronomy 1 Introduction The night sky has always served as a source of wonder and mystery to people. However, it has only been in the past few decades that we have truly begun to observe the Universe in all its glory over the entire electromagnetic spectrum (EM) due to advances in space science and technology. The orbital telescopes and receiving devices sensitive to the infrared, ultraviolet, X-rays, and gamma- ray wavelengths above the Earth atmosphere were developed since the space exploration era. 1 Figure 1: (Top) Electromagnetic spectrum. Image credit: https: //en.wikipedia.org/wiki/ (public domain). Original author: Philip Ronan. (Bottom) The transparency of the Earth's atmosphere for electromagnetic waves. Image credit: https://www.quora.com/ (public domain). Our Universe contains objects that produce a vast range of radiation with wavelengths either too short or too long for our eyes to see from gamma-rays to radio (the top panel of Fig.1). Some celestial bodies emit mostly infrared radiation, others mostly visible light, and still others mostly ultraviolet radiation or X-ray. What determines the type of electromagnetic radiation emitted by astronomical objects? The simple answer is a temperature. The hotter solid or gas, the more rapid the motion of the molecules or atoms, and temperature is just a measure of the average energy of those particles. The nature of astronomical sources can be obtained only through detecting different kinds of radiation coming from them. But the Earth's atmosphere is quite opaque; as a result, we are able to observe only a tiny proportion of all the radiation present in space. The bottom panel of Fig.1 illustrates the transparency of Earth's atmosphere for electromagnetic wavelengths. So, the multiwavelength astronomy provides a huge amount of data of different sources over the whole EM bands. All-sky and large area surveys and their cataloged databases enriched and continue to enrich our knowledge of the Uni- verse. Astronomy has entered the Big Data era, when these data are combined into numerous archives. The modern astronomy is the data-oriented science that allows classifying the Astroinformatics as a new academic research field, which 2 covers various multi-disciplinary applications of the e-Astronomy. Among them are the data modeling, data mining, metadata standards development, data access, digital astronomical databases, image archives and visualization, ma- chine learning, statistics, and other computational methods and software for work with astronomical surveys and catalogues with their teta- to peta-scale astroinformation resource. \Many scientific disciplines are developing formal subdisciplines that are information-rich and data-based, to such an extent that these are now stand- alone research and academic programs recognized on their own merits. In astronomy, peta-scale sky surveys will soon challenge our traditional research approaches and will radically transform how we train the next generation of astronomers, whose experiences with data are now increasingly more virtual (through online databases) than physical (through trips to mountaintop obser- vatories). We describe Astroinformatics as a rigorous approach to these challenges" (cited by \Astroinformatics: A 21st Century Approach to Astronomy", (Borne et al. 2009); see, also, Cavuoti et al. 2012; I. B. Vavilova, Pakulyak, et al. 2012; Goodman 2012; Borne 2013). However, modern astrophysics requires studying an object across the whole electromagnetic spectrum, because different physical processes can be studied at different wavelengths (different substructures of celestial body radiate at different wavelengths). A greatest zest in identifying such structures and processes relates to high-energy astrophysical objects (especially gamma sources) and radio sources, wherein gamma-ray, X-ray, and radio sources need to be identified exactly with their optical counterparts. Namely the optical EM band was the first our window into the Universe due to its transparency of the Earth's atmosphere. 2 From the first star photographic catalogues to the modern digital sky surveys. Optical and near-Infrared astronomy 2.1 First important visual surveys and catalogues Since the last half of the XIX century, the astronomy has become a big data science. The first projects which could be referred to as \big data" comprised of dozens to hundreds of thousands of celestial objects. Each object was obtained and treated manually and, mostly, was considered independently of others. The main challenges faced by astronomers of that time: • protracted observations; • a large amount of protracted manual work; • different approaches of different groups of observers to the processing of observational data; • as a consequence, the heterogeneity of resulting data and the need to bring them to one reference system; • the problem of choosing the reference system in the absence of standards and the need for their prior creation; We can only astonish and admire the thoroughness of the work of astronomers, 3 which allowed them to obtain the accurate data reliable for decades and centuries. The first "big datasets" of astronomical objects were obtained as result of visual observations. The beginning was laid by F. Argelander with his Bonner Durchmusterung (BD, 1859{1862) survey of stars down to about visual magnitude 9m-10m. The BD firstly contained 324 188 stars from the north celestial pole to 2◦ south of the celestial equator. The catalog was periodically updated, supplemented, and reissued again in 1989 being comprised of 325 037 stars. The star list included all the stars visible in the 3-inch Bonn refractor. During the observation an observer kept the telescope fixed and registered every star ap- peared in the field of view in each 1o◦ zone on declination. The star charts, made on its basis and published after the catalog in 1863, were the most com- plete and accurate as to compare with others created at that time (Fig.2). In 1886 the BD was enhanced with SBD - Sudliche Bonner Durchmusterung { down to -23◦. The SBD added about of 138 thousand stars observed with a 6-inch Bonn refractor using the same technique as the BD. Figure 2: BD star atlas. Picture from https://www.datuopinion.com/bonner- durchmusterung (public domain) The BD does not cover the entire sky, but only the part that is visible from Germany. Therefore, it was supplemented with two surveys made at observa- tories located in the Southern hemisphere. The first one was the Cordoba Durchmusterung (CD, 1892{1932) covered the southern stars in declination zones from -22◦ to -89◦. The CD list of objects contains around 614 thousand records for stars brighter than visual magnitude 10m. The survey was made using visual observations just like the BD has done. The period of CD star list observations is ten times longer than that of the BD. The conditions of observations changed so much that it led to the heterogeneity of CD data in comparison with its northern counterpart. The history of cataloging the extragalactic objects began with the first catalog by Charles Messier, a French astronomer of the XVIII century. However, 4 Messier itself did not care about the nebulae. The comets were his main scientific interest, and precisely in order not to confuse the comet with the nebulae, he made his famous catalog in 1784, 2nd edition, Messier Catalogue, M, which contained 102 dissimilar sky objects observed in the north hemisphere (Messier 1781). William Herschel was the first to make a systematic visual survey of the weak nebulae and to identify patterns in their distribution. He discovered more than 2.5 thousand nebulae and stellar clusters, and about 80 % of these objects were later, in the XX century, identified as other galaxies. William Her- schel published three catalogues in 1786-1802. In the 19th century, the work of William Herschel was continued by his only son John Herschel, who supplemented these discoveries by new 1754 celestial objects and published its as the General Catalogue of Nebulae and Clusters, GC (Herschel 1864). This catalogue was later edited by John Dreyer, who included discoveries of other 19th century astronomers in it and published in 1888 as the New General Catalogue, NGC (J. L. E. Dreyer 1888) as well as later he supplemented it by the Index Catalogues (J.

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