Big Data Science in Astronomy Especially with respect to the Search for Exoplanets aka Earth Analogue 2.0

Abstract

Big data Science in Astronomy for the Hunt for Earth Analogue as the current research embodies the rationale for such scientific data driven projects as far as the dystopian future of our planet earth is concerned. The research provides the conceptual framework for the various terminologies or jargons associated with exoplanet hunting or searching for the Earth’s analogue along with the challenges embedded in the procedure to carry out the project. The research emphasis mainly on exoplanet hunting using transit method of planet hunting deploys the data science and its underlined algorithms like the KNN algorithm to illustrate the process hunting or searching an analogous earth 2.0. The research work also successfully demonstrates based on the data modeling techniques the ways and means to differentiate between an actual data set against outliers or anomalous data. The research deploys research methods namely observations, experiments, document screening, empirical data and scientific illustration in forms of graphs to illustrate the underlying research concepts pertaining to Big Data in astronomical science as an intensive data driven field of science. The results and findings are synonymous to the hypothesis of the research that Astronomical Science has undergone a paradigm shift from a theory based field to more of an intensively data driven field of science in the current day and age of Big Data Era.