Astroinformatics: Getting New Knowledge from the Astronomical Data Avalanche

Abstract

The research in almost all natural sciences is facing the data avalanche represented by an exponential growth of information produced by big digital detectors and large-scale multi-dimensional computer simulations stored in the worldwide network of distributed archives. As the data volumes have been growing faster than computer technology can cope with, a qualitatively new research methodology called Data Intensive Science or X-informatics is required, based on an advanced statistics and data mining methods, as well as on a new approach to sharing huge databases in a seamless way by global research communities. This approach, sometimes presented as a Fourth Paradigm of contemporary science, promises new scientific discoveries as a result of understanding hidden dependencies and finding rare outliers in common statistical patterns extracted by machine learning methods from Peta-scale data archives. The implementation of X-informatics in astronomy, Astroinformatics, is a new emerging discipline, integrating computer science, advanced statistics, and astrophysics to yield new discoveries and better understanding of nature of astronomical objects. It has been fully benefitting from the long-term skill of astronomy of building well documented astronomical catalogues and automatically processed telescope and satellite data archives. The astronomical Virtual Observatory project plays a key role in this effort, being the global infrastructure of federated astronomical archives, web-based services, and powerful client tools supported by supercomputer grids and clusters. It is driven by strict standards describing all astronomical resources worldwide, enabling the standardized discovery and access to these collections as well as advanced visualization and analysis of large data sets. In our talk, we give a overview of the motivations, early history, and technological principles of Virtual Observatory, as well as a more philosophical view of data mining, Citizen Science, and new promises of Astroinformatics in the age of data-flooded astronomy. © Springer International Publishing Switzerland 2013.