Big Data accelerated Science: Trends and Challenges

Massive amount of data that are routinely, sometimes involuntarily, generated by computational chemists, physicists and material scientists are inexhaustible sources of scientific knowledge. All that is required is to collate various forms of such data, ranging from raw input/output files to tabulations based on post computation analysis, and provide access to the scientific community for data-mining. Easier said than done! The MolDis repository developed at the TIFR Centre for Interdisciplinary Sciences aims to provide an analytics platform for Big Data of computed molecular properties. Presently massively large datasets are being generated for a multitude of domains of application. I shall demonstrate the usage of this facility and discuss progresses in this direction world wide.