Day 3 | Technical Session 3 | January 29, 2021 : 10:30 am to 01:00 pm

Theme: Cyber Infrastructure and Big Data Analytics

eScience is the convergence of different sets of trends and technologies that have radically transformed the scientific method and the conduct of science. As science moves towards a data-intensive and collaborative approach, digital technologies have strengthened the power and reach of data and raised new challenges for the research community. The bedrock of eScience is the infrastructure and processes of data management such as mining, extraction, curation and analysis of humongous quantities of data from distributed systems, along with the ability to share the ideas and results of the analysis to help discover patterns and trends and advancing science.

Cyberinfrastructure⎯a term first used by the US National Science Foundation (NSF), consists of computing systems, data storage systems, advanced instruments and data repositories, tools and techniques for visualization environments, and people, all linked by high speed networks to make possible scholarly innovation and discoveries not otherwise possible. The NSF made cyberinfrastructure a central theme in its plans for developing and delivering tools to enhance scientific discovery and set out an aggressive set of plans for development of cyberinfrastructure as a national discovery environment through the NSF Vision for a Cyberinfrastructure Framework for 21st Century Science and Engineering (CIF21) funding program. The Department of Science & Technology, Government of India launched a new programme called “Interdisciplinary Cyber Physical Systems (ICPS)” to foster and promote R&D in this emerging field of research. CPSs are defined as systems emerging from the integration of embedded computing devices, smart objects, people and physical environments, tied by a communication infrastructure. Funding for research projects in areas of data sciences and Internet of Things were initiated under this Programme.

Studying any phenomenon⎯natural or societal, as a system requires a combination of recorded observational data and simulation data produced by numerical models. Our capability to explore phenomena has been enhanced with the emergence of information technologies. While the technological advancements accelerate collecting, simulating and sharing data, they also produce Big Data. Effectively analyzing these data are essential but the tasks are challenging for scientists in that data analytics requires complex procedures and multiple tools.

This session brings together experts to examine the prospects of building the required cyberinfrastructure and debate on how to effectively process and analyze big data of science which are becoming critical to challenges such as climate change, natural disasters, diseases and other emergencies.

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