Center of Excellence in Big Data Engineering

This project aims to establish a collaboration between the International Institute of Information Technology (IIIT-B), with City University London, as the UK partner and Siemens Research, India, as the industry partner, to set up a centre of excellence in Big Data Engineering. With emerging trends like Web Science and the Internet of Things, expertise in Big Data is going to be in high demand in the future.

As part of our initiatives to create a talent pool of research and engineering expertise, IIIT-B has collaborated with several partners in this area on specific projects. This project aims to consolidate our disparate activities in this area and create a Centre of Excellence in Big Data Engineering. The term “Big Data” is defined here to mean any kind of data management problem for which, conventional RDBMS based solutions are inadequate. The “Big” refers to not just the volume of data, but also challenges concerning variety, veracity and velocity of the data.

This centre is hosted by the Web Science Lab at IIIT-B.


  • Prof. Srinath Srinivasa
  • Prof. Vinu E. Venugopal
  • Apurva Kulkarni, Postdoc
  • Praseeda, Research Scholar
  • Raksha, Research Scholar
  • Anish, MTech. Thesis Student


  • Prof Muttukrishnan Rajarajan, City University, Northampton Square, London,
    United Kingdom
  • Dr. Amarnath Bose, Siemens Technology and Service, Bangalore


The centre focuses on integrating open datasets– specially Open Government Data (OGD) and building AI models that can help explain causal dependencies between several variables and indicators pertaining to Sustainable Development Goals (SDGs).

This project involves the creation of Big Data processing pipelines to process different kinds of datasets and create case files for one or more SDG indicators, showing factors that are highly correlated with them. Based on this case file, we build AI models that can potentially identify causal dependencies between these factors and the indicator.

Based on these models, we now perform– predictive or “what if” analysis, and prescriptive analysis. The former is an exploratory exercise that predicts the expected impact of a policy change on SDG indicators in different geographical regions. The latter is another form of exploratory exercise that prescribes values of affecting factors for bringing a given indicator towards its intended target.

We have also developed models for assessing the stability of policy interventions, asking whether a given outcome due to an intervention will sustain over time, or will it revert back to its earlier state, due to disparity in outcomes.

This project also has matching funding from the Planning Dept of the Govt of Karnataka, which supports project staff who develop interactive dashboards based on the models generated, for use by policy makers. All research activities carried out under this project are supported by the BDE centre.


Associated Projects

  • Open City: The project looks at managing large-scale access control of IOT devices data in a secure fashion.
  • Cogno Web Observatory



  • Aniket Mitra and Vinu Venugopal. Enhancing Region-Based Geometric Embedding for Gene-Disease Associations. 7th International Conference on Data Science and Management of Data (CODS-COMAD 2024), Bangalore, India, Jan 2024
  • Apurva Kulkarni, Pooja Bassin, Niharika Sri Parasa, Srinath Srinivasa, Vinu EV, Chandrashekar Ramanathan. Ontology Augmented Data Lake System for Policy Support. 10th International Conference on Big Data Analytics in Astronomy, Science and Engineering (BASE) December 05 – 07, 2022
  • Srinivasa S., Pavagada Subbanarasimha R. (2018) Design of the Cogno Web Observatory for Characterizing Online Social Cognition. In: Anirban Mondal, Himanshu Gupta, Jaideep Srivastava, P.Krishna Reddy, D.V.L.N. Somayajulu. (eds) Big Data Analytics. BDA 2018. Lecture Notes in Computer Science. Springer, Cham.
  • Raksha Pavagada Subbanarasimha, Lokesh Todwal, Mamillapalli Rachana, Aditya Naidu, and Srinath Srinivasa. 2018. Mithya: A Framework For Identifying Opinion Drivers On Social Media. Demo at ACM IKDD Conference on Data Science and International Conference on Management of Data, Goa, India, Jan 2018 (CODS-COMAD 2018).
  • Anish Bhanushali, Raksha Pavagada Subbanarasimha, and Srinath Srinivasa. 2017. Identifying Opinion Drivers on Social Media. In On the Move to Meaningful Internet Systems. OTM 2017 Conferences: Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, Rhodes, Greece, October 23-27, 2017, Proceedings, Part II. Springer International Publishing, Cham, 242–253.