Published: February 13, 2020

Volume, Velocity, Variety, Variability, Value, and Veracity. These are the ‘six Vs’ of achieving high-quality big data for responsible data science, as outlined by Dr Divesh Srivastava, Head of Database Research at AT&T Labs, the development division of the world’s largest telecommunications company AT&T.

Dr Srivastava this week presented a Distinguished Lecture in Data Science to The University of Queensland School of Information Technology & Electrical Engineering (ITEE). His lecture, hosted by Associate Professor Helen Huang of the ITEE Data Science Group, addressed a number of case studies and challenges in dealing with big data.

‘Big data means different things to different people’, ‘one size does not fit all’, and ‘let the data speak for itself’ were all key messages from Dr Srivastava. He also highlighted the need for big data to ‘complement’ what humans do. He said low-quality big data was an impediment to responsible data science, and achieving high-quality big data rested on meeting the challenges of the ‘Six Vs’. “Much interesting work has been done in this area, and a lot more needs to be done,” Dr Srivastava said.

Dr Divesh Srivastava

Other important messages delivered by Dr Srivastava at the lecture included:

• Learning approximate, conditional models (semantics) from big data
• Identifying data glitches as violations of the learned models, and
• Repairing data glitches and models in a timely manner.

As well as his role at AT&T Labs, Dr Srivastava is a Fellow of the Association for Computing Machinery (ACM), on the ACM Publications Board and an associate editor of the ACM Transactions on Data Science, the Vice President of the Very Large Data Base Endowment, and on the Board of Directors of the Computing Research Association. He received his PhD from the University of Wisconsin, Madison, and his Bachelor of Technology from the Indian Institute of Technology, Bombay.

Data science and analysis will be a key research focus of the new Life Course Centre. Associate Professor Huang will be joining the Centre as a Chief Investigator, as will Dr Srivastava as an Associate Investigator.

Their skills will boost the Centre’s capacity to link and analyse increasingly large and variable data sets from multiple sources in order to map the complex interactions of social disadvantage.