Abstract
Timely yet data-driven policies and decisions require ingestion and assimilation of real-time data, while acknowledging and measuring their inherent incompleteness, uncertainty, biases, and under/over-representation. Living in "digital era" has given us an unprecedented opportunity to zoom into individuals but still see the bigger picture of cities and society almost in real time for free. However, "new forms of data”, such as social media data, and smart devices data are incomplete, sparse, biased, and under-represented. This talk will look at the quality-quantity tradeoff of big geospatial data and the challenges, theoretical and applied solutions to effectively combine and make the most of both the traditional and new forms of data, and use missing data as useful data to understand why and how missingness happens in the first place.

 

Bio: Ana Basiri is a Professor in Geospatial Data Science, a UK Research and Innovation Future Leaders Fellow, the Director of the Centre for Data Science and AI, and Royal Academy of Engineering's EngineeringX Champion at the University of Glasgow. Ana leads a team working on developing (theoretical and applied) solutions that consider unavailability and biases in data as useful sources of data to make inferences about the underlying reasons that caused missingness or biases. To find out more about Ana and her work please visit: https://www.gla.ac.uk/schools/ges/staff/anabasiri/