Who Are the "Crowd"? Learning from Large but Patchy Samples

Ana Basiri (UCL)

Thursday 21st May, 2020 14:00-15:00 Via Zoom



This talk will look at the challenges of crowdsourced/self-reporting data, such as missingness and biases in ‘new forms of data’ and consider them as a useful source of data itself. A few applications and examples of these will be discussed, including extracting the 3D map of cities using the patterns of blockage, reflection, and attenuation of the GPS signals (or other similar signals), that are contributed by the volunteers/crowd. In the era of big data, open data, social media and crowdsourced data when “we are drowning in data”, gaps and unavailability, representativeness and bias issues associated with them may indicate some hidden problems or reasons allowing us to understand the data, society and cities better.

Ana Basiri is a UK Research and Innovation Future Leaders Fellow (currently at UCL, but will be Professor of Geospatial Data Science at the University of Glasgow from 1st June). Ana works on developing (theoretical and applied) solutions that consider gaps, unavailability, and biases in data as a useful source of data to make inference about the underlying reasons that caused missingness or biases. For this, she leads a team of an interdisciplinary team and collaborates with world-leading academic and industrial partners, including Ordnance Survey GB, Uber, Alan Turing Institute, and engage with the public, policymakers and government. Ana is the Editor in Chief of Journal of Navigation and Associate/Guest Editor of several high impact journals including IET Smart city and International Journal Geographical Information Science. She has received several awards and prizes, including Women Role Model in Science by Alexander Humboldt and European Commission Marie Curie Alumni.

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