GDSL Brown Bag with Ana Basiri, Hyesop Shin and Terry Lines

Описание: Abstract:
This talk will discuss Open Geospatial Data Science of The Turing Way, which is an open-source community-driven guide to reproducible, ethical, inclusive, and collaborative data science led by the Alan Turing Institute. We will take one of the Geospatial Data Science projects, one initiative, and one case study to explore how and where Geospatial Data Scientists can join the community to contribute to reproducible, open, ethical research. We will start with an introduction to The Turing Way and Responsible Data Science Special Interest group, then will overview briefly the Indicative Data Science project that considers biases and missingness of data as useful data. We will see how missing geospatial data, e.g. blocked GPS signals, can be used to create 3D maps and how to develop an inclusive crowdsourcing platform for Volunteering Geographic Information (VGI) data collection.
Bios:
Ana Basiri is a Professor in Geospatial Data Science and a UK Research and Innovation Future Leaders Fellow at the University of Glasgow. Ana works on developing (theoretical and applied) solutions that consider gaps, unavailability, and biases in data as a useful source of data to make inferences about the underlying reasons that caused missingness or biases. For this, Ana collaborates with world-leading academic and industrial partners, including Ordnance Survey GB, Uber, Alan Turing Institute. Ana is the Editor in Chief of the Journal of Navigation and has received several awards and prizes, including Women Role Model in Science by Alexander Humboldt and European Commission Marie Curie Alumni.
Hyesop Shin is a PostDoc Research Fellow at the University of Glasgow. Hyesop is a quantitative geographer interested in environmental hazards, urban air quality, mobility patterns, and citizen science. Hyesop completed his PhD at the University of Cambridge where he looked at how individuals' exposure to air pollution can differ by commuting routes and socioeconomic backgrounds using an agent-based simulation. At Glasgow, his current project unravels the benefits of using crowdsourcing to help improve our understanding of locational services for under-represented groups.
Terry Lines is a researcher at the University of Glasgow’s School of Geographical & Earth Sciences. His research interests are the use of low-quality spatial data for inference about urban environments. Many new forms of data are crowdsourced or automatically collected without controls on quality. Theoretical and applied methods are required to investigate the environmental processes leading to data creation and measure uncertainty.