Hi everyone,

Third in a row! We’re continuing with another great session in Mid May in the Lister Learning and Teaching Centre, room LLTC_3.3 (https://www.ed.ac.uk/timetabling-examinations/timetabling/room-bookings/bookable-rooms3/room/0335_03_3.3).

Register here:

• Dr Michael Sinclair is a Research Associate in Digital Footprints Data at the Urban Big Data Centre and Principle Investigator of the ESRC SDAI grant ‘Developing and exploring methods to understand human-nature interactions in urban areas using new forms of big data’. Michael completed his PhD in Natural Resources and Environmental Management where he explored human-nature interactions via crowdsourced data. He has an MA in Geography from the University of Edinburgh, UK, and an MBA with a focus on sustainability from the University of Haifa, Israel. His research interests revolve around using Digital Footprints Data to address environmental issues with a specific focus on human-nature interactions

• Dr Mike Spencer is head of research at the Smart Data Foundry, a startup owned by the University of Edinburgh. He helps researchers and governments access financial data about businesses and citizens for the public good.

Exploring the use of Glasgow’s greenspaces using mobile phone app data

Dr Michael Sinclair

Mobile phone app data offers vast potential as an alternative to more traditional forms of data. However, there are uncertainties in how well these data represent the population which may limit their use. Through the case study of Glasgow’s greenspaces, this research uses R to explore the representativeness of mobile phone app data and uses said data to explore greenspace use, including estimating visitation numbers and patterns of use for different groups.

Scale your workflow beyond memory limits with Arrow

Dr Mike Spencer

We’ve all struggled with available hardware limits, whether that’s on a laptop or large server. There’s always a job too big for the available memory (RAM). One way of solving this is using the Arrow package, which is much easier than you might imagine! In this talk Mike will walkthrough using Arrow with dplyr and how to make the most of this workflow.

May 2023: mobile phone data and big(ger) data workflows</p></blockquote>