CIM News
“Uncovering social and regional inequalities using spatial data and interdisciplinary methods” – a workshop led by Zofia Bednarowska-Michaiel
Dr Zofia Bednarowska-Michaiel ran a CIM Research Workshop on 19th of May 2021. It aimed to bridge participants on campus and those joining online together. The workshop focused on an interdisciplinary approach to researching inequalities around the role of regional science and spatial data in stimulating policy discussions around inequalities.
Big Data and Society - Situational Analytics in Computational settings
For a situational analytics: An interpretative methodology for the study of situations in computational settings.
authoring a new research article:
https://buff.ly/2JHr4EA #STS #platformstudies #AutonomousVehicles #ComputationalSocialScience
Emma Uprichard - CIM @ the Alan Turing Institute
Congratulations to Emma Uprichard (Reader in CIM) who will be a Turing Fellow for the next 2 years at the Alan Turing Institute for Data Science.
Big Data Video - IAA Award
Big data are said to be transforming everyday life. At CIM, our researchers are currently leading and/or involved in several major data-driven projects.
CIM - UNDP Public Lecture
Public Lecture – all welcome!
Come and join us to learn more about this CIM-UNDP project on: Visualising Big Data for Global Development Policy: Introducing the Joint Warwick/UNDP Initiative on Climate Change Adaptation in Cabo Verde’, Thursday, October 29, 2015 from 5:15 PM to 7:00 PM (GMT) in LIB2 (Library Building).
Please note this event is being hosted and supported by CIM, Warwick Q-Step, the Warwick Faculty of Social Science, and Professor Celia Lury's ESRC Fellowship, 'Order and Continuity: Methods for Change in a Topological Society'.
Please register here to attend: http://goo.gl/x9uZyU.
New MSc and Diploma in Big Data and Digital Futures
CIM is delighted to announce its new MSc (and Diploma) in Big Data and Digital Futures for 2015-16.
DTC Advanced Training Workshop: Socialising Big Data
This one-day course is designed for students who want to learn more about the risks, challenges and potentials of working with Big Data.