From maps to action
We envision a future where geospatial data serves as one of the key driving forces of positive change in our communities.
The Urban and Movement Analytics (UMA) Lab is a research group based at the School of Earth and Environment | Te Kura Aronukurangi at the University of Canterbury | Te Whare Wānanga o Waitaha, Christchurch | Ōtautahi, New Zealand | Aotearoa.
Fostering Innovation and Ethical Data Solutions
The UMA Lab aspires to become a catalyst for innovation, fostering collaboration among data scientists, researchers, policymakers, and communities to create solutions that are not only data-driven but also ethically sound and inclusive.
-
Innovation Catalyst
The UMA Lab serves as a hub for fostering innovation within a collaborative ecosystem.
-
Cross-Disciplinary Collaboration
We bring together diverse experts—data scientists, researchers, policymakers, and communities—to work collectively on impactful solutions.
-
Data-Driven with Ethics
They believe in harnessing the power of data while upholding ethical principles and ensuring solutions benefit all.
-
Positive Societal Impact
Inclusivity is a core value, ensuring solutions address the needs of diverse communities. We aim to contribute to positive societal change through our research and collaborations
"Data is considered the new gold because it has become a critical raw material for producing digital products and services. The vast amount of data available has the potential to generate valuable insights and fuel innovation. In order to realize the full potential of data, it's important to store, organize and structure it in a way that makes it easy to access."
Sandro Shubladze
Founder & CEO at Datamam
In Forbes: How To Make Use Of The New Gold: Data
Geospatial Analytics for a Better Aotearoa
Inspired by the principles of DataKind and Data4Good, the our mission to develop spatio-temporal methods to unlock the power of underutilised geospatial data to support policymakers developing better cities and better living in Aotearoa.
Problem Statement
A clear and concise description of the problem that the data science initiative aims to solve.
Social Actors
Identification of the key stakeholders who will be impacted by the initiative, including communities, individuals, and organizations.
Subject Matter Expertise
Identification of the experts in the field who will be consulted during the initiative.
Data Scientists
Identification of the skills and expertise needed by the data scientists who will work on the initiative.
Datasets
Identification and description of the data sets that will be used in the initiative.