Individually, our data sources, including registry data, personalised data from sensors, social media, biomarker data from our cohorts and environmental datasets, are rich data sources. However the exciting possibilities that arise in BERTHA occur when we can integrate the disparate data-sources, and use cutting edge spatial and temporal data analytics to mine for data associations.
Data will come from all the other Work Packages in BERTHA.
Interactive data mining, data analytics, machine learning, exploratory visualising and spatial data analysis will be combined and applied to our myriad data sources and health outcomes. A significant challenge will be developing analytics which preserve data integrity and confidentiality, across a distributed network.
The outcomes will be an integrated computational framework and a toolset to test interaction hypotheses between environment and health. The toolsets will be applied to test specific associations.
Potential topics for new PhD or Post Doc projects
Developing Big Data spatial analytics for health and environment
There is no ongoing projects yet
Work Package Leader: Professor Clive Sabel
