In BERTHA, we address the challenges facing Big Data in biomedicine in never-before paralleled detail, focusing on individual level whole life course environmental and social exposures and health. We collect and create linkage between multiple data sources as the unique historical population registers and medical records in Denmark, biomarker assessments, environmental exposure assessments and modelling, personalised sensors and social media.
To us, Big Data is not just about using large data sets, but critically, to create linkage between multiple sources of information to reveal patterns, trends, and associations. In other words, to reveal value much greater than the sum of the individual parts. In BERTHA, we prefer to call it Rich Data rather than Big Data.
In BERTHA, we address the challenges facing Big Data in biomedicine in never-before paralleled detail, focusing on individual level whole life course environmental and social exposures and health. We collect and create linkage between multiple data sources as the unique historical population registers and medical records in Denmark, biomarker assessments, environmental exposure assessments and modelling, personalised sensors and social media.
To us, Big Data is not just about using large data sets, but critically, to create linkage between multiple sources of information to reveal patterns, trends, and associations. In other words, to reveal value much greater than the sum of the individual parts. In BERTHA, we prefer to call it Rich Data rather than Big Data.
A new synthesis in health geography, Genetic Geographical Information Science (GISc), seeks to document, quantify and model the relationships between place, and the genome, exposome and behavome (health-related behaviors) that are the determinants of illness and wellness. This paradigm requires an explicit understanding of how these determinants are related to space-time patterns of health outcomes in human populations. Because the exposome and behavome are defined at the level of the individual, techniques for estimating disease latency, - the time between exposure and the onset of disease, are essential. This requires technical innovation, such as spatially enabled sensors, spatial methodological innovations and theoretical developments in the whole life exposure exposome and behavome field. The BERTHA researchers and collaborators address these needs.
We handle all personal identifiable information with confidentiality and according to the European General Data Protection Regulation (GDPR). The data are analysed only through Statistics Denmark’s research platform, where download of personal identifiable information is strictly prohibited and monitored.
