Methodologies and data mining techniques for the analysis of big data based on longitudinal population and epidemiological registers (LONGPOP)
Goal: European societies face rapid social changes, challenges and benefits, which can be studied with traditional tools of analysis, but with serious limitations. Owing to population ageing across Europe, countries are now experiencing the impact of these rapid changes on the sustainability of their welfare systems. Over the past decade research teams across Europe have been involved in the development and construction of longitudinal population registers and large research databases, while opening up avenues for new linkages between different data sources (ie administrative and health data) making possible to gain an understanding of these fast societal transformations.
The project in Geneva will focus on healthy ageing from a life course perspective. Different aspects of health that are of importance when studying ageing will be explored, such as physical, mental, and cognitive health and well-being. Several large-scale datasets will be used that cover longitudinal changes in those factors across the life course into very old age. Special attention will be given to social inequalities.
Working with different types of datasets requires advanced skills in both data management and statistical techniques. LONGPOP aims to create network to utilize these different research teams to share experiences, construct joint research, create a training track for specialist in the field and increase the number of users of these large – possibly underused – databases, making more scientists and stakeholders aware of the richness in the databases.
Principal investigator: Michel Oris
Project team: Matthias Kliegel, Rainer Gabriel, Rose van der Linden
- Center for Humanities and Social Sciences – Madrid, Spain
- International Institute of Social History – Amsterdam, the Netherlands
- Lund University – Lund, Sweden
- Radboud University – Nijmegen, the Netherlands
- Universita degli Studi di Sassari – Sassari, Italy
- The University of Edinburgh – Edinburgh, United Kingdom
- KU Leuven – Leuven, Belgium
- Telnet. Redes inteligentes S.L. – La Muela, Spain
- ESRI España – Madrid, Spain
- Instituto de Estadistica y Cartografia de Andalucia – Sevilla, Spain
Project duration: 01.02.2016 – 31.01.2020.
Project funding: European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska Curie grant agreement No 676060