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Lookup NU author(s): Professor Paul WatsonORCiD, Dr Hugo Hiden
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by IEEE, 2022.
For re-use rights please refer to the publisher's terms and conditions.
This paper describes a novel study management platform that is being used to collect, process and analyse data gathered from a large-scale pan-European digital healthcare study. The platform consists of two main components. Firstly a secure, scalable, cloud-based platform to ingest and process data uploaded from body-worn sensors, as well as from clinical evaluation forms. Features extracted from this data are then loaded into a Data Warehouse with a novel schema designed specifically for study data. This allows scientists to explore, analyse and visualise this data in a variety of different ways. A key aspect of the warehouse design is that it also stores metadata describing the types and format of the data. This enables automatic report generation, exploratory data analysis and error checking. The overall result is a flexible, general purpose system that is open-source and uses the cloud for scalability. This paper describes the design of the integrated study data platform and its use in the large Mobilise-D study that has collected and analysed both sensor and clinical data from over 3,000 participants.
Author(s): Watson P, Hiden H
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 2022 IEEE 18th International Conference on e-Science (e-Science)
Year of Conference: 2022
Acceptance date: 02/04/2022
Date deposited: 13/08/2022
Publisher: IEEE
ePrints DOI: 10.57711/e7kg-z752
