A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and its Users

Simpson, M., Woodman, S., Hiden, H., Stein, S. , Dowsland, S., Turner, M., Hanson, V. L. and Watson, P. (2017) A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and its Users. In: 2017 IEEE 13th International Conference on eScience, Aukland, New Zealand, 24-27 Oct 2017, pp. 228-237. ISBN 9781538626863 (doi: 10.1109/eScience.2017.36)

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Abstract

There are many scenarios in which it is necessary to collect data from multiple sources in order to evaluate a system, including the collection of both quantitative data - from sensors and smart devices - and qualitative data - such as observations and interview results. However, there are currently very few systems that enable both of these data types to be combined in such a way that they can be analysed side-by-side. This paper describes an end-to-end system for the collection, analysis, storage and visualisation of qualitative and quantitative data, developed using the e-Science Central cloud analytics platform. We describe the experience of developing the system, based on a case study that involved collecting data about the built environment and its users. In this case study, data is collected from older adults living in residential care. Sensors were placed throughout the care home and smart devices were issued to the residents. This sensor data is uploaded to the analytics platform and the processed results are stored in a data warehouse, where it is integrated with qualitative data collected by healthcare and architecture researchers. Visualisations are also presented which were intended to allow the data to be explored and for potential correlations between the quantitative and qualitative data to be investigated.

Item Type:Conference Proceedings
Additional Information:This work was supported by the RCUK Lifelong Health and Well-being Programme grant number EP/K037293/1 - BESiDE: The Built Environment for Social Inclusion in the Digital Economy.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Stein, Dr Sebastian
Authors: Simpson, M., Woodman, S., Hiden, H., Stein, S., Dowsland, S., Turner, M., Hanson, V. L., and Watson, P.
College/School:College of Science and Engineering > School of Computing Science
ISBN:9781538626863
Published Online:16 November 2017
Copyright Holders:Copyright © 2017 IEEE
First Published:First published in 2017 IEEE 13th International Conference on eScience: 228-237
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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