Abstract
Epidemiological studies analyze and monitor the health state of a population. They typically use different methods and techniques to capture and to integrate data of interest before they can be analyzed. As new technologies and, thus, devices are available for data capturing, such as wearables, new requirements arise for current data integration approaches. In this paper, we review current techniques and approaches as well as new trends in data capturing and the resulting requirement for its integration.
T. Kirsten and J. Bumberger—Contributed equally to this work.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wild, P.W.: Complementing the genome with an “exposome”: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol. Biomark. Prev. 14, 1847 (2005)
Quante, M., Hesse, M., Döhnert, M., et al.: The life child study: a life course approach to disease and health. BMC Pub. Health 12(1), 1021 (2012)
Loeffler, M., Engel, C., Ahnert, P., et al.: The LIFE-Adult-Study: objectives and design of a population-based cohort study with 10,000 deeply phenotyped adults in Germany. BMC Pub. Health 15 (2015)
Richardson, D.B., Volkow, N.D., Kwan, M.P., et al.: Spatial turn in health research. Science 339(6126), 1390–1392 (2013)
Kostkova, P., Brewer, H., de Lusignan, S., et al.: Who owns the data? Open data for healthcare. Fronties Pub. Health 4(7), February 2016
Danielsen, F., et al.: Local participation in natural resource monitoring: a characterization of approaches. Conserv. Biol. 23(1), 31 (2009)
Chan, M., Estève, D., Fourniols, J.Y., Escriba, C., Campo, E.: Smart wearable systems: current status and future challenges. Artif. Intell. Med. 56(3), 137–156 (2012)
Soh, P.J., Vandenbosh, G.A.E., Mercuri, M., Schreurs, D.: Wearable wireless health monitoring: current developments, challenges, and future trends. IEEE Microwave Mag. 16(4), 55 (2015)
Ma, H., Zhao, D., Yuan, P.: Opportunities in mobile crowd sensing. IEEE Commun. Mag. 52(8), 29–35 (2014)
Pitts, R.: Geospatial data integration challenges and considerations, 12 November 2013. http://sensorsandsystems.com/geospatial-data-integration-challenges-and-considerations/
Ganti, R.K., Ye, F., Lei, H.: Mobile crowdsensing: current state and future challenges. IEEE Commun. Mag. 49(11), 32–39 (2011)
Sagl, G., Resch, B., Hawelka, B., Beinat, E.: From social sensor data to collective human behaviour patterns: analysing and visualising spatio-temporal dynamics in urban environments. In: Proceedings of the GI-Forum, pp. 54–63 (2012)
Acknowledgment
This publication is supported by LIFE (Leipzig Research Center for Civilization Diseases, University of Leipzig). LIFE is funded by means of the European Union, by the European Regional Development Fund (ERFD) and by means of the Free State of Saxony within the framework of the excellence initiative.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Kirsten, T. et al. (2017). Research in Progress on Integrating Health and Environmental Data in Epidemiological Studies. In: Abramowicz, W., Alt, R., Franczyk, B. (eds) Business Information Systems Workshops. BIS 2016. Lecture Notes in Business Information Processing, vol 263. Springer, Cham. https://doi.org/10.1007/978-3-319-52464-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-319-52464-1_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-52463-4
Online ISBN: 978-3-319-52464-1
eBook Packages: Business and ManagementBusiness and Management (R0)