Towards an air pollution health study data management system - A case study from a smoky Swiss railway
In air pollution health studies, measurements are conducted intensively but only periodically at numerous locations in a variety of environments (indoors, outdoors, personal). Often a variety of instruments are used to measure various pollutants ranging from gases (eg, CO, NO2, O3, VOCs, PAHs) to particulate matter (eg, particles smaller than 2.5um: PM2.5, PM10, ultrafine particles: UFP), and including other environmental parameters such as temperature, relative humidity, GPS position. As a result it is always a significant challenge for researchers to effectively QA/QC, combine, and archive these data so as to reliably assess people’s exposure to poor air quality. With the CEDAR system presented here we aim to provide a solution to this problem by employing a platform using templates for easily reading custom formatted files, apply rules for filtering and quality checking measurements, and ultimately publishing them as services on the web. The system is demonstrated for the case an air quality project conducted in a Swiss railway station where smoking is allowed.
E. Papoutsoglou, A. Samourkasidis, M.-Y. Tsai, M. Davey, A. Ineichen, M. Eeftens, I. N. Athanasiadis, Towards an air pollution health study data management system - A case study from a smoky Swiss railway, Building the knowledge base for environmental action and sustainability, Adjunct Proceedings of the 29th EnviroInfo and 3rd ICT4S Conference, vol. 2, pg. 65-74, 2015, University of Copenhagen.
You might also enjoy (View all publications)
- Defining and classifying infrastructural contestation: Towards a synergy between anthropology and data science
- Investigation of common big data analytics and decision-making requirements across diverse precision agriculture and livestock farming use cases
- Blockchain applications in the agrifood domain: the first wave