Data scientist Michael Tso and colleagues from the UK Centre for Ecology & Hydrology have recently published a paper in Frontiers in Environmental Science
, detailing an innovative approach to assessing environmental data quality. Tso and colleagues developed a system state tagging app that aims to provide insights for users to help better understand variability in the data. They used ECN moth and butterfly time series data, as well as long-term observations from the Cumbrian Lakes Monitoring Scheme, to develop the app. As Tso states: "The long-term monitoring data from co-located measurements at ECN sites gives us perfect examples to showcase its utility".
Each observed value is associated with a state, such that it can be interpreted based on the conditions characteristic of that particular state. Following substantial development using the ECN data, demonstration versions of the App are available publicly while efforts to extend its applicability are ongoing.
Tso will present this work during a session at the annual EGU meeting, which this year will take place online. This will be part of a session convened by the European Long-Term Ecosystem Research community entitled Whole system approaches in addressing processes and long-term changes in terrestrial and aquatic ecosystems
. A live text-based chat session will take place on Friday 8th May, 10:45 - 12:30 CET.
Tso, CHM., Henrys, P., Rennie, S. and Watkins, J. (2020). State Tagging for Improved Earth and Environmental Data Quality Assurance. Frontiers in Environmental Science
, 8. DOI: 10.3389/fenvs.2020.00046