From WaterML to TimeseriesML: Evolution and implications for cross-domain data interoperability

Tuesday, 15 December 2015
Poster Hall (Moscone South)
David K Arctur, University of Texas at Austin, Austin, TX, United States, Peter Taylor, CSIRO Hobart, Hobart, Australia, Dominic Lowe, Bureau of Meteorology, Melbourne, Australia, James Tomkins, UK Meteorological Office, Exeter, United Kingdom, William L Teng, ADNET Systems Inc. Greenbelt, Greenbelt, MD, United States and Daniel P Ames, Brigham Young University, Provo, UT, United States
WaterML 2.0 part 1 was adopted by the Open Geospatial Consortium (OGC) in 2012 as an international standard profile of the Observations and Measurements conceptual model, for exchange of water observations time series data. It is implemented by national data producers such as the US Geological Survey for surface water time series, the NOAA/National Weather Service for forecast time series, the French Geological Survey for groundwater level monitoring, and the Australian Bureau of Meteorology for surface water observations. But WaterML 2.0 is not “just for water”. The World Meteorological Organization (WMO) has recognized its potential role as a common time series description that could work for multiple application domains such as meteorology, climate, oceanography, and others. Accordingly, the WMO requested the OGC to migrate the non-hydrology parts of WaterML 2.0 to a new standard to be called TimeseriesML. This would then be considered by WMO for adoption as an operational standard globally. What does this mean for the geosciences? How far can this time series description be applied? What about time series of satellite retrievals? What will happen to WaterML 2.0 (and applications that work with it) when TimeseriesML is finished? These are among the questions we address in this presentation.