SensorDat: a testbed for improving real-time data quality and sensor provenance Mike Daniels Matthew Bartos, mdbartos@umich.edu Connor Scully-Allison Scotty Strachan aaron botnick charlie martin 10.6084/m9.figshare.7828160.v1 https://esip.figshare.com/articles/poster/SensorDat_a_testbed_for_improving_real-time_data_quality_and_sensor_provenance/7828160 <div>SensorDat is an ESIP Lab Incubator project, which was funded in the summer of 2018. Real-time sensors are increasingly being used for scientific analysis and discovery in earth science research. The Internet of Things (IoT)</div><div>concept has led to an environment in which small, inexpensive sensors are becoming ubiquitous, providing a whole new set of real-time measurements to the research community. Sensor data used for scientific research</div><div>purposes require additional sophistication due to issues such as interoperability and metadata requirements, spatial and temporal coverage, data quality considerations and precise measurement specifications. Through</div><div>systems like CHORDS, it is now possible to bring a level of standardization and consistency to these new sensor streams, addressing data quality issues in real-time so that problems are caught quickly, ultimately improving</div><div>these measurements. In addition, CHORDS adheres to evolving metadata standards and controlled vocabularies to help researchers discover streaming data in their areas of interest while fully describing the measurements</div><div>being taken (e.g., variables measured, units of measurement, spatial and temporal coverage, etc.). Through the ESIP lab, we have 1) extended the use of CHORDS to real-time data streams that are outside of the traditional NSF</div><div>Geosciences domain, including new sensors that take advantage of IoT miniaturization and 2) develop advanced workflow prototypes focused on automated data quality recipes and annotation. This poster was presented at the Earth Science Information Partners (ESIP) Winter Meeting in January 2019.</div> 2019-03-13 17:35:54 CHORDS NEVCAN SensorDat Data Quality Born Connected Climate Science Atmospheric Sciences Earth Sciences not elsewhere classified Environmental Monitoring Environmental Science Geology Geophysics Geophysics not elsewhere classified Hydrology Meteorology Oceanography not elsewhere classified Oceanography Tectonics Volcanology