SensorDat: a testbed for improving real-time data quality and sensor provenance

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)

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

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

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

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

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

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.