Download FREE eBook

Meet the Author

Stu Hamilton
Senior Hydrologist
Aquatic Informatics

Stu Hamilton was a senior hydrometric technologist with Water Survey Canada for nearly 30 years and managed the operations of over 500 monitoring stations. He is an expert volunteer with the WMO, the ISO, NASH, and the OGC.

FREE eBook  
Communicating Hydrometric Data Quality: What, How, & Why

WHAT?  Characterizing data quality requires compliance with recognized industry standards. Discover the latest standards for selecting a site, monitoring water level, and computing discharge so you can better assess the quality of your data.

HOW?  The OGC has published WaterML 2.0 codes for communicating data quality. Learn how standard operating procedures (e.g. WMO, ISO, USGS, WSC, & NEMS) can be used to characterize the quality property for this new standard for data sharing.

WHY?  Communicating context and quality instills confidence in the data. This enhanced trust results in faster response to emergencies, improved certainty in the allocation of water, and more decisive actions for protecting water and the environment.

The OGC WaterML 2.0 standard is an industry game-changer. The interoperable exchange of water data across agencies is unlocking information silos. But not all data are created equal. Sharing data quality is key to building trust. Making the right decisions requires data that are fit for purpose.

This eBook examines the current standards for characterizing and communicating data quality. Discover how qualifying your data can build confidence and trust with your stakeholders.

Data quality varies from gauge to gauge and from time to time. Understanding this variation is essential for the development of effective monitoring plans. Rigorous characterization of this variation demonstrates a commitment to quality management. Communicating this variation is critically important for the interpretation and analysis of the data. Good outcomes can arise from poor quality data when that quality is properly accounted for in decision making. Inefficient or ineffective results can arise from good quality data if the quality is unspecified and therefore assumed to be poor. All data, regardless of quality, become more valuable when quality is understood, characterized, and shared.

Download Stu's FREE eBook today to learn more!


Providing your email will ensure you receive Aquatic Informatics news, product updates, and industry resources. You can unsubscribe at any time. Privacy Policy.

Aquatic Informatics Inc. | 2400 – 1111 West Georgia St. | Vancouver, BC | V6E 4M3 | 604.873.2782

Aquatic Informatics Inc.