Collecting, Maintaining and Sharing Large Environmental Datasets

Session: 42. - Multi-Watershed Nutrient Study: Establishing a Monitoring Network in Agricultural Regions

Grace Arabian, Ministry of the Environment and Climate Change, [email protected]
Laura Benakoun, Ministry of the Environment and Climate Change, [email protected]
Derek Smith, Ontario Ministry of the Environment and Climate Change, [email protected]

Abstract

The storage and retrieval of hydrological observation data and water quality data is crucial to support environmental scientific research. A major challenge of data management in environmental science is the integration of data from various instruments and types of data into comparable formats and time scales. Data collected through the Ontario Ministry of Environment and Climate Change’s Multi-Watershed Nutrient Study (MWNS) includes real-time and point water quantity, quality, and meteorological sensor data and additional supporting data collected by partners. This talk will detail the data goals, priorities, tools, challenges and successes of managing large and diverse datasets under the MWNS.  The study leverages various data management tools, primarily relying on open source software called the Observation Data Model (ODM), a relational database model developed by the Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUASHI). Effectively managing large environmental datasets involves maintaining data integrity and clearly documenting metadata, preserving raw data, and retaining the traceability of any modifications for quality control and quality assurance. Clear data management procedures and utilizing supplementary data tools and software are effective solutions for optimizing data analysis and data sharing.

1. Keyword
data storage and retrieval

2. Keyword
data acquisition

3. Keyword
nutrients

4. Additional Keyword
sensor data

5. Additional Keyword
water quantity

6. Additional Keyword
water quality