The types and magnitude of earth-observation and water management data pose unique challenges. Instrumentation deployment is growing exponentially, automation is becoming commonplace, and the sophistication of data processing tools are evolving daily. However, data availability does not translate to data usefulness, hindering informed decision-making. Owners, responsible executives, and operators can be inundated with data, especially with the implementation of a multi-disciplinary knowledge base. A wide variety of commercial tools exist to manage site data, however, they are often too rigid and do not accommodate data streams of various types. This talk presents a flexible data management framework developed by SRK to address these challenges. The focus here is not on a specific data management tool or product, but rather on the lessons learned in the process of framework development and the principles adopted in the process. These principles include:
- Assignment of data management responsibilities
- Computer programming and data engineering skills are key
- Flexibility of data ingestion protocols
- Centralized management with data mirroring
- Data QA/QC with subject matter expertise
This presentation discusses the successful application of this framework to legacy sites with over 100 years of historical data and a high throughput of presently collected data, focusing on surface water, groundwater, and geochemical data.
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