This video looks at the environmental monitoring workflow. One of the clearest ways to understand environmental monitoring data management is to understand the workflow it supports.
Transcript
The environmental monitoring workflow.
One of the clearest ways to understand environmental monitoring data management is to understand the workflow it supports.
From Planning
Field data collection
Sample collection
Laboratory analysis
Data import
QA/QC review
Standards comparisons
Trend analysis
and finally Reporting
That workflow sounds simple when written in one line, but every stage matters because monitoring data is cumulative. Each monitoring round adds new information, and the quality of each stage affects the usefulness of the next stage.
Step 1. Planning.
Monitoring begins with sites, locations, schedules, analytes, sample plans, and objectives. A structured program starts here, not at the reporting stage.
Step 2. Field data collection.
Field teams record observations, measurements, groundwater levels, field chemistry, and photographs, and they collect samples. Errors or inconsistencies here often travel downstream into the rest of the workflow.
Step 3. Laboratory analysis.
Samples are analyzed and returned as laboratory data, often in structured electronic formats. This stage creates large quantities of information quickly, especially in recurring programs.
Step 4. Data import.
Those laboratory results need to be loaded accurately and linked to the correct samples, locations, dates, and monitoring rounds.
Step 5. Quality Assurance and Quality Control Review.
Before the data is used in compliance decisions or reporting, it should be reviewed for completeness and consistency.
Step 6. Standards comparison
Results are then compared against the relevant environmental standards, trigger values, or site-specific limits.
Step 7. Trend analysis
Monitoring data is valuable because it shows change across time. Graphs, dashboards, tables, and maps all become useful here.
Step 8. Reporting
The final stage is not just storage or export. It is communication: internal reporting, client updates, regulator submissions, and public-facing outputs where needed.
This is one reason environmental monitoring data management is best understood as a workflow discipline rather than just a software feature.
The Full article on the Environmental Monitoring
