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Description
Description
We've identified an issue with the measurement data format provided by Will and Vlad. The dataset contains multiple measurement records with identical collection timestamps but different geographic locations and values. This creates ambiguity when attempting to visualize or analyze the data as a time series.
Current Behavior
The current JSON input has the following characteristics:
- All measurements share the exact same collection time ("2023-02-22 15:35")
- Each measurement has a unique geographic location (POINT format with longitude/latitude)
- Each measurement has a different measurement value
Example of problematic data structure:
{
"measurement": [
{
"measurementvalue": 0.219884184,
"collectiontime": "2023-02-22 15:35",
"geometry": "POINT (-93.956472 29.984063)"
},
{
"measurementvalue": 0.239372971,
"collectiontime": "2023-02-22 15:35",
"geometry": "POINT (-93.956477 29.984125)"
},
...
]
}Impact
This structure creates several problems:
- Time series plots will show multiple values at the same timestamp
- Temporal analysis becomes difficult when all measurements occur at the same moment
- It's unclear how to order or aggregate the measurements at the same timestamp
Proposed Solution
Consider one of the following approaches:
- Increase timestamp precision: Use millisecond or microsecond precision in timestamps to differentiate sequential measurements
{ "measurementvalue": 0.219884184, "collectiontime": "2023-02-22 15:35:00.001", "geometry": "POINT (-93.956472 29.984063)" }
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