Project: make one useful observation
Put the observation lessons together by making a small record another person could understand without asking you what every field meant.
Why this matters
A small complete record is better practice than importing a giant mysterious dataset. The goal is not volume; it is clarity.
Learn it
Choose something you can honestly observe. Record location, observation time, what was observed, source, value, units, and provenance. Add quality, vertical context, method, media, or uncertainty only when relevant. Then inspect the record as if it came from someone else and ask what is still ambiguous.
Work through an example
A student can record air temperature at a school, a researcher can record water condition at a shoreline, or a field worker can record an inspection state. The structure stays understandable across domains.
Can another person answer: where, when, what, source, value, units, provenance?Practice
- 1Create the observation in the exercise.
- 2Hand it to someone else—or read it tomorrow—and identify any field that needs more context.
- 3Export or represent it in JSON/GeoJSON if location is part of the record.
Try it
Build an observation
A useful observation says what was measured, where and when it happened, what source produced it, the value and units, and enough provenance to understand where the record came from.
{
"where": "47.6062,-122.3321",
"when": "",
"what": "",
"source": "",
"value": "",
"units": "",
"provenance": ""
}What to watch for
Do not fill fields with invented precision or provenance just to make the record look complete. Unknown is better than false.
Where this takes you
This project prepares you for stations, field forms, APIs, datasets, spatial rules, and future Quick Starts.