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Data annotation
mathcoll edited this page Nov 20, 2021
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t6 is focused on timeseries, Data-annotation process is classifying Datapoints from Flows using categories.
Annotations and Categories are going to be used in the Exploratory Data Analysis process.
A classification category is a dataset cotaining a name, a descriptive content and a color. Users on t6 can customize their own Categories - and there are constraints on the number of Categories per users. There is no process of approval on the annotations.
Data-annotation can be associated to Datapoints using any of the following processes:
- Adding manually an annotation with the specific annotation Api endpoint. This hand process is strong but require manual annotation.
- Adding annotations programmatically from a Decision Rule during Datapoint creation.
Each annotation are set for a range of date/time, so the category_id associated to the Annotation can be defined on a specific timespan. Both process are expecting to handle large datasets.
t6 Technical Api Documentation. Please refers to CONTRIBUTING.md in case you would like to help :-)
- Installing t6
- Internal errors
- Repository structure
- Six main Resources
- Other Resources
- Datapoints
- Users
- UIs 💥 not detailed
- Mqtt Topic 💥 not detailed
- Referentials
- Technical Api Documentation 🔗
- TWA Application Screenshots
- t6 Security policy
- Advanced t6 concepts