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The catalog lists many different types of data. | The catalog lists many different types of data. The text below gives important information about the main types of datasets and what should/shouldn't be indexed. | ||
= Acceptable Data Types = | = Acceptable Data Types = |
Revision as of 08:55, 10 December 2024
The catalog lists many different types of data. The text below gives important information about the main types of datasets and what should/shouldn't be indexed.
Acceptable Data Types
- Model outputs: The output of numerical weather prediction models, such as DALES, HARMONIE and other types of numerical simulations, reanalyses and forecasts. This category partially overlaps with the "Derived/Processed data" category.
- In-situ observations: these are datasets collected directly at the location of interest.
- Remote-sensing observations: (Datasets collected from a distance, typically using satellites or ground-based remote sensors.)
- Derived/Processed Data: highly processed datasets such as blended satellite and in-situ data, physical retrievals, reanalyses and higher-level datasets based on other datasets.
- Geospatial Data: datasets that include spatial information about the Earth's surface, sub-surface and atmosphere. For example GIS layers, coordinate systems, grids, projections etc..
What should not be indexed?
- Software: numerical weather models, toolboxes, etc. should not be indexed.
- Data analysis scripts: For example, Python notebooks, Matlab, R or C scripts should not be indexed. The latter can be documented and distributed through the Ruisdael github page.
- Articles: peer-reviewed papers, technical reports, presentations and other forms of written/oral publications should not be indexed in the catalog.
- datasets that do not have any link to the Ruisdael project.