This ontology contains a description of soil texture classes determined by sand, clay and silt fractions. It contains inference rules and can be used to translate data that contains numeric soil grain size fractions determined in the lab into their soil texture classification counterpart (and vice versa from classes to clay/silt/sand fraction ranges).
The ontology has initially been created based upon the German soil texture classification system as described in the Bodenkundliche Kartieranleitung, edition 4 (KA4 - in particular table 26 on page 135 of that document). It has been cross-checked against the most recent 6th edition of the Kartieranleitung with no need for changes being observed.
Thus, at the moment it covers requirements for being used as descriptors for datasets only that have been recorded according to that system. The ontology however is easily extensible and using the existing class definitions and hierarchy as a template, basically any different soil texture classification system can be added, like the USDA system, which has different grain diameter limits.
Maintenance is done in this github repo: https://github.com/fairagro/SoilTextureOntology/. Feel free to send patches/pull requests for that - also if you spot errors.
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Initial created on
September 30, 2022.
For additional information, contact
Daniel Martini (d.martini@ktbl.de).
The ontology has initially been created based upon the German soil texture classification system as described in the Bodenkundliche Kartieranleitung, edition 4 (KA4 - in particular table 26 on page 135 of that document). It has been cross-checked against the most recent 6th edition of the Kartieranleitung with no need for changes being observed.
FAIR Data Annotation: Enriches soil datasets with persistent URIs and standardized metadata to make them machine-readable and interoperable., Modeling & Analytics: Provides consistent feature definitions for soil texture variables used in machine learning workflows and crop simulation models., Data Harmonization: Maps different national soil classification schemes (e.g., USDA, WRB, KA5) to a single unified semantic framework for cross-dataset analysis.
