OPENAIRE OpenAire Datacite B2FIND Recherche Data Gouv OpenAIRE Open Access Open AccessThis dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project. The database was developed by using a decision tree based script which determines the presence or absence of selected WRB diagnostic units (horizons, properties and materials) based on the harmonized soil profile dataset. The python-based code was developed based on the criteria defined by the World Reference Base for Soil Resources 2014 for the selected diagnostic units, by considering the difference in the information content of the input soil profile databases. Besides the presence/absence information, the code returns a percentage of reliability which provides an estimation on the reliability of the prediction of a certain diagnostic unit. The attributes are presented in the 'dh_dictionary' file. Open AccessThis dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project. The database was developed by using a decision tree based script which determines the presence or absence of selected WRB diagnostic units (horizons, properties and materials) based on the harmonized soil profile dataset. The python-based code was developed based on the criteria defined by the World Reference Base for Soil Resources 2014 for the selected diagnostic units, by considering the difference in the information content of the input soil profile databases. Besides the presence/absence information, the code returns a percentage of reliability which provides an estimation on the reliability of the prediction of a certain diagnostic unit. The attributes are presented in the 'dh_dictionary' file. <p>This dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project.</p> <p>The database was developed by using a decision tree based script which determines the presence or absence of selected WRB diagnostic units (horizons, properties and materials) based on the harmonized soil profile dataset. The python-based code was developed based on the criteria defined by the World Reference Base for Soil Resources 2014 for the selected diagnostic units, by considering the d Earth and Environmental Science Soils and soil sciences Agricultural Sciences Climate Life Sciences Agriculture, Forestry, Horticulture, Aquaculture 15. Life on land Soil functions Farming Systems soil Farming Systems and Practices Earth and Environmental Sciences Soil Sciences Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine Environmental Research Natural Sciences climate Agriculture, Forestry, Horticulture Geosciences Saby, Nicolas P.A., Michéli, Erika, Csorba, Adam, Szergi, Tamás, Vadnai, Peter, Dobos, Endre, Bertuzzi, Patrick, Toutain, Benoît, Picaud, Calypso, Gay, Laura, Chenu, Jean-Philippe, Creamer, Rachel, 2020-01-01 Open AccessThis dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project. The database was developed by using a decision tree based script which determines the presence or absence of selected WRB diagnostic units (horizons, properties and materials) based on the harmonized soil profile dataset. The python-based code was developed based on the criteria defined by the World Reference Base for Soil Resources 2014 for the selected diagnostic units, by considering the difference in the information content of the input soil profile databases. Besides the presence/absence information, the code returns a percentage of reliability which provides an estimation on the reliability of the prediction of a certain diagnostic unit. The attributes are presented in the 'dh_dictionary' file. Open AccessThis dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project. The database was developed by using a decision tree based script which determines the presence or absence of selected WRB diagnostic units (horizons, properties and materials) based on the harmonized soil profile dataset. The python-based code was developed based on the criteria defined by the World Reference Base for Soil Resources 2014 for the selected diagnostic units, by considering the difference in the information content of the input soil profile databases. Besides the presence/absence information, the code returns a percentage of reliability which provides an estimation on the reliability of the prediction of a certain diagnostic unit. The attributes are presented in the 'dh_dictionary' file. <p>This dataset corresponds to a datamart produced by the WP2 team of the Landmark H2020 project.</p> <p>The database was developed by using a decision tree based script which determines the presence or absence of selected WRB diagnostic units (horizons, properties and materials) based on the harmonized soil profile dataset. The python-based code was developed based on the criteria defined by the World Reference Base for Soil Resources 2014 for the selected diagnostic units, by considering the d Compilation of diagnostic horizons data 10.15454/fiuwgq dataset https://doi.org/10.15454/fiuwgq 635201