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Tech Manuals & Tools

This page lists various technology related documents focussed on data processing and data publication. Guidelines for the field survey and laboratory analyses can be found at the procedures page.

SIS user manual

A manual on how to use the Soil Data Of Africa system.

SIS user manual

DSM manual

Digital Soil Mapping (DSM) is a digital variation to traditional soil mapping. Modern digital techniques are used to predict the distribution of soil properties in an area.

DSM manual

Predicting soil properties using spectral data

A Jupyter Notebook demonstrating how to build AI models for predicting soil properties using Mid-Infrared (MIR) spectral data. The tutorial progresses through three levels of proficiency: Beginner, Intermediate, and Expert, leveraging the spectraxai library

Open spectral notebook

eXplainable Artificial Intelligence for spectral datasets (Spectraxai)

Spectraxai is a python library to easily develop XAI models for spectral datasets.

Open spectraxai

ISO28258 data model documentation

This document introduces a generic data model implementing the ISO 28258 standard. Furthermore, the data model captures the extensive code-lists gathered in the GloSIS web ontology as thesauri. This data model is intended as a template to be specialised in particular projects or use cases.

ISO28258 data model documentation

Soils4Africa data model (based on ISO28258)

A repository for the development and maintenance of the relational database for the Soils4Africa soil information system.

Open s4a database repository

ISRIC resource library

Resources provided here will support knowledge and skills development on various steps of the Soil Information Workflow, especially to develop soil information system on the national level. The library contains resources provided by various organisations.

Open resource library

SIS framework

The framework helps to find resources and tools to support you with the design and development of national SISs.

Open SIS framework

FAIR data principles

Guidelines to improve the Findability, Accessibility, Interoperability, and Reuse of digital assets. The principles emphasise machine-actionability (i.e., the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention) because humans increasingly rely on computational support to deal with data as a result of the increase in volume, complexity, and creation speed of data.

Open FAIR website

GeoDataCrawler

A commandline tool to create and extract metadata from a file repository containing various spatial datasets. The extracted metadata can be exported in various standardised model and used to populate a catalogue or configure a mapserver.

Open GeoDataCrawler in the Python package index

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