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13 In a fully interoperable system there would be interdependencies between the use cases.
1. Use case 4 would use data published by services implemented to provide data according to use cases 1, 2 and 3.
2. Use case 3 would include data from services supporting use cases 1, 2 and 4 along with other environmental datasets when generating the predictions.
8 Comparison of Existing Soil Information Models
Various national and international initiatives have worked on information models to support the exchange of soil data. This experiment intended to reconcile core concepts
and features of these models into a single coherent, fully attributed, implementable, albeit provisional, standard. The five models that were reviewed in this IE were:
1. Australia and New Zealand Soil Mark-up Language ANZSoilML; 2. e-SOTER Soil and Terrain Mark-up Language SoTerML;
3. INSPIRE D2.8.III.3 Data Specification on Soil INSPIRE Soil; 4. ISO 28258:2013 Soil quality – Digital exchange of soil-related data ISO SoilML;
and 5. IUSSISO ‘Wageningen Proposal’ a variation of 4 with reference to 1, 2 and 3.
This section provides an overview of the models, comparing their breadth of content and modeling technique. A summary of each model can be found in Annex B.
8.1 Basis for comparison
The models were compared according to their scope, the modeling techniques and patterns used in their definition, whether they are readily available and implemented, and
the context in which they have been used e.g. production or prototype. Only documents that could reasonably be considered normative and were of unambiguous origin were
used for the comparison UML models and XML Schema Documents.
Scope refers to the breadth of information captured by each model. As each model has a different level of abstraction and conceptual base an external basis for comparison was
necessary. The FAO Guidelines for Soil Description [3], with additional guidance from the USDA Field Book for Describing and Sampling Soils [11], was adapted to define and
group the key dimensions of a soil. The comparison is only intended to be indicative of scope and does not imply strict conformance to the FAO and USDA guidelines.
The criteria for comparison can be grouped into eight categories:
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1. Site registration: identity, location, timing and other metadata about sampling sites; 2. Soil formation: environmental and human factors influencing the formation of the
soil; 3. Soil description: physical, chemical and organic character of a soil;
4. Sampling: collection of physical samples; 5. Observation: field or laboratory measurements of soil properties;
6. Classification: categorization of soil and horizons according to formal taxonomies; 7. Vocabularies: systems for managing terms and their definitions; and
8. Mapping: mapping the distribution of soils according to their type.
Modeling approach refers to how the model was defined. Models may be:
— comprehensive, attempting to cover as many dimensions of the soil as possible and favoring hard-typed properties where properties are explicitly defined and bound to
classes. Additional properties may be specified using a soft-typing mechanism values presented as property-value-pairs where the property refers to a dynamic
register of properties;
— targeted, hard-typing a selected set of essential properties while relying on soft-typing for a significant set of properties; or
— framework, a model that simply provides a framework of classes. Soft-typed properties are used almost exclusively.
Accessibility refers to the availability of the model UML models, XML schema, specification documents and other artefacts in terms of access constraints or charges for
access.
Implementation readiness attempts to capture whether a model may be implemented e.g. deployed as web services with comparative ease high, some difficulty but
minimal technical impediment medium or with significant effort andor technical impediments low.
Implementation shows whether a standard has been implemented, either as a prototype in a production environment.
