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An Ontology of Soil Properties and Processes

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Assessing the Underworld (ATU) is a large interdisciplinary UK research project, which addresses challenges in integrated inter-asset maintenance. As assets on the surface of the ground (e.g. roads or pavements) and those buried under it (e.g. pipes and cables) are supported by the ground, the properties and processes of soil affect the performance of these assets to a significant degree. In order to make integrated decisions, it is necessary to combine the knowledge and expertise in multiple areas, such as roads, soil, buried assets, sensing, etc. This requires an underpinning knowledge model, in the form of an ontology. Within this context, we present a new ontology for describing soil properties (e.g. soil strength) and processes (e.g. soil compaction), as well as how they affect each other. This ontology can be used to express how the ground affects and is affected by assets buried under the ground or on the ground surface. The ontology is written in OWL 2 and openly available from the University of Leeds data repository: http:// doi. org/ 10. 5518/ 54.
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An Ontology of Soil Properties and Processes
Heshan Du1, Vania Dimitrova1, Derek Magee1, Ross Stirling2, Giulio Curioni3,
Helen Reeves4, Barry Clarke1, Anthony Cohn1
1University of Leeds
2Newcastle University
3University of Birmingham
4British Geological Survey
Abstract. Assessing the Underworld (ATU) is a large interdisciplinary
UK research project, which addresses challenges in integrated inter-asset
maintenance. As assets on the surface of the ground (e.g. roads or pave-
ments) and those buried under it (e.g. pipes and cables) are supported
by the ground, the properties and processes of soil affect the performance
of these assets to a significant degree. In order to make integrated deci-
sions, it is necessary to combine the knowledge and expertise in multiple
areas, such as roads, soil, buried assets, sensing, etc. This requires an
underpinning knowledge model, in the form of an ontology. Within this
context, we present a new ontology for describing soil properties (e.g.
soil strength) and processes (e.g. soil compaction), as well as how they
affect each other. This ontology can be used to express how the ground
affects and is affected by assets buried under the ground or on the ground
surface. The ontology is written in OWL 2 and openly available from the
University of Leeds data repository: http://doi.org/10.5518/54.
Keywords: OWL ontology, soil property/process, asset maintenance
1 Introduction
Assessing the Underworld (ATU) project is a large interdisciplinary UK research
project, which addresses challenges in asset maintenance, especially how to re-
duce the economic, social and environmental costs or impacts of streetworks
required in the maintenance of roads and buried assets (e.g. pipes and cables).
Existing asset management systems (e.g. UK Pavement Management Systems)
can help local authorities or utility companies with financial reporting or assess-
ing the economic costs of the construction, repairing and replacement of assets,
but provide less support in assessing the environmental/social impacts and the
impacts on other assets, which are also important for enabling better informed
decisions in asset maintenance. To establish the total cost (social and environ-
mental impacts along with economic costs) of asset maintenance activities, it
is essential to understand how assets affect each other and how they affect or
are affected by the natural environment and human activities. Within the ATU
project, we are developing a series of ontologies based on the knowledge and
2 H. Du et al.
expertise in multiple areas for describing how buried assets, soil, roads, the nat-
ural environment and human activities affect each other. The ontology of soil
properties and processes (OSP) is a central ontology in this series.
The condition of an asset can affect and be affected by assets close to it. For
example, a water pipe burst increases the water content of the soil (including
man-made fills) surrounding it. As a consequence, the strength of soil decreases,
which has negative effects on the function of soil for supporting buried pipes and
cables nearby, as well as the roads or pavements above. In many interactions
between assets, as shown in the example above, soil plays a role as a medium. In
other words, the conditions of roads and buried assets affect each other through
soil, and soil directly affect and is affected by the conditions of roads and buried
assets. Therefore, when assessing the impacts of decisions (e.g. whether to fix a
water pipe leakage immediately) for surface or buried asset maintenance, it is
important to have a basic knowledge of soil properties and processes.
Soil has many properties and is involved in various processes, as described in
[16, 15]. The relationships between soil properties and processes are complicated.
Whilst it is often easy to know what a process or property affects directly,
it is more difficult for people to answer questions like ‘what are the factors
affecting or affected (directly or indirectly) by a particular property or process
of soil?’. To answer such questions, it is necessary to handle information about
soil properties, processes and their relationships automatically. This requires a
proper ontological model and automated reasoning.
There exist several ontologies [17,9,20,12,7,18,8,1,2], where soil is defined.
Some of them [17, 7, 1, 2] are general environmental or agricultural ontologies,
whilst others are specialized for describing soil. These soil ontologies [9, 20, 12,
18, 8] are not publicly available. Most of the existing soil ontologies [9, 20, 18, 8]
describe classifications of soil or different types of soil but do not elaborate the
various soil properties and processes. The ontologies described in [12, 2] define
some soil physical/chemical properties, but limited to those relevant to farming
or agricultural applications. None of the existing ontological models provides a
systematic and comprehensive description of soil properties and processes, and
none of them defines how soil properties and processes affect each other.
The paper addresses this gap. We present a new ontology for describing soil
properties and processes, as well as how they affect each other. It reuses and
specifies high-level classes in NASA’s Semantic Web for Earth and Environ-
mental Terminology (the SWEET ontology) [17], which is widely adopted and
extended. The ontology is developed using the NeOn methodology [19]. It is
written in OWL 2 Web Ontology Language Manchester Syntax [14], which is
based on description logic (DL) [6]. The DL expressivity of the ontology is SRI,
allowing transitive relations and inverse relations5. The ontology contains 592
concepts and 2243 relation statements (OWL logical axioms), which are based
on the knowledge of soil experts6, the SWEET ontology [5, 17], English dictio-
5To avoid confusion, we call ‘OWL object properties’ relations.
6Soil experts were involved in the development and evaluation of the OSP ontology.
They checked 1407 relation statements for describing 193 main classes.
An Ontology of Soil Properties and Processes 3
naries [3, 4] and a textbook on soil physics [16]. The ontology, together with
a tutorial of viewing and querying it, a translation of its main relation state-
ments in natural language and a feedback form, is publicly available [11] from
the University of Leeds data repository: http://doi.org/10.5518/54, under
the license Creative Commons Attribution 4.0 International (CC BY 4.0)7.
The rest of the paper is structured as follows. Section 2 describes how the
main concepts and relations are defined in the ontology. Section 3 explains how
to reason with and query the ontology. Section 4 illustrates the extensibility of
the ontology. Section 5 discusses its applications. Section 6 concludes the paper.
2 Defining Soil Properties and Processes
The ontology of soil properties and processes (OSP) defines two main high-level
classes or categories: SoilProperty and SoilProcess. The classes SoilProperty and
SoilProcess are specifications of the classes Property and Process in the SWEET
ontology [5, 17] for soil. A property is an attribute, quality, or characteristic of
something [4]. A soil property is a property of soil. A process refers to a series of
changes that happen naturally over time [3,4]. A soil process is a process involv-
ing soil. Following the style of the SWEET ontology, we define different kinds of
soil properties and processes as classes in the OSP ontology and classify them
into physical, chemical and spatial/biological categories. Table 2 summarizes
the number of subclasses of SoilProperty and SoilProcess in different categories.
Though the OSP ontology covers classes in all these categories, it mainly de-
scribes soil physical properties and processes.
Table 1. Number of subclasses of SoilProperty and SoilProcess in the OSP ontology
SoilProperty Subclasses SoilProcess Subclasses
SoilPhysicalProperty 176 SoilPhysicalProcess 111
SoilChemicalProperty 16 SoilChemicalProcess 29
SoilSpatialProperty 4 SoilBiologicalProcess 8
In addition to classifying soil properties and processes into different cate-
gories as the SWEET ontology does, we also define soil properties and processes
regarding how they affect each other. The main types of relations defined in the
OSP ontology are hasImpactOn and its inverse influencedBy, meaning ‘affects or
changes’ and ‘is affected or changed by’ respectively. The relations hasImpactOn
and influencedBy are both defined as transitive. A process qhasImpactOn a
property p, if qcauses a change in p. A property phasImpactOn a process q,
if a change in pchanges how the process qgoes. A property p1hasImpactOn a
property p2, if a change in p1causes a change in p2. A process q1hasImpactOn
7https://creativecommons.org/licenses/by/4.0/
4 H. Du et al.
a process q2, if q1changes how the process q2goes. Other relations defined in
the OSP ontology include hasPossibleCause and its inverse hasPossibleEffect,
meaning ‘has a possible reason’ and ‘has a possible consequence’ respectively.
The word ‘possible’ means the cause/effect exists in some situation, but may
exist or not exist in a particular real world situation considered.
In the OSP ontology, we define relationships between soil properties and
processes at the concept level rather than at the individual level. For example,
we express ‘soil water content hasImpactOn soil strength’ in description logic as
SoilWaterContent v ∃hasImpactOn.SoilStrength. Such relation statements are
not defined for a particular type of soil at a certain location and depth, but
generally applicable to any soil. The statement ‘soil water content hasImpactOn
soil strength’ means that for any soil, a change in its water content causes a
change in its strength8. Similarly, the statement ‘soil compaction hasImpactOn
soil air content’ means for any soil, a compaction applied to it changes the air
content of it. The statement ‘soil compaction hasImpactOn soil air movement’
means for any soil, a compaction applied to it changes how the air in it moves.
The statement ‘soil air movement is influencedBy soil porosity’ means for any
soil, a change in its porosity changes how the air in it moves. Note that inverse
relations are not always reciprocally asserted in the manually-written ontology.
We rank subclasses of SoilProperty and SoilProcess based on their usages or
how many statements a class is involved. If a class is involved in a statement,
then any class equivalent to it is also considered to be involved in the same
statement. Table 2 lists the top 20 classes in this ranking, which illustrates the
main soil properties and processes defined in the OSP ontology well. For each set
of equivalent classes, only one class in it is included in the list to represent the
whole set. When naming a soil property/process class, ‘Soil’ is added to the front
to avoid potential name conflicts. A class name indicates its intended meaning.
For instance, the class name SoilWaterInfiltration is intended to represent the
concept of ‘infiltration of water into soil’.
3 Querying the OSP ontology
Description logic (DL) reasoners can be used to reason about statements in the
OSP ontology. A basic question a reasoner can answer is whether a statement
(e.g. ‘SoilWaterEvaporation hasImpactOn SoilStrength’) can be inferred from
statements in a given ontology. A justification based explanation framework [13]
can be used together with a DL reasoner to explain how a new statement is
inferred from existing statements. By reasoning with the OSP ontology, more
advanced questions can be answered, such as, for given a class C, list all the
classes that ChasImpactOn or influencedBy.
8According to DL/OWL semantics, it means ‘every soil water content hasImpactOn
some soil strength’. The interpretation adopted here is more strict, however, this
makes more sense for soil experts and the standard DL inference rules are still
sound. In practice, we only expect the model to be applied to a local spatial context.
An Ontology of Soil Properties and Processes 5
Table 2. Ranking the subclasses of SoilProperty and SoilProcess in the OSP ontology
by the number of statements involved (usages) — the Top 20
SoilProperty Usages SoilProcess Usages
1 SoilMoistureContent 93 SoilAeration 70
2 SoilStructure 93 SoilCompaction 59
3 SoilTexture 67 SoilWaterInfiltration 40
4 SoilPorosity 62 SoilCrusting 40
5 SoilTemperature 59 SoilWaterEvaporation 39
6 SoilStrength 52 SoilAggregation 39
7 SoilClayMineral 49 SoilWaterMovement 32
8 SoilBulkDensity 40 SoilErosion 29
9 SoilOrganicMatterContent 39 SoilDrying 29
10 SoilHydraulicConductivity 36 SoilShrinkage 28
11 SoilParticleSpecificSurfaceArea 31 SoilWaterRetention 28
12 SoilClayContent 30 SoilSoluteTransport 26
13 SoilPoreSizeDistribution 28 SoilMicrobialActivity 21
14 SoilCohesion 23 SoilHardsetting 20
15 SoilPlasticity 22 SoilWaterTransmission 19
16 SoilMoisturePotential 18 SoilFreezing 19
17 SoilParticleArrangement 18 SoilDeformation 18
18 SoilBearingCapacity 18 SoilSwelling 18
19 SoilOxygenConcentration 18 SoilDispersion 18
20 SoilAirContent 17 SoilGaseousEmission 17
A simple way to reason with and query the OSP ontology is to use an on-
tology editor Prot´eg´e9and its reasoner plugins. Within the DL query tab of
Prot´eg´e, we can execute queries like getting all subclasses of the class expression
‘(hasImpactOn some SoilStrength) and SoilProperty’. For each class listed in the
query results, its explanations can be obtained easily. We provide a tutorial [10]
illustrating (with figures and examples) how to query the OSP ontology. It is
available at: http://doi.org/10.5518/54, the same DOI of the OSP ontology.
4 Extensibility of the OSP ontology
The OSP ontology extends three other top-level classes, Phenomena,
HumanActivity and Substance, of the SWEET ontology [5, 17]. A phenomenon
refers to a fact/situation that exists and can be observed [3, 4]. A human ac-
tivity refers to a thing that a person/group does or has done [4]. The con-
cept Substance [5] covers living entities and non-living entities, such as animals,
plants, material things, etc. By including these concepts, the OSP ontology can
express how soil properties and processes affect/are affected by other environ-
mental factors (such as water, air, weather and trees) and human activities.
9http://protege.stanford.edu
6 H. Du et al.
For each of the five top-level classes, its next-level classes in the OSP ontology
are shown in Fig. 1. Some of the next-level classes (e.g. PlanetaryPhenomena,
and MaterialThing) are inherited from the SWEET ontology, whilst others (e.g.
PlantProcess and SoilSubstance) are created by specifying high-level concepts in
the SWEET ontology for a particular type of objects. All the high-level categories
can be extended and enriched further easily by reusing concepts in the SWEET
ontology and following similar ways as defining soil properties and processes in
Section 2. In addition, more high-level categories can be added easily and linked
to the existing classes. We are developing ontologies for describing pipe/road
properties, processes and phenomena (e.g. defects or failures) in a similar way
and linking them to the OSP ontology.
Fig. 1. Class hierarchies of the five top-level classes in the OSP ontology
Note that the OSP ontology mainly describes soil properties and processes
from a soil science perspective, but also captures main terminologies (e.g. soil
compaction) used in engineering applications. We are aware that terminological
differences exist between soil scientists and geotechnical engineers. We follow the
concepts defined in soil science mainly because they are more understandable by
non-specialists. The OSP ontology can be extended and enriched with parame-
ters10 (e.g. soil shear strength) and calculations defined in soil mechanics [15].
5 Application
The OSP ontology is intended to be used in a software system that supports
inter-asset management/maintenance decisions (ATU decision support system).
10 The OSP ontology describes several parameters used for assessing soil structure,
under a class called SoilStructureIndex.
An Ontology of Soil Properties and Processes 7
When making decisions for maintaining a single asset, people (e.g. local author-
ities and utility companies) often consider the economic cost but may not be
aware or take into account the impacts of their decisions or actions on other
assets, the natural environment and our daily life. The ATU decision support
system will prompt people into asking a series of questions, the answers to which
will lead to a complete understanding of the economic, social and economic im-
pacts of different options for dealing with an asset defect/failure. By developing
the OSP ontology, we establish a general framework, which extends the SWEET
ontology, for expressing how properties, processes, phenomena, human activities
and substances affect each other. In this way, many environmental and social
impacts can be represented in an ontology or inferred from it using automatic
reasoning. The OSP ontology can help users understand the environmental im-
pacts of a process or a human activity related to soil. For example, knowing that
a water pipe leakage affects soil water content, we may ask the OSP ontology
about the impacts of a change in soil water content. By executing a DL query
of getting subclasses of ‘influencedBy some SoilWaterContent’ in Prot´eg´e, a list
of 264 classes is returned11, including various soil properties and processes, as
well as factors like building stability, plant growth, air quality, water quality, etc.
For classes listed, explanations are provided, which are useful for identifying and
understanding indirect or hidden impacts.
The soil properties and processes described in the OSP ontology have many
agricultural, engineering and environmental applications (see the subclasses of
SoilFunction). For example, the OSP ontology describes how the growth of a
plant is affected by soil and other environmental factors. The OSP ontology can
be applied to a range of contexts that require descriptions of soil properties or
processes. For example, the EU project NeTTUN12 utilises soil properties and
processes to provide contextual factors for tunnel construction and maintenance.
By extending the OSP ontology and linking it to ontologies for describing the
environment, infrastructure assets, human activities and economic cost models,
we envisage that the OSP ontology will make a useful contribution to ontological
models for environmental, social and economic sustainability.
6 Conclusion
We present a new ontology OSP for describing soil properties, processes and how
they affect each other. It is created using reliable knowledge sources and extends
the SWEET ontology. It can be reasoned with automatically using DL reasoners
and queried using Prot´eg´e. The OSP ontology helps people to understand indi-
rect and complicated relationships between soil properties and processes, as well
as many environmental impacts of a process or a human activity related to soil.
The OSP ontology is easy to (re)use, easily extensible, generally applicable, pub-
licly available and findable. As the ATU decision support system develops, we
will maintain and enhance this ontology, making new versions publicly available.
11 Different types of factors can be filtered out easily using DL query.
12 http://nettun.org
8 H. Du et al.
Acknowledgments. This research is supported by EPSRC under grant no.
EP/K021699/1 which we gratefully acknowledge. The final publication is avail-
able at Springer via http://dx.doi.org/10.1007/978-3-319-46547- 0_4.
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... Soil classification plays a vital role in safety regulations, where each type of soil has its own structure and properties, which affect soil behavior under different circumstances. Soil classification can be obtained based on different values of the properties [23], which directly affect the stability of the excavation and the choice of suitable safety procedures and resources. OSHA standard number 1926 Subpart P Appendix A [24] provides examples of the guidelines that can be applied to classify the soil based on various properties. ...
... However, outside of the discipline of soils science, there is confusion over soil's properties and processes amongst experts from related fields (e.g. Du et al., 2016). Furthermore, once concepts such as soil security enter the policy realm they are likely to be subject to reinterpretation by non-disciplinary experts leading to reframing and confusion, and perhaps, dilution of the power of the narrative to drive changes in the policy agenda. ...
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