simpler figure, table, and alerts

Note that Figure 1 aims at showing a global overview of the main classes of SAREF4AGRI and their mutual relations. More details on the different parts of Figure 1 are provided from clause 4.2.2 to clause 4.2.8.

Note that Figure 1 aims at showing a global overview of the main classes of SAREF4AGRI and their mutual relations. More details on the different parts of Figure 1 are provided from clause 4.2.2 to clause 4.2.8.

<figure id="Figure_1">

<figure>

        <img data-docx-width="23.59cm" src="diagrams/Overview.png" alt="SAREF4AGRI overview"/>

        <img data-docx-width="23.59cm" src="diagrams/Overview.png" alt="SAREF4AGRI overview"/>

        <figcaption>Figure 1: SAREF4AGRI overview</figcaption>

        <figcaption>Figure 1: SAREF4AGRI overview</figcaption>

    </figure>

    </figure>

The `ssn:System` class in the SSN ontology represents a system and is components as specific devices, actuators or sensors. Moreover, the `ssn:Deployment` class from the SSN ontology describes the deployment of one or more systems on a `sosa:Platform` for a particular purpose for a given time period. SAREF4AGRI defines a `saref:Device` as subclass of an `ssn:System` and extends the `ssn:Deployment` class by means of the `s4agri:Deployment` class. In this way, it is possible to represent a specific installation of a certain agricultural system (e.g. a smart irrigation system) in a given space (expressed by means of the property `s4agri:hasDeploymentPeriod`) and at a given temporal frame (expressed by means of the property `s4agri:isDeployedAtSpace`) where SAREF4AGRI devices (e.g. a pluviometer, a soil tensiometer, a weather station and a watering gun) can be deployed. The deployment can involve a given `sosa:Platform` which hosts the system deployed in such deployment. In order to represent temporal information the TIME ontology has been reused. For the geographical information both the GeoSPARQL ontology ([http://www.opengis.net/ont/geosparql#](http://www.opengis.net/ont/geosparql)) and the WGS84 Geo vocabulary ([http://www.w3.org/2003/01/geo/wgs84_pos#](http://www.w3.org/2003/01/geo/wgs84_pos)) are reused.

The `ssn:System` class in the SSN ontology represents a system and is components as specific devices, actuators or sensors. Moreover, the `ssn:Deployment` class from the SSN ontology describes the deployment of one or more systems on a `sosa:Platform` for a particular purpose for a given time period. SAREF4AGRI defines a `saref:Device` as subclass of an `ssn:System` and extends the `ssn:Deployment` class by means of the `s4agri:Deployment` class. In this way, it is possible to represent a specific installation of a certain agricultural system (e.g. a smart irrigation system) in a given space (expressed by means of the property `s4agri:hasDeploymentPeriod`) and at a given temporal frame (expressed by means of the property `s4agri:isDeployedAtSpace`) where SAREF4AGRI devices (e.g. a pluviometer, a soil tensiometer, a weather station and a watering gun) can be deployed. The deployment can involve a given `sosa:Platform` which hosts the system deployed in such deployment. In order to represent temporal information the TIME ontology has been reused. For the geographical information both the GeoSPARQL ontology ([http://www.opengis.net/ont/geosparql#](http://www.opengis.net/ont/geosparql)) and the WGS84 Geo vocabulary ([http://www.w3.org/2003/01/geo/wgs84_pos#](http://www.w3.org/2003/01/geo/wgs84_pos)) are reused.

<figure id="Figure_2">

<figure>

        <img data-docx-width="17.00cm" src="diagrams/Platform.png" alt="Platform, System and Deployment"/>

        <img data-docx-width="17.00cm" src="diagrams/Platform.png" alt="Platform, System and Deployment"/>

        <figcaption>Figure 2: Platform, System and Deployment</figcaption>

        <figcaption>Figure 2: Platform, System and Deployment</figcaption>

    </figure>

    </figure>

Table 2 summarizes the properties that characterize the `s4agri:Deployment` class.

Table 2 summarizes the properties that characterize the `s4agri:Deployment` class.

<table id="Table_2" data-docx-preferred-width="9.48cm 6.96cm">

<table data-docx-preferred-width="9.48cm 6.96cm">

  <caption>Table 2: Properties of Deployment</caption>

  <caption>Table 2: Properties of Deployment</caption>

  <tr>

  <tr>

    <th>

    <th>

* `saref:hasFeatureOfInterest` (and its inverse `saref:isFeatureOfInterestOf`) to link a given measurement with the feature of interest being observed.

* `saref:hasFeatureOfInterest` (and its inverse `saref:isFeatureOfInterestOf`) to link a given measurement with the feature of interest being observed.

* `saref:measurementMadeBy` has been included as complement of the `saref:makesMeasurement`, as its inverse, to link a measurement and the device that produces it.

* `saref:measurementMadeBy` has been included as complement of the `saref:makesMeasurement`, as its inverse, to link a measurement and the device that produces it.

<figure id="Figure_3">

<figure>

        <img data-docx-width="13.52cm" src="diagrams/Measurement.png" alt="Measurement model"/>

        <img data-docx-width="13.52cm" src="diagrams/Measurement.png" alt="Measurement model"/>

        <figcaption>Figure 3: Measurement model</figcaption>

        <figcaption>Figure 3: Measurement model</figcaption>

    </figure>

    </figure>

The main features of interest in SAREF4AGRI currently support (aspects of) the livestock farming and smart irrigation use cases and are represented by the `s4agri:Animal`, `s4agri:AnimalGroup`, `s4agri:Crop` and `s4agri:Soil` classes that are shown in Figure 4. 

The main features of interest in SAREF4AGRI currently support (aspects of) the livestock farming and smart irrigation use cases and are represented by the `s4agri:Animal`, `s4agri:AnimalGroup`, `s4agri:Crop` and `s4agri:Soil` classes that are shown in Figure 4. 

<figure id="Figure_4">

<figure>

        <img data-docx-width="4.54cm" src="diagrams/FoI.png" alt="Animal, Crop and Soil"/>

        <img data-docx-width="4.54cm" src="diagrams/FoI.png" alt="Animal, Crop and Soil"/>

        <figcaption>Figure 4: Animal, Crop and Soil</figcaption>

        <figcaption>Figure 4: Animal, Crop and Soil</figcaption>

    </figure>

    </figure>

Table 3 and Table 4 summarize the definitions of the main classes and properties described above. 

Table 3 and Table 4 summarize the definitions of the main classes and properties described above. 

<table id="Table_3" data-docx-preferred-width="4.24cm 12.74cm">

<table data-docx-preferred-width="4.24cm 12.74cm">

  <caption>Table 3: Animal, Crop and Soil: class definitions</caption>

  <caption>Table 3: Animal, Crop and Soil: class definitions</caption>

  <tr>

  <tr>

    <th>

    <th>

<table id="Table_4" data-docx-preferred-width="6.74cm 10.24cm">

<table data-docx-preferred-width="6.74cm 10.24cm">

  <caption>Table 4: Animal and Crop: property definitions</caption>

  <caption>Table 4: Animal and Crop: property definitions</caption>

  <tr>

  <tr>

    <th>

    <th>

SAREF4AGRI extends the device hierarchy defined in SAREF in order to include devices needed to support the livestock farming and the smart irrigation use cases. These devices are shown in Figure 5. The devices included for the Smart Irrigation use case are: `s4agri:Pluviometer`, `s4agri:SoilTensiometer`, `s4agri:WeatherStation,` and `s4agri:WateringGun`. The devices included for the Livestock Farming use case are: `s4agri:MovementActivitySensor`, `EatingActivitySensor`, `s4agri:MilkingSensor,` and `s4agri:WeightSensor`.

SAREF4AGRI extends the device hierarchy defined in SAREF in order to include devices needed to support the livestock farming and the smart irrigation use cases. These devices are shown in Figure 5. The devices included for the Smart Irrigation use case are: `s4agri:Pluviometer`, `s4agri:SoilTensiometer`, `s4agri:WeatherStation,` and `s4agri:WateringGun`. The devices included for the Livestock Farming use case are: `s4agri:MovementActivitySensor`, `EatingActivitySensor`, `s4agri:MilkingSensor,` and `s4agri:WeightSensor`.

<figure id="Figure_5">

<figure>

        <img data-docx-width="8.34cm" src="diagrams/Device.png" alt="Device hierarchy"/>

        <img data-docx-width="8.34cm" src="diagrams/Device.png" alt="Device hierarchy"/>

        <figcaption>Figure 5: Device hierarchy</figcaption>

        <figcaption>Figure 5: Device hierarchy</figcaption>

    </figure>

    </figure>

The properties included for the livestock farming use case are: `s4agri:Yield` (which can further be specialized in subclasses, such as MilkYield, CropYield, MeatYield, MilkYield, etc. as needed) and `s4agri:Intake` (which can further be specialized in subclasses, such as FoodIntake for animals, FertilizerIntake for crops, etc. as needed). 

The properties included for the livestock farming use case are: `s4agri:Yield` (which can further be specialized in subclasses, such as MilkYield, CropYield, MeatYield, MilkYield, etc. as needed) and `s4agri:Intake` (which can further be specialized in subclasses, such as FoodIntake for animals, FertilizerIntake for crops, etc. as needed). 

<figure id="Figure_6">

<figure>

        <img data-docx-width="8.08cm" src="diagrams/Property.png" alt="Property hierarchy"/>

        <img data-docx-width="8.08cm" src="diagrams/Property.png" alt="Property hierarchy"/>

        <figcaption>Figure 6: Property hierarchy</figcaption>

        <figcaption>Figure 6: Property hierarchy</figcaption>

    </figure>

    </figure>

Table 5 summarizes the definitions of the classes described above.

Table 5 summarizes the definitions of the classes described above.

<table id="Table_5" data-docx-preferred-width="4.24cm 12.74cm">

<table data-docx-preferred-width="4.24cm 12.74cm">

  <caption>Table 5: Intake and Yield: class definitions</caption>

  <caption>Table 5: Intake and Yield: class definitions</caption>

  <tr>

  <tr>

    <th>

    <th>

SAREF4AGRI adopts the same topology modelling pattern that is adopted in the SAREF4CITY extension [i.3], where existing standard ontologies have been reused for this purpose. As shown in Figure 7, for representing spatial objects in SAREF4AGRI, the `geosp:SpatialObject` class from GeoSPARQL has been reused along with its subclasses `geosp:Feature`, `geosp:Geometry` and the properties `geosp:sfContains`, `geosp:sfWithin` and `geosp:hasGeometry`. In addition, the class `geo:Point` and the property `geo:location` have been reused from the "WGS84 Geo Positioning vocabulary" (which is the W3C de-facto standard for geographical information) in order to be able to indicate that something is located at certain coordinates. 

SAREF4AGRI adopts the same topology modelling pattern that is adopted in the SAREF4CITY extension [i.3], where existing standard ontologies have been reused for this purpose. As shown in Figure 7, for representing spatial objects in SAREF4AGRI, the `geosp:SpatialObject` class from GeoSPARQL has been reused along with its subclasses `geosp:Feature`, `geosp:Geometry` and the properties `geosp:sfContains`, `geosp:sfWithin` and `geosp:hasGeometry`. In addition, the class `geo:Point` and the property `geo:location` have been reused from the "WGS84 Geo Positioning vocabulary" (which is the W3C de-facto standard for geographical information) in order to be able to indicate that something is located at certain coordinates. 

<figure id="Figure_7">

<figure>

        <img data-docx-width="8.80cm" src="diagrams/Topology.png" alt="Topology model"/>

        <img data-docx-width="8.80cm" src="diagrams/Topology.png" alt="Topology model"/>

        <figcaption>Figure 7: Topology model</figcaption>

        <figcaption>Figure 7: Topology model</figcaption>

    </figure>

    </figure>

As it is modelled in the SAREF4CITY extension [i.3], also SAREF4AGRI reuses the FOAF vocabulary (http://xmlns.com/foaf/0.1/) and Schema.org vocabulary ([https://schema.org/](https://schema.org/)) to represent the concepts of Person and Organization. Figure 8 shows that in SAREF4AGRI the `foaf:Person` and `org:Organization` classes are extended with the `s4agri:Farmer` and `s4agri:FarmHolding` subclasses to describe farmers and their organizations. Both `foaf:Person` and `org:Organization` are subclass of `foaf:Agent`. Organizations (e.g. `s4agri:FarmHolding)` have members (e.g. farmers). Both `s4agri:Farmer` and `s4agri:FarmHolding` can manage some `s4agri:Farm`. 

As it is modelled in the SAREF4CITY extension [i.3], also SAREF4AGRI reuses the FOAF vocabulary (http://xmlns.com/foaf/0.1/) and Schema.org vocabulary ([https://schema.org/](https://schema.org/)) to represent the concepts of Person and Organization. Figure 8 shows that in SAREF4AGRI the `foaf:Person` and `org:Organization` classes are extended with the `s4agri:Farmer` and `s4agri:FarmHolding` subclasses to describe farmers and their organizations. Both `foaf:Person` and `org:Organization` are subclass of `foaf:Agent`. Organizations (e.g. `s4agri:FarmHolding)` have members (e.g. farmers). Both `s4agri:Farmer` and `s4agri:FarmHolding` can manage some `s4agri:Farm`. 

<figure id="Figure_8">

<figure>

        <img data-docx-width="8.80cm" src="diagrams/Person.png" alt="Person and Organization model"/>

        <img data-docx-width="8.80cm" src="diagrams/Person.png" alt="Person and Organization model"/>

        <figcaption>Figure 8: Person and Organization model</figcaption>

        <figcaption>Figure 8: Person and Organization model</figcaption>

    </figure>

    </figure>

The first part of the example is related to the organizational aspects of the farm and is shown in Figure 9. 

The first part of the example is related to the organizational aspects of the farm and is shown in Figure 9. 

<figure id="Figure_9">

<figure>

        <img data-docx-width="25.10cm" src="diagrams/image10.png" alt="Farm example"/>

        <img data-docx-width="25.10cm" src="diagrams/image10.png" alt="Farm example"/>

        <figcaption>Figure 9: Farm example</figcaption>

        <figcaption>Figure 9: Farm example</figcaption>

    </figure>

    </figure>

Figure 10 elaborates on _ex:Parcel North_ that contains the _ex:Cow Group A_ with two cows (i.e. _ex:Cow1_ and _ex:Cow2_) which are similarly taxonomically described using the `TAXRANK` taxonomy vocabulary. The _ex:Cow Group A_ generates `s4agri:MilkYield`, which is a type of `s4agri:Yield` and consequently a `s4agri:Property`. The example contains one instance of _Milk Yield_ that represents the outcome of the milking procedure of a certain cow. The _Milk Yield_ instance is measured in _om:Liter_ by the _ex:MilkYieldSensor_. The _ex:MilkYieldSensor_ is of type `s4agri:MilkingSensor`, which is a `saref:Sensor`, and thus a FunctionRelated `saref:Device`. Figure 10 further shows that the sensor is contained in an _ex:Milking Machine_, which is a `saref:Device`, and the _ex:Milking Machine_ has a sensor that measures the yield. The measurements are directly linked to the sensor, instead of to the milk machine itself, because a large machine can have multiple sensors. 

Figure 10 elaborates on _ex:Parcel North_ that contains the _ex:Cow Group A_ with two cows (i.e. _ex:Cow1_ and _ex:Cow2_) which are similarly taxonomically described using the `TAXRANK` taxonomy vocabulary. The _ex:Cow Group A_ generates `s4agri:MilkYield`, which is a type of `s4agri:Yield` and consequently a `s4agri:Property`. The example contains one instance of _Milk Yield_ that represents the outcome of the milking procedure of a certain cow. The _Milk Yield_ instance is measured in _om:Liter_ by the _ex:MilkYieldSensor_. The _ex:MilkYieldSensor_ is of type `s4agri:MilkingSensor`, which is a `saref:Sensor`, and thus a FunctionRelated `saref:Device`. Figure 10 further shows that the sensor is contained in an _ex:Milking Machine_, which is a `saref:Device`, and the _ex:Milking Machine_ has a sensor that measures the yield. The measurements are directly linked to the sensor, instead of to the milk machine itself, because a large machine can have multiple sensors. 

<figure id="Figure_10">

<figure>

        <img data-docx-width="25.49cm" src="diagrams/image11.png" alt="Cow, milking sensor and measurement example"/>

        <img data-docx-width="25.49cm" src="diagrams/image11.png" alt="Cow, milking sensor and measurement example"/>

        <figcaption>Figure 10: Cow, milking sensor and measurement example</figcaption>

        <figcaption>Figure 10: Cow, milking sensor and measurement example</figcaption>

    </figure>

    </figure>

Figure 11 further shows an example of another `s4agri:AnimalGroup`, namely _ex:Cow Group B_. This `s4agri:AnimalGroup` only contains a single cow (i.e. _ex:Cow3_) whose eating activity is being monitored by _ex:Cow Eating Activity Sensor 33_. This `s4agri:EatingActivitySensor` made two measurements about the cow eating activity (i.e. the minutes a cow eats per hour).

Figure 11 further shows an example of another `s4agri:AnimalGroup`, namely _ex:Cow Group B_. This `s4agri:AnimalGroup` only contains a single cow (i.e. _ex:Cow3_) whose eating activity is being monitored by _ex:Cow Eating Activity Sensor 33_. This `s4agri:EatingActivitySensor` made two measurements about the cow eating activity (i.e. the minutes a cow eats per hour).

<figure id="Figure_11">

<figure>

        <img data-docx-width="26.06cm" src="diagrams/image12.png" alt="Cow, eating activity sensor and measurement example"/>

        <img data-docx-width="26.06cm" src="diagrams/image12.png" alt="Cow, eating activity sensor and measurement example"/>

        <figcaption>Figure 11: Cow, eating activity sensor and measurement example</figcaption>

        <figcaption>Figure 11: Cow, eating activity sensor and measurement example</figcaption>

    </figure>

    </figure>

This clause shows an example of how to instantiate the SAREF4AGRI extension of SAREF to represent the deployment of some sensors and an example of measurement for the smart irrigation use case. This example is shown in Figure 12.

This clause shows an example of how to instantiate the SAREF4AGRI extension of SAREF to represent the deployment of some sensors and an example of measurement for the smart irrigation use case. This example is shown in Figure 12.

<figure id="Figure_12">

<figure>

        <img data-docx-width="25.83cm" src="diagrams/image13.png" alt="Smart Irrigation example"/>

        <img data-docx-width="25.83cm" src="diagrams/image13.png" alt="Smart Irrigation example"/>

        <figcaption>Figure 12: Smart Irrigation example</figcaption>

        <figcaption>Figure 12: Smart Irrigation example</figcaption>

    </figure>

    </figure>

* <a id="[i.3]">[i.3]</a>	ETSI TS 103 410-4 (V1.1.2) (2020-04): "SmartM2M; Extension to SAREF; Part 4: Smart Cities Domain".

* <a id="[i.3]">[i.3]</a>	ETSI TS 103 410-4 (V1.1.2) (2020-04): "SmartM2M; Extension to SAREF; Part 4: Smart Cities Domain".

* <a id="[i.4]">[i.4]</a>	Verhoosel J. and Spek J.: "Applying Ontologies in the Dairy Farming Domain for Big Data Analysis". Proceedings of the 1st Semantic Web Technologies for the Internet of Things (SWIT) 2016 workshop, co-located with 15th International Semantic Web Conference (ISWC 2016), Kobe, Japan, October 2016, pg. 91-100, CEUR.

* <a id="[i.4]">[i.4]</a>	Verhoosel J. and Spek J.: "Applying Ontologies in the Dairy Farming Domain for Big Data Analysis". Proceedings of the 1st Semantic Web Technologies for the Internet of Things (SWIT) 2016 workshop, co-located with 15th International Semantic Web Conference (ISWC 2016), Kobe, Japan, October 2016, pg. 91-100, CEUR.

!!! alert-info "NOTE:"

!!! alert alert-info "NOTE:"

    Available at [http://ceur-ws.org/Vol-1783/](http://ceur-ws.org/Vol-1783/).

    Available at [http://ceur-ws.org/Vol-1783/](http://ceur-ws.org/Vol-1783/).