a linked data model for ish dataset

4.2 a linked data model for ish dataset

The development of our proposed LD model for semantically describing the ISH dataset has been performed by following an iterative approach based on the reuse of existing ontologies

1 http://www1.ncdc.noaa.gov/pub/data/ish/ish-format-document.pdf 2 ftp://ftp.ncdc.noaa.gov/pub/data/noaa/isd-history.txt

4.2 a linked data model for ish dataset 49

Table 4.2: Involved ontologies and namespaces in proposed linked data model

Prefix Namespace URI Description

got http://graphofthings.org/ontology/ Our domain extension ontology to describe meteorological concepts got-res http://graphofthings.org/resource/ The GoT resource namespace

sosa http://www.w3.org/ns/sosa/ Sensor, Observation, Sample, and Actuator (SOSA) ontology

ssn http://www.w3.org/ns/ssn/ Semantic Sensor Network ontology time http://www.w3.org/2006/time# Time Ontology in OWL

geo http://www.opengis.net/ont/geosparql# An RDF/OWL vocabulary for representing spatial information.

xsd http://www.w3.org/2001/XMLSchema# Schema namespace as defined by XSD.

rdf http://www.w3.org/1999/02/22-rdf-syntaxns#

This is the RDF Schema for the RDF vocabulary

terms in the RDF Namespace, defined in RDF 1.1 Concepts.

rdfs http://www.w3.org/2000/01/

rdf-schema#

RDF Schema provides a data modelling vocabulary for RDF data.

owl http://www.w3.org/2002/07/owl#

This ontology partially describes the built-in classes and properties that together form the basis of the RDF/XML syntax of OWL 2.

in the sensor network area. More specifically, we construct our Linked Sensor Data model by combining the usage of the SSN ontology [40],SOSAontology [93] in conjunction with the W3C Time ontology [87] and OGCGeoSPARQL [19]. Furthermore, we also extend the model with meteorological concepts in order to describe the ISH sensor data. List of involved ontologies and namespaces are presented in Table4.2. Details of using these reference ontologies, the domain extensions, and URI design principles are discussed in the following subsequent sections.

4.2.1 Semantic Properties

The semantic properties of sensor data provide not only the general description of sensor but also the connections between sensor data and the domain knowledge. Several semantic properties describe the sensor data can be listed here, such as platform, sensor type, observable property, a feature of interest, etc. We propose using the W3C recommended sensor ontologies, called SOSA/SSN [40,93] , to describe the semantic properties of sensor data. Figure4.2illustrates the modular structure consisting of SOSA/SSN as the central ontologies and connections with the domain ontologies. The description of the core classes and properties that are used to annotate the semantic properties of sensor data are described as follows.

• sosa:Sensor- Conceptually, a sensor is an abstract concept that implies a physical device, agent (including humans), or software (simulation) involved in, or implementing, a (sens-ing) procedure. A sensor can generate a sensing result and can be mounted on platforms, e.g., a modern smartphone hosts multiple sensors. In SOSA/SSN ontologies, the sosa:Sensor class lies at the central position from where any subdomain category of the sensor can be conceptualized.

• sosa:Platform- The sosa:Platform class is used to describe a complex system which carries at least one Sensor, Actuator, or sampling device to produce observations, actuations, or samples. A platform can also have geometric properties, i.e., placement, of sensors in relation to one another. A sensor attaches to the platform through sosa:isHostedBy property.

In our meteorological dataset, a sensor station is defined as a platform.

• sosa:Observation - Observation is the outcome of the sensing activity of a sensor.

Specifically, an observation involves a Sensor (sosa:madeBySensor) and yields a Result

50 a case study in modeling and publishing linked meteorological dataset

Figure 4.2: The core classes and properties of Linked Sensor Data model

got-res:Station/u4eu1epv0n_ish_1001499999 a got:WeatherStation;

Listing 4.1: Semantic modeling ofISHsensor.

(sosa:hasResult). While SOSA relies on QUDT [88] or other vocabularies to describe ob-servation results and their values, an additional datatype property is provided to handle the simple case that merely requires a typed literal, via the sosa:hasSimpleResult property.

• sosa:ObservableProperty- An observable property is defined as an observable quality of a thing, typically a feature of interest. Observable properties are similar to procedures or units of measure in the sense that they are singletons. One observable property will apply to many acts of observation, concerning different features of interest, at different times, or using different procedures or sensors, e.g.

• sosa:Result- This class describes a result of observation, actuation, or sampling, e.g., the value for an observed property of some feature of interest, such as 20 Celsius for the current temperature of the room.

• sosa:FeatureOfInterest- This is used to point to the observed feature of interest. A feature of interest can be any observed real-world phenomenon.

Listing4.1illustrates an example for describing the semantic properties of an ISH sensor and its observation data using SSN/SOSA ontologies. In this example, we also use some specific

4.2 a linked data model for ish dataset 51

domain concepts, such as got:WeatherStation and got:AirTemperatureProperty, which are defined in our meteorological domain extension ontology presented in the next section.

4.2.2 Meteorological Domain Extension for ISH Sensor Data

The SOSA/SSN ontologies represent sensor data at an abstract level, thus, in order to explicitly describe theISHdata, we need to extend the SOSA/SSN ontologies with the meteorological do-main concepts. In this regard, we first collect all the meteorological-related terms inISHdataset and define them as ontology classes and properties accordingly. The additional classes and properties are hosted in our separated domain extension ontology, namelyGoT. Figure4.3 illus-trates these additional meteorological concepts and how they are connected to the SOSA/SSN ontologies.

Figure 4.3: A SSN/SOSA meteorological domain extension model

As mentioned in Section4.1, theISHobservations are generated by a set of sensors deployed on a weather station. In our proposed data model, a weather station is defined as a sub-concept of the sosa:Platform class in SOSA ontology. Therefore, to conceptualize this concept, we de-fine the got:WeatherStation class linking to sosa:Platform as its subclass. After that, we extend the concept sosa:Sensor by means of a hierarchy of types of meteorological sensors used by ISH