Материал готовится,

пожалуйста, возвращайтесь позднее

пожалуйста, возвращайтесь позднее

3

A Running Example

We will use a running example throughout this synopsis to illustrate the approaches for ontology- based discovery of data access and geoprocessing services.

Susan is visiting an unfamiliar city. She wants to use a mobile device (e.g. a mobile phone or PDA) to find the nearest place to eat that is still open. Her mobile device is equipped with some location

Figure 1: Service discovery during service composition. The properties of services that have already been discovered impose constraints on the queries for further services.

sensor (e.g. GPS), so that Susan knows her current location. She now wants to find services that provide information about ”places to eat” (including their location and opening hours) and a service for computing the distance from her current location. Both services could be combined into a service chain using a workflow service.

We assume that Susan is connected to an SDI and can use its catalogue service to perform her search. The SDI offers three WFS (whose provider is called John) that might be appropriate for Susan’s request:

WFS 1 provides information on Pub features, including their location, opening hours and the meals they serve. The location is given as a point with a geographic coordinate reference system: WGS84 (EPSG:4326).

WFS 2 provides information on Restaurants, again including their location, opening hours and the meals they serve. The location is given as a point with a projected coordinate reference system.

WFS 3 provides information on Pub features, including their location and the meals and drinks they serve.

Obviously, both WFS 1 and 2 contain the information (places to eat and their location and opening hours) required for answering Susan’s question. WFS 3, however, while providing ”places to eat”, fails to provide information on the opening hours and is therefore unsuitable.

The SDI also offers three services (which are also provided by John) for calculating the distances between point geometries :

Distance 1 returns the great circle or geodesic distance between two points on a sphere expressed in geographic coordinates , which equals the length of the great circle section on the spherical surface that is defined by the two points.

Distance 2 returns the 2D Euclidian distance between two points in a plane expressed in Carte- sian coordinates, which equals the length of a straight line between them.

Distance 3 returns the distance between two points in a specific road network. The network’s geometry is represented in a specific coordinate reference system, e.g. in WGS84 (Distance 3a) or Gauß-Kr ̈ger, zone 2 (Distance 3b). One can imagine such a network to be located on the associated sphere or plane. Formally, the network can be represented as a weighted graph, whose nodes represent the network’s intersections and whose edge weights are equal to the length of the curve connecting two intersections (measured in the space on which the network is located). The distance between two points in the network can then be computed based on the shortest path between the corresponding nodes in the graph, e.g. using Dijkstra’s algorithm (Cormen et al., 1990).

Figure 2: Possible combinations of data access and geoprocessing services for answering Susan’s question.

Which of John’s services is appropriate for answering Susan’s question depends on (i) the WFS she has chosen in the first step and (ii) the kind of distance she wants to compute (figure 2).

A Running Example

We will use a running example throughout this synopsis to illustrate the approaches for ontology- based discovery of data access and geoprocessing services.

Susan is visiting an unfamiliar city. She wants to use a mobile device (e.g. a mobile phone or PDA) to find the nearest place to eat that is still open. Her mobile device is equipped with some location

Figure 1: Service discovery during service composition. The properties of services that have already been discovered impose constraints on the queries for further services.

sensor (e.g. GPS), so that Susan knows her current location. She now wants to find services that provide information about ”places to eat” (including their location and opening hours) and a service for computing the distance from her current location. Both services could be combined into a service chain using a workflow service.

We assume that Susan is connected to an SDI and can use its catalogue service to perform her search. The SDI offers three WFS (whose provider is called John) that might be appropriate for Susan’s request:

WFS 1 provides information on Pub features, including their location, opening hours and the meals they serve. The location is given as a point with a geographic coordinate reference system: WGS84 (EPSG:4326).

WFS 2 provides information on Restaurants, again including their location, opening hours and the meals they serve. The location is given as a point with a projected coordinate reference system.

WFS 3 provides information on Pub features, including their location and the meals and drinks they serve.

Obviously, both WFS 1 and 2 contain the information (places to eat and their location and opening hours) required for answering Susan’s question. WFS 3, however, while providing ”places to eat”, fails to provide information on the opening hours and is therefore unsuitable.

The SDI also offers three services (which are also provided by John) for calculating the distances between point geometries :

Distance 1 returns the great circle or geodesic distance between two points on a sphere expressed in geographic coordinates , which equals the length of the great circle section on the spherical surface that is defined by the two points.

Distance 2 returns the 2D Euclidian distance between two points in a plane expressed in Carte- sian coordinates, which equals the length of a straight line between them.

Distance 3 returns the distance between two points in a specific road network. The network’s geometry is represented in a specific coordinate reference system, e.g. in WGS84 (Distance 3a) or Gauß-Kr ̈ger, zone 2 (Distance 3b). One can imagine such a network to be located on the associated sphere or plane. Formally, the network can be represented as a weighted graph, whose nodes represent the network’s intersections and whose edge weights are equal to the length of the curve connecting two intersections (measured in the space on which the network is located). The distance between two points in the network can then be computed based on the shortest path between the corresponding nodes in the graph, e.g. using Dijkstra’s algorithm (Cormen et al., 1990).

Figure 2: Possible combinations of data access and geoprocessing services for answering Susan’s question.

Which of John’s services is appropriate for answering Susan’s question depends on (i) the WFS she has chosen in the first step and (ii) the kind of distance she wants to compute (figure 2).

Загрузка...

Выбрать следующее задание

Ты добавил

Выбрать следующее задание

Ты добавил