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Semantic Interoperability of Geographic Information

2.2. Cost-benefit analysis of interoperability
Let us discuss the significant fact that since human services account for major cost and effort component in the usage of GI products (consider services as the product offered), it would be significant to include automation as a core component of service discovery and matchmaking. It has been reported [5] that for requesting a typical GI product more that 90 percent of the costs are in the area of human services such as training, consultancy, technical support and this is di-rectly related to issues of interoperability.

So what is the value addition proposition and why is it important to have interoperability. Let us assume that there are two services offered in the market place - one offers the road net-work data and the other offers route finding service. It is obvious that by integrating these two services customers can get a information service as ready to use GI product mentioned earlier. There are four scenarios possible in this regard.

1. Total Interoperability is assured
2. Syntactic interoperability is assured
3. Only semantic interoperability is assured
4. No Interoperability is assured

The level of human services involved gets higher as we go down the list. It also increases the chance of incorrect results, the cost of which cannot be realistically estimated. Thus the value add proposition would have to be on the lines of going up the order in the list and hence provide increased savings and larger customer base for the vendors. The consumers would look forward to higher reliability and freedom to choose. This is shown in the figure 2 below.


Figure 2 Value of Interoperablity
Lastly, one has to look at the investment required for such a proposition. Investments in standardization and implementation of standards are required for syntactic case. Use of Ontolo-gies or other conceptual modeling tools and investments in such knowledge based systems is the investment for the later case. We discuss these in our next section. It is important to note that in-vestments for semantic interoperability

3. Semantic interoperability
We have attempted to explain our notion of the term semantic interoperability which has been frequently used with different and often confusing connotations. A related explanation is given by Doer et al [6] who maintain that information integration at semantic levels consists of mapping between concepts of the two systems or communities. This naturally requires that con-cepts should be formally specified. Gruber [7] defines ontologies as “an explicit specification of a conceptualization” and thus such ontologies can form the basis of the mapping between con-cepts and hence semantic interoperability.

Ontologies have been used in the domain of knowledge representation and artificial intel-ligence from a long time. Conceptualizations that are behind the objects and artifacts that consti-tute the system are domain dependent. These conceptualizations that are expressed as ontologies usually specify objects and their relation to other objects. So how do ontologies help in ensuring semantic interoperability and do they really help? A flat answer to this question is currently there are some efforts to achieve semantic integration based on ontology alignment [8, 9]. Several challenges still exist, ranging from automation of the ontology mapping process, relating concepts on similarity and automated reasoning.

3.1. Web services and semantics
The W3C defines a web service as “software application identified by a URI, whose in-terfaces and binding are capable of being defined, described and discovered by XML artifacts and supports direct interactions with other software applications using XML based messages via Internet-based protocols” [http://www.w3.org/2002/ws/]. The emergence of Service oriented Ar-chitectures (SoA) is an important development by itself but more significantly the limelight on semantic interoperability due to the distributed nature of the SoA has brought major investments into the Semantic Web.

The Semantic Web is defined by the W3C as “an extension of the current Web in which information is given a well-defined meaning, better enabling computers and people to work in cooperation. It is the idea of having data on the Web defined and linked in a way that it can be used for more effective discovery, automation, integration and reuse across various applications. The Web can reach its full potential if it becomes a place where data can be processed by auto-mated tools as well as people” [http://www.w3.org/2001/sw/] Some of the important hurdles of the semantic web are in the context of

• Locating Services (Different terms used for service advertisements and requests)
• Negotiating contracts & communications (Different protocols used for agreements in transactions)
• Service invoking (constructing valid messages based on the published signature of the service)
• Understanding results of the invoked service
• Composing services (constructing composite service based on available services)

Use of ontologies in the semantic web has seen many developments as shown in the figure 3 be-low. The OWL-S and WSMF initiatives are some of the significant activities in this area al-though it has been pointed out that current offerings of the semantic web are not expressive and useful enough [10].


Figure 3 The Semantic Wave [Breners & Lee, 2003]
3.2. Semantics of GI
It is important to examine some of the uniqueness of GI in the context of semantics so that these can be taken care while dealing with GI web services and semantic interoperability problems there in.

1. GI usually deals with physical locations and entities which exist in the real world. Further, it is also true that such information is often based on measurement values in the real world rather than artificial values.
2. The semantics of geospatial information also has a temporal basis and hence a tem-perature, a real-estate price or a bathometry value is relevant to a particular time as it is to a place.
3. Social agreements on semantics based on naming of geographic features (physical features such as mountains and lakes as well as man made features such as countries) are also essential part of GI.
4. Semantics of these geographic features are also closely linked to the geospatial proc-esses that they participate in. The behavior of geospatial entities with respect to other entities in many ways defines its semantics. For example mountains are relatively dif-ficult to climb (for humans) as compared to hills. However such relations are rela-tively difficult to express in current taxonomy based approaches of ontological speci-fications.
5. GI semantics are often associated to vagueness in terms of the granularities at which they are defined. Non-monotonic reasoning capacity in humans usually allows such multiple levels of granularities and selection/amalgamation.

This non-exhaustive list of characteristics of GI does not restrict adaptation of approaches in the semantic web community but only provides further evaluation criteria for semantic inter-operability and focused areas of research.