Institute for Geoinformatics (IFGI), Robert-Koch-Str. 26-28, 48149 Münster, Germany
Email: [email protected]
Geographic Information (GI) is characterized by cross domain applicability and the eco-nomic value of such information is linked to the wider usage of such information. With increas-ing efforts to provide GI data and processing through web based services, it has become essen-tial to have a closer look at the term interoperability, its various forms and the notion of seman-tic interoperability in particular. Recent research focus on these issues has helped to outline some major challenges of semantic interoperability of GI and approaches to solve these.
1. GI usage and Information communities
Users of GI come from different domains and are ever expanding. Traditionally such in-formation resided locally with the users and human interfacing provided the means to usage across domains. Such user domains could be at various levels ranging from industry verticals, cultural-linguistic communities or even departments in the same organization. Such domains can be characterized by the term information communities .
Access and usage of GI has undergone radical change in the last decade with a higher emphasis on co-operation and interchange for enterprise decision making and management. This does not just include geospatial data but also geospatial processing (i.e., query and analysis tasks pertaining to geospatial data). This has not only lead to efforts on format and interface standardi-zation efforts but also generated data sharing infrastructures such as Spatial Data Infrastructures (SDIs) and move towards open technology based architectures (OGC). All this can be argued to be interrelated to the trend of increased integration of the information communities.
It is also important to note that information communities enshrine their identity in the way it uses the GI. These may include the GI data components used, the processing that is ap-plied on such data components and the combinations of these. Thus while the cadastral mapping agency usually creates and maintains the land parcel maps, the utilities agencies create and main-tain the utility data in reference to the base map. Power or sewerage utilities can only refer to the base map and not alter it. Beyond this level one can also see how within a power utility company the operations department is allowed to create or alter the utility network data. Departments such as safety or marketing are only able to view this data besides make specialized analysis.
The view of information communities about GI data and processing also varies and this can be easily seen from the granularity at which the data is used. The notion of granularity can be explained on the basis of how people understand geospatial entities as constituted of other geo-spatial entities. For example the marketing department of the power utility company may visual-ize a building or apartment as a customer point the operations department would consider it as a region with access points (say the main switch, meter etc). It is more interesting to note that people belonging to two different information communities at the same time are able to switch between such granularity levels. The dual role of such people imbibes the mapping of what we call semantics of the GI between domains. The important point that can be noted in this example is that human services are employed to ensure information exchange and hence interoperability in some sense. Such human resources who have experience across domains are crucial for or-ganizations and cross department appointments or transfers are intentionally resorted to. This is applicable to non geographic information as well. However one can understand the scale of this problem when we discuss information access across diverse communities that access and share GI in SDIs.
Given such a situation, information communities increasingly look towards technologies to provide access to information. An infrastructure and syntax to provide access to information can be considered the base requirement before one could even start. SDIs and open architectures promoted by XML based data interchange can be considered to such starting steps. We discuss such steps towards what we can claim as interoperability in the next section.
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  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.
- Total Interoperability is assured
- Syntactic interoperability is assured
- Only semantic interoperability is assured
- 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  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  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” [https://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” [https://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 .
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.
- 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.
- 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.
- 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.
- 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.
- 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.
4. Where do we go from here
After having identified some of the challenges of semantic interoperability specially re-lated to GI we can now look at some of the approaches that are being taken to solve such prob-lems. Again, these are non-exhaustive but only indicative of some directions that are being taken.
Shared vocabularies and ontological mappings: Shared vocabularies form the basis of common ontological commitment and can be found in the knowledge tools of user do-mains/communities. Such domain ontologies can be used to align more specific applica-tion and task ontologies. Domain ontologies, in turn, are expected to be aligned to upper level ontologies. However from the abstract considerations about the distributed nature of knowledge as well as from observation of actual (human) ontology negotiation proc-esses it seems clear that globally agreed-upon conceptualizations are difficult to obtain. Hence there is an increased focus on ontological mappings based on a process of merging and aggregation.
Grounding in cognitive linguistics and measurement theory: The ontological negotia-tion process in humans discussed can be argued to be best understood from cognitive lin-guistics and principles there in such as embodied learning from image schemas . Such schemas provide precognitive basis for formation of human concepts and therefore allow grounding of concepts. Similarly, measurement theory  is also important in grounding of GI concepts world which are often based on measurements.
Semantic Reference Systems: The term grounding used above extends the metaphor of referencing things to some point on the ground. Semantic Reference Systems  is a similar idea of extending the notion of Spatial Reference Systems that is commonly used in maps and GIS, to the non spatial component of GI that needs semantic referencing.
Figure 4 Reference systems for interpreting geospatial information 
All interoperability problems are part of the greater system integration problem and one can only hope that in future technology would provide greater automation towards such integra-tion. This would allow the true extent of GI usage in human society from navigation services to emergency management.
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