Abstract
Research in information systems interoperability is motivated by the ever-increasing heterogeneity of the computer world. New generations of applications, such as geographic information systems (GISs), have much more demands in comparison to possibilities of legacy information systems and traditional database technology. The popularity of GIS in governmental and municipality institutions induce increasing amounts of available information (Stoimenov, Ðordevic-Kajan, & Stojanovic, 2000). In a local community environment (city services, local offices, local telecom, public utilities, water and power supply services, etc.), different information systems deal with huge amounts of available information, where most data in databases are geo-referenced. GIS applications often have to process geo-data obtained from various geo-information communities. Also, information that exists in different spatial database may be useful for many other GIS applications. Numerous legacy systems should be coupled with GIS systems, which present additional difficulties in developing end-user applications.
TopBackground
Heterogeneity of Data Sources
The realization of interoperable information systems is a weighty process involving two main system characteristics: distributed data sources and their heterogeneity. Information systems heterogeneity may be considered as structural (schematic heterogeneity), semantic (data heterogeneity), and syntactic heterogeneity (database heterogeneity; Bishr, 1998). Syntactic heterogeneity means that various database systems use different query languages (SQL [structured query language], OQL, etc.). Structural heterogeneity means that different information systems store their data in different structures. Semantic heterogeneity considers the content of an information item and its meaning. Semantic conflicts among information systems occur whenever information systems do not use the same interpretation of the information. Stuckenschmidt, Wache, Vogele, and Vissar (2000) give an introduction to problems concerning the syntactic, structural, and semantic integration. This article also presents technologies for enabling interoperability.
Key Terms in this Chapter
Interoperability: The ability of two or more systems or components to exchange information and to use the information that has been exchanged.
Geographic Information System (GIS): A computerized system for managing data about spatially referenced objects. GISs differ from other types of information systems in that they manage huge quantities of data, require complex concepts to describe the geometry of objects, and specify complex topological relationships between them.
Semantic Interoperability: The ability of two or more computer systems to exchange information and have the meaning of that information accurately and automatically interpreted by the receiving system.
Ontological Commitments: Agreements to use the vocabulary in a consistent way for knowledge sharing.
Data Integration: The problem of combining data residing at different sources and providing the user with a unified view of these data.
Ontology: An ontology is a specification of a conceptualization. In both computer science and information science, an ontology is a data model that represents a domain and is used to reason about the objects in that domain and the relations between them.
Mediator: A software component of a knowledge-based system that is used to isolate problem solvers from the logistical issues associated with accessing the database. Mediator is as an intermediate abstraction layer between databases and applications that use them.
Semantic Heterogeneity: Semantic heterogeneity considers the content of an information item and its meaning. Semantic conflicts among information systems occur whenever information systems do not use the same interpretation of the information.
Wrapping/Wrapper: Wrapping a system is the process of defining and restricting access to a system through an abstract interface. A wrapper is a program that is specific to every data source. Wrapper extracts a set of tuples from the source file and performs translation in the data format. A wrapper for information sources accepts queries in a given format, converts them into one or more commands or subqueries understandable by the underlying information source, and transforms the native results into a format understood by the application.