text: In recent years, the amount of information on the Internet has increased exponentially developing great interest in selective information dissemination systems. The publish subscribe paradigm is particularly suited for designing systems for routing information and requests according to their content throughout wide-area network of brokers. Current publish subscribe systems use limited syntax-based content routing but since publishers and subscribers are anonymous and decoupled in time, space and location, often over wide-area network boundary, they do not necessarily speak the same language. Consequently, adding semantics to current publish subscribe systems is important. In this paper we identify and examine the issues in developing semantic-based content routing for publish subscribe broker networks.
  @cite_9: A method for integrating separately developed information resources that overcomes incompatibilities in syntax and semantics and permits the resources to be accessed and modified coherently is described. The method provides logical connectivity among the information resources via a semantic service layer that automates the maintenance of data integrity and provides an approximation of global data integration across systems. This layer is a fundamental part of the Carnot architecture, which provides tools for interoperability across global enterprises. >
  @cite_13: 
  @cite_12: Large organizations need to exchange information among many separately developed systems. In order for this exchange to be useful, the individual systems must agree on the meaning of their exchanged data. That is, the organization must ensure semantic interoperability . This paper provides a theory of semantic values as a unit of exchange that facilitates semantic interoperability betweeen heterogeneous information systems. We show how semantic values can either be stored explicitly or be defined by environments . A system architecture is presented that allows autonomous components to share semantic values. The key component in this architecture is called the context mediator , whose job is to identify and construct the semantic values being sent, to determine when the exchange is meaningful, and to convert the semantic values to the form required by the receiver. Our theory is then applied to the relational model. We provide an interpretation of standard SQL queries in which context conversions and manipulations are transparent to the user. We also introduce an extension of SQL, called Context-SQL (C-SQL), in which the context of a semantic value can be explicitly accessed and updated. Finally, we describe the implementation of a prototype context mediator for a relational C-SQL system.
  @cite_3: There has been an explosion in the types, availability and volume of data accessible in an information system, thanks to the World Wide Web (the Web) and related inter-networking technologies. In this environment, there is a critical need to replace or complement earlier database integration approaches and current browsing and keyword-based techniques with concept-based approaches. Ontologies are increasingly becoming accepted as an important part of any concept or semantics based solution, and there is increasing realization that any viable solution will need to support multiple ontologies that may be independently developed and managed. In particular, we consider the use of concepts from pre-existing real world domain ontologies for describing the content of the underlying data repositories. The most challenging issue in this approach is that of vocabulary sharing, which involves dealing with the use of different terms or concepts to describe similar information. In this paper, we describe the architecture, design and implementation of the OBSERVER system. Brokering across the domain ontologies is enabled by representing and utilizing interontology relationships such as (but not limited to) synonyms, hyponyms and hypernyms across terms in different ontologies. User queries are rewritten by using these relationships to obtain translations across ontologies. Well established metrics like precision and recall based on the extensions underlying the concepts are used to estimate the loss of information, if any.
summary: Some systems @cite_9 @cite_13 use inference engines to discover semantic relationships between data from ontology representations. Inference engines usually have specialized languages for expressing queries different from the language used to retrieve data, therefore user queries have to be either expressed in or translated into the language of the inference engine. The ontology is either global (i.e., domain independent) or domain-specific (i.e., only a single domain) ontology. Domain-specific ontologies are smaller and more commonly found than global ontologies because they are easier to specify. Additionally, there are systems that use mapping functions exclusively and do not have inference engines @cite_3 @cite_12 . In these systems, mapping functions serve the role of an inference engine.