To survive in the 21st century, enterprises need to collaborate. Collaboration at the enterprise-level presupposes the interoperability of the underlying information systems. Access to heterogeneous information sources must be provided transparently while maintaining their autonomy. Further, the availability of nearly unlimited information calls for efficient and precise information retrieval, which can be achieved by making the semantics embedded in information sources explicit. Solving the semantic interoperability problem becomes imperative to the success of information search and retrieval applications and enterprises that rely on them. Inspired by self-organizing systems found in biology, physics, and computing, the approach of emergent semantics has been proposed as a solution to the semantic interoperability problem. Emergent semantics refers to the bottom-up construction of interoperable systems, in which semantically related peers are discovered and linked together during the normal operation of the system. Individual information source providers will provide mappings (so-called semantic bridges) between their own local and semantically related foreign information sources. Emergent Semantics in a peer-to-peer (P2P) network is the lowest common knowledge, semantically relevant concepts, among all the peers of the network. Local mappings between peers with different knowledge representations, and their correctness, are prerequisites for the creation of emergent semantics. Yet, approaches to emergent semantics often fail to distinguish between permanent and transient mapping faults. This may result in erroneously labeling peers as having incompatible knowledge representations. In turn, this can further prevent such peers from interacting with other semantically related peers . This is because, in emergent semantics, peers use past interactions to determine which peers they will interact with in future collaborations. This chapter will explore the issue of semantic mapping faults. This issue has not received enough attention in the literature. Specifically, it will focus on the effect of non-permanent semantic mapping faults on both inclusiveness of semantic emergence and robustness of applications and systems that use semantic mappings. A fault-tolerant emergent semantics algorithm with the ability to resist transient semantic mapping faults is also provided. The contributions of this chapter are: (a) an analysis of the impact of the semantic mapping faults on the inclusiveness of semantic knowledge sharing in P2P systems, (b) a preliminary solution to the problems created by semantic mapping faults in P2P semantic knowledge sharing systems, and (c) a qualitative analysis of the causal links between fault causes and fault types. The rest of this chapter is organized as follows. Section II provides broad discussion and literature review about semantic interoperability problem among heterogeneous information source. Section III defines what we mean by a semantic mapping fault and the types of faults. Section IV lists sources of semantic mapping faults. Section V classifies temporal semantic mapping faults. Section VI describes the emergent semantics approach. Section VII presents an algorithm to eliminate the harmful effects of transient mapping faults on emergent semantics (fault-tolerant emergent semantics). Section VIII concludes the chapter and Section IX identifies directions for future work.
TopBackground
In today’s globally connected and digitalized world, the ability to exchange information, provide services and carry out business worldwide has become an essential requirement for many government agencies and departments, interest groups, businesses, etc. The need for transparent exchange of information and doing business on the global scale is faced with the semantic heterogeneous information representation problem among autonomous and distributed information source providers.
Existing information sources are scattered around the world. They are stored in repositories located in different government departments, research labs, universities, interest groups, enterprises, etc. The stored information is represented heterogeneously along different aspects. For example, data or information can be in XML filesb, relational tables, HTML files, RDFc documents etc. Further, when the same type of representation format is used for storing information, the information modeling, the structure and semantics of concepts used in the modeling may vary among different information source providers.
An example of semantic differences would be using different vocabularies to refer to the same physical or conceptual object by different information representations: one’s “zip code” is somebody else’s “area code”; or using the same vocabulary to refer to different conceptual or physical real life objects in different representations: a “terminal” for one is a computer monitor, but a “station” for somebody else.
In the distributed environment, information source providers are autonomous. In other words, information source providers have control on their local information sources. They could make changes, update, remove or restrict the access to their information sources. Consequently, in order for various businesses and service applications and systems to be able to cooperate and exchange information in the environment described above, they need to overcome the barrier of heterogeneity between semantic information representations.
In the sections below, we will delineate how a common ontology and emergent semantics help resolve the issue of semantic heterogeneity, and review existing literature on the different approaches for solving the problem.