Aris M. Ouksel

Semantic interoperability in global information systems

Internet, Web and distributed computing infrastructures continue to gain in popularity as a means of communication for organizations, groups and individuals alike. In such an environment, characterized by large distributed, autonomous, diverse, and dynamic information sources, access to relevant and accurate information is becoming increasingly complex. This complexity is exacerbated by the evolving system, semantic and structural heterogeneity of these potentially global, cross-disciplinary, multicultural and rich-media technologies. Clearly, solutions to these challenges require addressing directly a variety of interoperability issues.

Opportunistic resource exchange in inter-vehicle ad-hoc networks

In this paper we examine resource discovery in inter-vehicle ad-hoc networks in an urban area, where moving vehicles communicate with each other via short-range wireless transmission. Our focus is on real-time location-specific information. We explore an opportunistic approach to resource recovery, in which a vehicle obtains information about resources from encountered vehicles. The vehicle uses a spatio-temporal relevance function to sort the resources, and save only the most relevant ones. Our theoretical and experimental analysis indicates that the opportunistic exchange algorithm automatically limits the distribution of a resource to a bounded spatial area and to the duration for which the resource is of interest.

Emergent semantics principles and issues

Information and communication infrastructures underwent a rapid and extreme decentralization process over the past decade: From a world of statically and partially connected central servers rose an intricate web of millions of information sources loosely connecting one to another. Today, we expect to witness the extension of this revolution with the wide adoption of meta-data standards like RDF or OWL underpinning the creation of a semantic web. Again, we hope for global properties to emerge from a multiplicity of pair-wise, local interactions, resulting eventually in a self-stabilizing semantic infrastructure. This paper represents an effort to summarize the conditions under which this revolution would take place as well as an attempt to underline its main properties, limitations and possible applications.

Coordinating context building in heterogeneous information systems

We present an architecture to coordinate the construction of the context within which meaningful information between heterogeneous information systems can be exchanged. We call this coordinator SCOPES (Semantic Coordinator Over Parallel Exploration Spaces). A classification of semantic conflicts we proposed elsewhere is used to build and refine the context, by discovering the semantic mapping rules (inter-schema correspondence assertions) between corresponding elements of the communicating systems. A truth maintenance system is used to manage the multiple intermediate contexts. It provides a mechanism to infer or retract assertions on the basis of the knowledge acquired during the reconciliation process. This nonmonotonic technique is used in conjunction with the Dempster-Shafer theory of belief functions to model the likelihood of alternative contexts. Finally, we propose an algorithm which illustrates how the various components of the architecture interact with one another in order to build context.

Distributed databases and peer-to-peer databases: past and present

The need for large-scale data sharing between autonomous and possibly heterogeneous decentralized systems on the Web gave rise to the concept of P2P database systems. Decentralized databases are, however, not new. Whereas a definition for a P2P database system can be readily provided, a comparison with the more established decentralized models, commonly referred to as distributed, federated and multi-databases, is more likely to provide a better insight to this new P2P data management technology. Thus, in the paper, by distinguishing between db-centric and P2P-centric features, we examine features common to these database systems as well as other ad-hoc features that solely characterize P2P databases. We also provide a non-exhaustive taxonomy of the most prominent research efforts toward the realization of full-fledged P2P databases.

Ontologies are not the Panacea in Data Integration: A FlexibleCoordinator to Mediate Context Construction

Shared ontologies describe concepts and relationships to resolve semantic conflicts amongst users accessing multiple autonomous and heterogeneous information sources. We contend that while ontologies are useful in semantic reconciliation, they do not guarantee correct classification of semantic conflicts, nor do they provide the capability to handle evolving semantics or a mechanism to support a dynamic reconciliation process. Their limitations are illustrated through a conceptual analysis of several prominent examples used in heterogeneous database systems and in natural language processing. We view semantic reconciliation as a nonmonotonic query-dependent process that requires flexible interpretation of query context, and as a mechanism to coordinate knowledge elicitation while constructing the query context. We propose a system that is based on these characteristics, namely the SCOPES (Semantic Coordinator Over Parallel Exploration Spaces) system. SCOPES takes advantage of ontologies to constrain exploration of a remote database during the incremental discovery and refinement of the context within which a query can be answered. It uses an Assumption-based Truth Maintenance System (ATMS) to manage the multiple plausible contexts which coexist while the semantic reconciliation process is unfolding, and the Dempster-Shafer (DS) theory of belief to model the likelihood of these plausible contexts.

A Framework for a Scalable Agent Architecture of Cooperating Heterogeneous Knowledge Sources

Interoperability amongst heterogeneous information sources continues to pose enormous challenges to the database, AI and other communities. While significant progress has been achieved in system, syntactic, and structural/schematic interoperability, comprehensive solutions to semantic interoperability remain elusive. We present and motivate the conceptual framework underlying SCOPES (Semiotic/Semantic Coordination of Parallel Exploration Spaces), a scalable agent architecture designed to support interoperable, autonomous and heterogeneous knowledge sources. It is posited that the traditional approach to semantics is insufficient to account for a variety of misinterpretations in a realistic social world. Agents are viewed as existing in a social world (of beliefs, expectations, commitments, etc) constrained by pragmatics (intentions, communication, etc) and with particular semantics (meanings, propositions, validity, etc) and syntactics (formal structures, language, data, deduction, etc). We then concentrate on semantic interoperability and how this is handled in SCOPES. Semantic reconciliation is viewed as a non-monotonic query-dependent that requires flexible interpretation of query context, and as a mechanism to coordinate knowledge elicitation while constructing the query context. We elaborate on the specific concepts needed to build this context, and briefly discuss the SCOPES’ algorithm for context construction.

G-Grid: a class of scalable and self-organizing data structures for multi-dimensional querying and content routing in p2p networks

Peer-to-Peer (P2P) technologies promise to provide efficient distribution, sharing and management of resources, such as storage, processing, routing and other sundry service capabilities, over autonomous and heterogeneous peers. Yet, most current P2P systems only support rudimentary query and content routing over a single data attribute, such as the file-sharing applications popularized in Napster, Gnutella and so forth. Full-fledged applications in distributed data management and grid computing demand more complex functionality, including querying and content routing over multiple attributes. In this paper we present a class of scalable and self-organizing multi-dimensional distributed data structures able to efficiently perform range queries in totally decentralized dynamic P2P environments. These structures are not imposed a priori over the network of peers. Rather, they emerge from the independent interactions of autonomous peers. They are also adaptive to unanticipated changes in the network topology. This robustness property expands their range of usefulness to many application areas such as mobile ad-hoc networks.

Agents and peer-to-peer computing: a promising combination of paradigms

P2P personal information-sharing services will see explosive growth, reaching 35% of all online users by 2006. Once personal P2P applications are common and the infrastructure supports them, computing will change. Developers of Web-based applications will realize that adding P2P functionality makes their apps come alive -user communication is the secret sauce for enhancing client- server applications.

Tolerance of localization imprecision in efficiently managing mobile sensor databases

Query processing on mobile sensor networks requires efficient indexing and partitioning of the data space to support efficient routing as the network scales up. Building an index structure in an ad hoc manner requires two operations: localization to discover the sensors position; and assignment to each sensor of the appropriate data space partition. We propose a fully distributed, cost-effective scheme, which integrates localization, indexing and data space management for sensors. We show that without affecting the overall performance of routing and query processing, our localization scheme, which involves merely local interaction, is performed with significantly less message and time cost than traditional approaches.