Distributed Reasoning in a Peer-to-Peer Setting: Application to the Semantic Web

In a peer-to-peer inference system, each peer can reason locally but can also solicit some of its acquaintances, which are peers sharing part of its vocabulary. In this paper, we consider peer-to-peer inference systems in which the local theory of each peer is a set of propositional clauses defined upon a local vocabulary. An important characteristic of peer-to-peer inference systems is that the global theory (the union of all peer theories) is not known (as opposed to partition-based reasoning systems). The main contribution of this paper is to provide the first consequence finding algorithm in a peer-to-peer setting: DeCA. It is anytime and computes consequences gradually from the solicited peer to peers that are more and more distant. We exhibit a sufficient condition on the acquaintance graph of the peer-to-peer inference system for guaranteeing the completeness of this algorithm. Another important contribution is to apply this general distributed reasoning setting to the setting of the Semantic Web through the Somewhere semantic peer-to-peer data management system. The last contribution of this paper is to provide an experimental analysis of the scalability of the peer-to-peer infrastructure that we propose, on large networks of 1000 peers

Improving User Interaction on Ontology-based Peer Data Management Systems

The issue of user interaction for query formulation and execution has been investigated for distributed and dynamic environments, such as Peer Data Management System (PDMS). Many of these PDMS are semantic based and composed by data peers which export schemas that are represented by ontologies. In the literature we can find some proposed PDMS interfaces, but none of them addresses, in a general way, the needs of a PDMS for user interaction. In this work we propose a visual user query interface for ontology-based PDMS. It provides a simple and straightforward interaction with this type of system. It aims not only providing a natural visual query interface but also supporting a precise and direct manipulation of the data schemas for query generation

GLOBAL INDEX CONSTRUCTION FOR DATA INTEGRATION IN LARGE SCALE SYSTEM

Several scientific projects focused on the creation of Peer-to-Peer data management system. The main objective of these systems is to allow data sharing and integration among a large set of distributed, heterogeneous data sources. The emergence of large scale systems provides solutions and brings to surface new challenging unsolved problems, among which, we address the data integration problem. In order to address this problem, we propose a new data integration approach that allows the semantic integration of heterogeneous and distributed data sources in a Peer-to-Peer environment with high distribution and evolution support. In this paper, we provide an introduction to the approaches; problems and research issues encountered when dealing with data integration.We present our approach and describe the several methods for constructing a global index that is the core of our approach by using semantic similarities. We end our work by an application example

Mapping Composition Combining Schema and Data Level Heterogeneity in Peer Data Sharing Systems

Abstract: The mapping semantics that combines the schema-level and the data-level mappings is called bi-level mappings. Bi-level mappings enhance data sharing overcoming the limitations of the non-combined approaches. This paper presents an algorithm for composing two bi-level mappings by using tableaux. Composition of mappings between peers has several computational advantages in a peer data management system, such as yielding more efficient query translation, pruning redundant paths, and better query execution plans. We also present a distributed algorithm for computing direct mapping between two end peers of a series of peers connected by a chain of mappings

Composition and Inversion of Schema Mappings

In the recent years, a lot of attention has been paid to the development of solid foundations for the composition and inversion of schema mappings. In this paper, we review the proposals for the semantics of these crucial operators. For each of these proposals, we concentrate on the three following problems: the definition of the semantics of the operator, the language needed to express the operator, and the algorithmic issues associated to the problem of computing the operator. It should be pointed out that we primarily consider the formalization of schema mappings introduced in the work on data exchange. In particular, when studying the problem of computing the composition and inverse of a schema mapping, we will be mostly interested in computing these operators for mappings specified by source-to-target tuple-generating dependencies

Implementing Database Coordination in P2P Networks

We are interested in the interaction of databases in Peer-to-Peer (P2P) networks. In this paper we propose a new solution for P2P databases, that we call database coordination. We see coordination as managing semantic interdependencies among databases at runtime. We propose a data coordination model where the notions of Interest Groups and Acquaintances play the most crucial role. Interest groups support the formation of peers according to data models they have in common; and acquaintances allow for peers inter-operation. Finally, we present an architecture supporting database coordination and show how it is implemented on top of JXTA

SomeRDFS in the Semantic Web

The Semantic Web envisions a world-wide distributed architecture where computational resources will easily inter-operate to coordinate complex tasks such as query answering. Semantic marking up of web resources using ontologies is expected to provide the necessary glue for making this vision work. Using ontology languages, (communities of) users will build their own ontologies in order to describe their own data. Adding semantic mappings between those ontologies, in order to semantically relate the data to share, gives rise to the Semantic Web: data on the web that are annotated by ontologies networked together by mappings. In this vision, the Semantic Web is a huge semantic peer data management system. In this paper, we describe the SomeRDFS peer data management systems that promote a "simple is beautiful" vision of the Semantic Web based on data annotated by RDFS ontologies