Paolo Bouquet

C-OWL: contextualizing ontologies

Ontologies are shared models of a domain that encode a view which is common to a set of different parties. Contexts are local models that encode a partys subjective view of a domain. In this paper we show how ontologies can be contextualized, thus acquiring certain useful properties that a pure shared approach cannot provide. We say that an ontology is contextualized or, also, that it is a contextual ontology, when its contents are kept local, and therefore not shared with other ontologies, and mapped with the contents of other ontologies via explicit (context) mappings. The result is Context OWL (C-OWL), a language whose syntax and semantics have been obtained by extending the OWL syntax and semantics to allow for the representation of contextual ontologies.

Semantic coordination: a new approach and an application

Semantic coordination, namely the problem of finding an agreement on the meaning of heterogeneous semantic models, is one of the key issues in the development of the Semantic Web. In this paper, we propose a new algorithm for discovering semantic mappings across hierarchical classifications based on a new approach to semantic coordination. This approach shifts the problem of semantic coordination from the problem of computing linguistic or structural similarities (what most other proposed approaches do) to the problem of deducing relations between sets of logical formulae that represent the meaning of concepts belonging to different models. We show how to apply the approach and the algorithm to an interesting family of semantic models, namely hierarchical classifications, and present the results of preliminary tests on two types of hierarchical classifications, web directories and catalogs. Finally, we argue why this is a significant improvement on previous approaches.

Contextual reasoning distilled

In this paper we provide a foundation of a theory of contextual reasoning from the perspective of a theory of knowledge representation. Starting from the so-called metaphor of the box, we firstly show that the mechanisms of contextual reasoning proposed in the literature can be classified into three general forms (called localized reasoning, push and pop, and shifting). Secondly, we provide a justification of this classification, by showing that each mechanism corresponds to operating on a fundamental dimension along which context dependent representations may vary (namely, partiality, approximation and perspective). From the previous analysis, we distill two general principles of a logic of contextual reasoning. Finally, we show that these two principles can be adequately formalized in the framework of MultiContext Systems. In the last part of the paper, we provide a practical illustration of the ideas discussed in the paper by formalising a simple scenario, called the Magic Box problem.

Peer-Mediated Distributed Knowledge Management

Distributed Knowledge Management is an approach to knowledge management based on the principle that the multiplicity (and heterogeneity) of perspectives within complex organizations should not be viewed as an obstacle to knowledge exploitation, but rather as an opportunity that can foster innovation and creativity. Despite a wide agreement on this principle, most current KM systems are based on the idea that all perspectival aspects of knowledge (including the process of its creation) should be eliminated in favor of an objective and general representation in a sort of corporate knowledge base. In this paper we criticize this approach, and propose a peer-to-peer architecture (called KEx), which implements a distributed approach to Knowledge Managament in a quite straightforward way: (i) each peer (called a K-peer) provides all the services needed to create and organize “local” knowledge from an individual’s or a group’s perspective, and (ii) social structures and protocols of meaning negotiation are introduced to achieve semantic coordination among autonomous peers (e.g., when searching documents from other K-peers). A first version of the system, called KEx, is implemented as a knowledge exchange level on top of JXTA.

Peer-to-peer semantic coordination

Semantic coordination, namely the problem of finding an agreement on the meaning of heterogeneous schemas, is one of the key issues in the development of the Semantic Web. In this paper, we propose a method for discovering semantic mappings across hierarchical classifications (HCs) based on a new approach, which shifts the problem of semantic coordination from the problem of computing linguistic or structural similarities (what most other proposed approaches do) to the problem of deducing relations between sets of logical formulae that represent the meaning of concepts belonging to different schema. We show how to apply the approach and the algorithm to an interesting family of schemas, namely hierarchical classifications, and present the results of preliminary tests on two types of hierarchical classifications, web directories and catalogs. Finally, we argue why this is a significant improvement on previous approaches.

A SAT-based algorithm for context matching

The development of more and more complex distributed applications over large networks of computers has raised the problem of semantic interoperability across applications based on local and autonomous semantic schemas (e.g., concept hierarchies, taxonomies, ontologies). In this paper we propose to view each semantic schema as a context (in the sense defined in [1]), and propose an algorithm for automatically discovering relations across contexts (where relations are defined in the sense of [7]). The main feature of the algorithm is that the problem of finding relationships between contexts is encoded as a problem of logical satisfiability, and so the discovered mappings have a well-defined semantic. The algorithm we describe has been implemented as part of a peer-to-peer system for Distributed Knowledge Management, and tested on significant cases.

An entity name system (ENS) for the semantic web

In this paper, we argue that implementing the grand vision of the Semantic Web would greatly benefit from a service which can enable the reuse of globally unique URIs across semantic datasets produced in a fully decentralized and open environment. Such a service, which we call Entity Name System (ENS), stores pre-existing URIs and makes them available for reuse mainly - but not only - in Semantic Web contents and applications. The ENS will make the integration of semantic datasets much easier and faster, and will foster the development of a whole family of applications which will exploit the data level integration through global URIs for implementing smart semantic-based solutions.

On the Dimensions of Context Dependence: Partiality, Approximation, and Perspective

In this paper we propose to re-read the past work on formalizing context as the search for a logic of the relationships between partial, approximate, and perspectival theories of the world. The idea is the following. We start from a very abstract analysis of a context dependent representation into three basic elements. We briefly show that all the mechanisms of contextual reasoning that have been studied in the past fall into three abstract forms: expand/contract, push/pop, and shifting. Moreover we argue that each of the three forms of reasoning actually captures an operation on a different dimension of variation of a context dependent representation, partiality, approximation, and perspective. We show how these ideas are formalized in the framework of MultiContext Systems, and briefly illustrate some applications.

Bootstrapping semantics on the web: meaning elicitation from schemas

In most web sites, web-based applications (such as web portals, e-marketplaces, search engines), and in the file systems of personal computers, a wide variety of schemas (such as taxonomies, directory trees, thesauri, Entity-Relationship schemas, RDF Schemas) are published which (i) convey a clear meaning to humans (e.g. help in the navigation of large collections of documents), but (ii) convey only a small fraction (if any) of their meaning to machines, as their intended meaning is not formally/explicitly represented. In this paper we present a general methodology for automatically eliciting and representing the intended meaning of these structures, and for making this meaning available in domains like information integration and interoperability, web service discovery and composition, peer-to-peer knowledge management, and semantic browsers. We also present an implementation (called CtxMatch2) of how such a method can be used for semantic interoperability.

Querying the Web of Data: A Formal Approach

The increasing amount of interlinked RDF data has finally made available the necessary building blocks for the web of data. This in turns makes it possible (and interesting) to query such a collection of graphs as an open and decentralized knowledge base. However, despite the fact that there are already implementations of query answering algorithms for the web of data, there is no formal characterization of what a satisfactory answer is expected to be. In this paper, we propose a preliminary model for such an open collection of graphs which goes beyond the standard single-graph RDF semantics, describes three different ways in which a query can be answered, and characterizes them semantically in terms of three incremental restrictions on the relation between the domain of interpretation of each single component graph.