research pages

These pages contain a high level description of work that has been performed and obtained results. Some of this work may be discontinued. The detailed presentation of these results is in the cited papers.

Computer-mediated communication of structured knowledge

Goal and motivation

Our expectation is that it is useful to express formalised knowledge on a computer, not especially for the need of the computer, but for those of communication. We consider that, in future information systems, formalised knowledge will be massively exchanged. However, there is no reason why this knowledge should be expressed in the same format or by reference to the same vocabulary (or ontology). In order to interoperate, these representations will have to be matched and transformed.

Moreover, in this communication process computers can add value to their memory and medium role by formatting, filtering, classifying, consistency checking or generalising knowledge. These manipulations can be thought of as transformations and also have to be carried out so that they facilitate communication. We have developed the Alignment API and Alignment server. The current alignment API is being extended in order to offer its services to these applications (through agent communication protocols and web service invocation) and generating or processing the various transformations required by the applications.

We currently investigate three practical applications of such an infrastructure: (1) Matching context and needs in ambient computing requires such an infrastructure and would benefit sharing alignments on a large scale. (2) Annotated resource sharing in peer-to-peer architecture requires to query peers with heterogeneous ontologies. The alignment service is used there to infer, edit and store the alignments and provide appropriate mediators for processing the queries. (3) The ontology infrastructure of the semantic web is made of networked ontologies for which alignments can be the relations between ontologies.

Alignments, transformations and properties

Such an alignment infrastructure is the occasion to adapt Exmo's objective of providing an environment guaranteeing properties of the transformations. Instead of directly considering the properties of transformations, we can consider those of alignments and generate transformation (or any other kind of mediators) from these alignments.

For that purpose, we are currently studying how alignment properties can be obtained by construction from the type of algorithm used for computing the alignment. We are also developing alignment composition operators that will be inserted in the alignment service. We will have to study how the transformation generators preserve these properties (and what distortion is introduced by these generators).

In the meantime we continue to investigate some particular interesting problems in which we can still progress:

the design and development of efficient alignment algorithms (with University of Montréal);
the design of semantically grounded alternative to precision and recall for comparing ontology alignments;
the semantic (and rhetoric) adaptation of multimedia documents (with WAM).

On a longer term, we want to explore Ť semiotic ť properties, i.e., properties which concern the interpretation of the communicated representation by a numan user. This goal should require an analysis of the extra-semantic rules that govern the choice of subsets of models.

Anticipated applications are in transformation system engineering (in which the information system is seen as a transformation flow) and the semantic web infrastructure.

Content

After setting the applicative context:

Our programme is presented around six axes:

Content and knowledge representation is the kind of languages we manipulate,
Ontology alignments for representing correspondences between models:
Ontology matching aims at finding alignments that can be used as transformations:
Transformations and properties is the general framework that we promote and apply to various contexts:
Semantic interoperability focuses on semantic properties of transformations:
Distributed and dynamic aspects of matching and exploiting alignments:
Infrastructure presents the steps toward a safe tranformation infrastructure:
Computational semiology, on a longer term, considers the opportunity to transmit more context during the communication.

research pages

Computer-mediated communication of structured knowledge

Goal and motivation

Alignments, transformations and properties

Content

Further readings