Multi-level Networked Knowledge Base: DDL-Reasoning Sihem Klai 1 , Antoine Zimmermann 2 , and Med Tarek Khadir 1 1 Labged, Department of Computer Science, University of Badji Mokhtar of Annaba, Po-Box 12, 2300, Algeria {klai,khadir}@labged.net 2 Univ Lyon, MINES Saint-Étienne, CNRS, Laboratoire Hubert Curien UMR 5516, F-42023 Saint-Étienne, France antoine.zimmermann@emse.fr Abstract. This paper describes a new formalism based on multi-level networked knowledge (MLNK), a combination of different ontologies describing heteroge- neous and complementary domains aligned with semantic correspondences. On- tology alignments make explicit the correspondences between terms from differ- ent ontologies and must be taken into account in reasoning, where two explicit form of correspondences are given: mappings represent predefined relations such as subsumption, equivalence, or disjointness, that have a fixed semantics in all interpretations; as well as links that can relate complementary ontologies by in- troducing terms defined by experts, and their semantics varies according to inter- pretations. The proposed MLNK formalism can be transformed into a Distributed System capable of supporting DDL semantics. It permits to apply a contextual reasoning where ontologies and alignments by pairs of ontologies are developed in different and incompatible contexts. The semantic of the proposed formalism is extensively described along with an illustrative example. Keywords: Multi-Level Networked Knowledge Base; ontologies; ontology-alignment; DDL-reasoning. 1 Introduction In information systems, and more recently in the Semantic Web, a number of heteroge- neous, independently developed ontologies may be exploited in a single application that needs to share some knowledge. These ontologies are developed in different contexts and may well cover complementary domains. In order to overcome the heterogeneity problem, complementary knowledge may be introduced in order to describe correspondences between ontologies to be exploited. These correspondences, represent relations between entities (terms or formulas) belong- ing to different ontologies. This set of correspondences is named ontology alignment. In order to exploit, during reasoning, a number of heterogeneous ontologies as well as correspondences, a simple solution consists in viewing the ontology system as a unique global ontology. Therefore, each local ontology as well as each alignment, is then considered as a knowledge complement over a larger domain. Taking into account