a b s t r a c tAn ontology represents a consensus on the representation of the concepts and axioms of a given domain. This consensus is often reached through an iterative process, each iteration consisting in modifying the current version of the consensus. Furthermore, frequent and continuous changes are also occurring when the represented domain evolves or when new requirements have to be considered. Consequently, ontologies have to be adaptable to handle evolution, revision and refinement. However, this process is highly challenging as it is often difficult to understand all affected ontology parts when changes are performed. Thus, inconsistencies can occur in the ontology as the changes can introduce contradictory axioms. To address this issue, this paper presents a formal approach for evolving ontologies using Typed Graph Grammars. This method relies on the algebraic approach Simple PushOut (SPO) of graph transformations. It formalizes the ontology changes and proposes an a priori approach of inconsistencies resolution. The modified ontology does not need an explicit checking as an incorrect ontology version cannot actually be generated. To validate our proposal, an implementation is presented using the Attributed Graph Grammar (AGG) toolbox.

No abstract

Ontologies are often used for the meta-modelling of dynamic domains, therefore it is essential to represent and manage their changes and to adapt them to new requirements. Due to changes, an ontology may become invalid and non-interpretable. This paper proposes the use of the graph grammars to formalize and manage ontologies evolution. The objective is to present an a priori approach of inconsistencies resolutions to adapt the ontologies and preserve their consistency. A framework composed of different graph rewriting rules is proposed and presented using the AGG (Algebraic Graph Grammar) tool. As an application, the article considers the EventCCAlps ontology developed within the CCAlps European project.

Meta-modeling is raising more and more interest in the field of language engineering. While this approach is now well understood for defining abstract syntaxes, formally defining textual concrete syntaxes with meta-models is still a challenge. Textual concrete syntaxes are traditionally expressed with rules, conforming to EBNF-like grammars, which can be processed by compiler compilers to generate parsers. Unfortunately, these generated parsers produce concrete syntax trees, leaving a gap with the abstract syntax defined by meta-models, and further ad hoc hand-coding is required. In this paper we propose a new kind of specification for concrete syntaxes, which takes advantage of meta-models to generate fully operational tools (such as parsers or text generators). The principle is to map abstract syntaxes to Communicated by Prof. Oscar Nierstrasz.

In the last years, ontology modeling became popular and thousands of ontologies covering multiple fields of application are now available. However, as multiple ontologies might be available on the same or related domain, there is an urgent need for tools to compare, match, merge and assess ontologies. Ontology matching, which consists in aligning ontology, has been widely studied and benchmarks exist to evaluate the different matching methods. However, somewhat surprisingly, there are no significant benchmarks for merging ontologies, proving input ontologies and the resulting merged ontology. To fill this gap, we propose a benchmark for ontologies merging, which contains different ontologies types, for instance: taxonomies, lightweight ontologies, heavyweight ontologies and multilingual ontologies. We also show how the GROM tool (Graph Rewriting for Ontology Merging) can address the merging process and we evaluate it based on coverage, redundancy and coherence metrics. We performed experiments and show that the tool obtained good results in terms of redundancy and coherence.