Results of the Ontology Alignment Evaluation Initiative 2009

euzenat2009cInternational audienceOntology matching consists of finding correspondences between on- tology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modal- ities, e.g., blind evaluation, open evaluation, consensus. OAEI-2009 builds over previous campaigns by having 5 tracks with 11 test cases followed by 16 partici- pants. This paper is an overall presentation of the OAEI 2009 campaign

Learning Subsumption Relations with CSR: A Classificationbased Method for the Alignment of Ontologies 1

Abstract. In this paper we propose the "Classification-Based Learning of Subsumption Relations for the Alignment of Ontologies " (CSR) method. Given a pair of concepts from two ontologies, the objective of CSR is to identify patterns of concepts ’ features (here, properties) that provide evidence for the subsumption relation among these concepts. This is achieved by means of a classification task using decision trees. For the learning of the decision trees, the proposed method generates training datasets from the source ontologies’, considering each ontology in isolation. The paper describes thoroughly the method, provides experimental results for computing subsumption relations over an extended version of the OAEI 2006 benchmarking series and discusses the potential of the method

Results of the Ontology Alignment Evaluation Initiative 2009

Ontology matching consists of finding correspondences between ontology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2009 builds over previous campaigns by having 5 tracks with 11 test cases followed by 16 participants. This paper is an overall presentation of the OAEI 2009 campaign

Results of the Ontology Alignment Evaluation Initiative 2009

euzenat2009cInternational audienceOntology matching consists of finding correspondences between on- tology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modal- ities, e.g., blind evaluation, open evaluation, consensus. OAEI-2009 builds over previous campaigns by having 5 tracks with 11 test cases followed by 16 partici- pants. This paper is an overall presentation of the OAEI 2009 campaign

Results of the ontology alignment evaluation initiative 2009

Abstract. Ontology matching consists of finding correspondences between ontology entities. OAEI campaigns aim at comparing ontology matching systems on precisely defined test cases. Test cases can use ontologies of different nature (from expressive OWL ontologies to simple directories) and use different modalities, e.g., blind evaluation, open evaluation, consensus. OAEI-2009 builds over previous campaigns by having 5 tracks with 11 test cases followed by 16 participants. This paper is an overall presentation of the OAEI 2009 campaign.

Co-designed Innovation and System for Resilient Exascale Computing in Europe: From Applications to Silicon (EuroEXA)

EuroEXA targets to provide the template for an upcoming exascale system by co-designing and implementing a petascale-level prototype with ground-breaking characteristics. To accomplish this, the project takes a holistic approach innovating both across the technology and the application/system software pillars. EuroEXA proposes a balanced architecture for compute and data-intensive applications, that builds on top of cost-efficient, modular-integration enabled by novel inter-die links, utilises a novel processing unit and embraces FPGA acceleration for computational, networking and storage operations. EuroEXA hardware designers work together with system software experts optimising the entire stack from language runtimes to low-level kernel drivers, and application developers that bring in a rich mix of key HPC applications from across climate/weather, physical/energy and life-science/bioinformatics domains to enable efficient system co-design and maximise the impact of the project