1. Probabilistic Message Passing in Peer Data Management Systems Philippe Cudré-Mauroux, Karl Aberer EPFL Andras Feher, T.U. Darmstadt

2. Peer Data Management Systems Pairwise mappings –Query reformulation between two peers (schemas) Local mappings overcome global heterogeneity –Transitive closures on mapping operations 2001-12- 19T18:49:03Z 2001-12- 19T20:09:28Z date? 05/08/2004 Jan 1, 2005 article weather es:cDate  xap:CreateDate es:cDate  myRDF :Date myRDF: Date  xap:ModifyDate

3. Problem: Precision/Recall Tradeoff Semantic Query routing –To whom shall I forward a query posed against my local schema? Some (most) mappings will be (partially) faulty –Low expressive power of mappings samePropertyAs / sameClassAs subclassOf –Automatic schema alignment techniques –Different views on conceptualizations Local query resolution –Low recall Flooding (PDMS so far) –Low precision Standard deductive integration is not sufficient –Uncertainty on mappings and conceptualizations

4. Probabilistic Message Passing Link-based analysis of the PDMS - Automatically deriving quality measures for the mappings Decentralized computations - Analysis of loops and parallel paths - Iterative sum-product computations (loopy belief propagation) a priori information on mapping

5. Implemented System Schemas –Import from OWL (Web Ontology Language) Mappings –KnowledgeWeb Ontology Alignment API –Import from RDF/XML –Automated on-the-fly creation –Comparison to standard alignments  Automatic derivation of quality measures P(m=correct | {F}) for the mappings using iterative message-passing Reference Probabilistic Message-Passing in Peer-Data Management Systems Philippe Cudré-Mauroux, Karl Aberer, and Andras Feher International Conference on Data Engineering (ICDE 06).