OpenKnowledge FP 6-027253 Comparison of Mapping Techniques

Matching has been recognized as a plausible solution for the semantic heterogeneity problem in many traditional applications, such as schema integration, ontology integration, data warehouses, data integration, and so on. Recently, there have emerged a line of new applications characterized by their dynamics, such as peer-to-peer systems, agents, web-services. In this deliverable we extend the notion of ontology matching, as it has been understood in traditional applications, to dynamic ontology matching. In particular, we examine real-world scenarios and collect the requirements they pose towards a plausible solution. We consider five general matching directions which we believe can appropriately address those requirements. These are: (i) approximate and partial ontology matching, (ii) interactive ontology matching, (iii) continuous ”design-time” ontology matching, (iv) community-driven ontology matching and (v) multi-ontology matching. We give an overview of state of the art matching systems as well as their evaluation principles from the dynamic ontology matching perspective. Finally, the key open issues and challenges towards a plausible dynamic ontology matching solution are discussed, thereby providing a vision for future activities. OpenKnowledge is a 3 year long STReP project financed under the European Commission’s 6th Framework Programme. See, http://www.openk.org/ for details.

[1]  Herbert B. Enderton,et al.  A mathematical introduction to logic , 1972 .

[2]  Editors , 1986, Brain Research Bulletin.

[3]  C. Batini,et al.  A comparative analysis of methodologies for database schema integration , 1986, CSUR.

[4]  James A. Larson,et al.  A Theory of Attribute Equivalence in Databases with Application to Schema Integration , 1989, IEEE Trans. Software Eng..

[5]  A. Sheth.  Federated database systems for managing distributed, heterogeneous, and autonomous databases , 1990, CSUR.

[6]  Joseph A. Goguen,et al.  Institutions: abstract model theory for specification and programming , 1992, JACM.

[7]  Douglas B. Lenat,et al.  CYC: a large-scale investment in knowledge infrastructure , 1995, CACM.

[8]  Tefko Saracevic,et al.  Evaluation of evaluation in information retrieval , 1995, SIGIR '95.

[9]  Vipul Kashyap,et al.  Observer: an approach for query processing in global information systems based on interoperation across pre-existing ontologies , 1996, Proceedings First IFCIS International Conference on Cooperative Information Systems.

[10]  Vipul Kashyap,et al.  Semantic and schematic similarities between database objects: a context-based approach , 1996, The VLDB Journal.

[11]  Richard Fikes,et al.  The Ontolingua Server: a tool for collaborative ontology construction , 1997, Int. J. Hum. Comput. Stud..

[12]  Jon Barwise,et al.  Information Flow: The Logic of Distributed Systems , 1997 .

[13]  Hinrich Schütze,et al.  Automatic Word Sense Discrimination , 1998, Comput. Linguistics.

[14]  Bernhard Ganter,et al.  Formal Concept Analysis: Mathematical Foundations , 1998 .

[15]  Viswanath Poosala,et al.  Aqua: A Fast Decision Support Systems Using Approximate Query Answers , 1999, VLDB.

[16]  Adam Pease,et al.  Towards a standard upper ontology , 2001, FOIS.

[17]  Erhard Rahm,et al.  A survey of approaches to automatic schema matching , 2001, The VLDB Journal.

[18]  Mark Handley,et al.  A scalable content-addressable network , 2001, SIGCOMM '01.

[19]  Erhard Rahm,et al.  Generic Schema Matching with Cupid , 2001, VLDB.

[20]  Mark A. Musen,et al.  Anchor-PROMPT: Using Non-Local Context for Semantic Matching , 2001, OIS@IJCAI.

[21]  Avigdor Gal,et al.  The Use of Machine-Generated Ontologies in Dynamic Information Seeking , 2001, CoopIS.

[22]  David R. Karger,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM '01.

[23]  Heiner Stuckenschmidt,et al.  Ontology-Based Integration of Information - A Survey of Existing Approaches , 2001, OIS@IJCAI.

[24]  Gary M. Hardegree,et al.  Algebraic Methods in Philosophical Logic , 2001 .

[25]  Erhard Rahm,et al.  Comparison of Schema Matching Evaluations , 2002, Web, Web-Services, and Database Systems.

[26]  Erhard Rahm,et al.  Similarity flooding: a versatile graph matching algorithm and its application to schema matching , 2002, Proceedings 18th International Conference on Data Engineering.

[27]  Heiner Stuckenschmidt.  Approximate Information Filtering with Multiple Classification Hierarchies , 2002, Int. J. Comput. Intell. Appl..

[28]  Fausto Giunchiglia,et al.  Making Peer Databases Interact - A Vision for an Architecture Supporting Data Coordination , 2002, CIA.

[29]  Erhard Rahm,et al.  COMA - A System for Flexible Combination of Schema Matching Approaches , 2002, VLDB.

[30]  Yang Wen.  Semantic integration of structured and semistructured data sources , 2002 .

[31]  Deborah L. McGuinness,et al.  Owl web ontology language guide , 2003 .

[32]  Fausto Giunchiglia,et al.  Semantic Matching: Algorithms and Implementation , 2007, J. Data Semant..

[33]  A. ADoefaa,et al.  ? ? ? ? f ? ? ? ? ? , 2003 .

[34]  Pedro M. Domingos,et al.  Learning to match ontologies on the Semantic Web , 2003, The VLDB Journal.

[35]  Yannis Kalfoglou,et al.  Centre for Intelligent Systems and Their Applications , 2006 .

[36]  José L. V. Mejino,et al.  A reference ontology for biomedical informatics: the Foundational Model of Anatomy , 2003, J. Biomed. Informatics.

[37]  M. Dzbor,et al.  Magpie - Towards a Semantic Web Browser , 2003, SEMWEB.

[38]  Hironori Mizuguchi,et al.  HUP-ML: Human Proteome Markup Language for Proteomics Database , 2003 .

[39]  Jeffrey F. Naughton,et al.  On schema matching with opaque column names and data values , 2003, SIGMOD '03.

[40]  Yannis Kalfoglou,et al.  Ontology mapping: the state of the art , 2003, The Knowledge Engineering Review.

[41]  Hong Yu,et al.  Extracting synonymous gene and protein terms from biological literature , 2003, ISMB.

[42]  Fiona McNeill.  Dynamic ontology refinement , 2003 .

[43]  Diego Calvanese,et al.  Logical foundations of peer-to-peer data integration , 2004, PODS '04.

[44]  Frank van Harmelen,et al.  Contextualizing ontologies , 2004, J. Web Semant..

[45]  York Sure-Vetter,et al.  Ontology Mapping - An Integrated Approach , 2004, ESWS.

[46]  H. Lan,et al.  SWRL : A semantic Web rule language combining OWL and ruleML , 2004 .

[47]  Fausto Giunchiglia,et al.  Element Level Semantic Matching , 2004 .

[48]  David Stuart Robertson,et al.  A Lightweight Coordination Calculus for Agent Systems , 2004, DALT.

[49]  Chris F. Taylor,et al.  A common open representation of mass spectrometry data and its application to proteomics research , 2004, Nature Biotechnology.

[50]  Fausto Giunchiglia,et al.  S-Match: an Algorithm and an Implementation of Semantic Matching , 2004, ESWS.

[51]  Jérôme Euzenat,et al.  Similarity-Based Ontology Alignment in OWL-Lite , 2004, ECAI.

[52]  Dan Suciu,et al.  The Piazza peer data management system , 2004, IEEE Transactions on Knowledge and Data Engineering.

[53]  Silvana Castano,et al.  Semantic Information Interoperability in Open Networked Systems , 2004, ICSNW.

[54]  Steffen Staab,et al.  QOM - Quick Ontology Mapping , 2004, GI Jahrestagung.

[55]  Natalya F. Noy,et al.  Semantic integration: a survey of ontology-based approaches , 2004, SGMD.

[56]  Dan Brickley,et al.  FOAF Vocabulary Specification , 2004 .

[57]  Dan Brickley,et al.  Rdf vocabulary description language 1.0 : Rdf schema , 2004 .

[58]  Jérôme Euzenat,et al.  An API for Ontology Alignment , 2004, SEMWEB.

[59]  Subbarao Kambhampati,et al.  Answering Imprecise Queries over Web Databases , 2005, VLDB.

[60]  Kevin Chen-Chuan Chang,et al.  Toward Large Scale Integration: Building a MetaQuerier over Databases on the Web , 2005, CIDR.

[61]  Alon Y. Halevy,et al.  Semantic Integration Research in the Database Community : A Brief Survey , 2005 .

[62]  Fausto Giunchiglia,et al.  Efficient Semantic Matching , 2005, ESWC.

[63]  Enrico Motta,et al.  AquaLog: An Ontology-Portable Question Answering System for the Semantic Web , 2005, ESWC.

[64]  Fausto Giunchiglia,et al.  Web Explanations for Semantic Heterogeneity Discovery , 2005, ESWC.

[65]  Fausto Giunchiglia,et al.  Semantic Schema Matching , 2005, OTM Conferences.

[66]  Yannis Kalfoglou,et al.  Progressive ontology alignment for meaning coordination: an information-theoretic foundation , 2005, AAMAS '05.

[67]  Avigdor Gal,et al.  Automatic Ontology Matching Using Application Semantics , 2005, AI Mag..

[68]  Steffen Staab,et al.  Bootstrapping ontology alignment methods with APFEL , 2005, WWW '05.

[69]  Jérôme Euzenat,et al.  A Survey of Schema-Based Matching Approaches , 2005, J. Data Semant..

[70]  Erhard Rahm,et al.  Schema and ontology matching with COMA++ , 2005, SIGMOD '05.

[71]  Fausto Giunchiglia,et al.  A Large Scale Taxonomy Mapping Evaluation , 2005, International Semantic Web Conference.

[72]  Heiner Stuckenschmidt,et al.  Introduction to the Ontology Alignment Evaluation 2005 , 2005, Integrating Ontologies.

[73]  Alan L. Rector,et al.  Web ontology segmentation: analysis, classification and use , 2006, WWW '06.

[74]  Pavel Shvaiko,et al.  Community-Driven Ontology Matching , 2006, ESWC.

[75]  Avigdor Gal,et al.  Managing Uncertainty in Schema Matching with Top-K Schema Mappings , 2006, J. Data Semant..

[76]  J. Euzenat,et al.  Integrated view and comparison of alignment semantics , 2006 .

[77]  Silvana Castano,et al.  Matching Ontologies in Open Networked Systems: Techniques and Applications , 2006, J. Data Semant..

[78]  Enrico Motta,et al.  PowerAqua: Fishing the Semantic Web , 2006, ESWC.

[79]  Fausto Giunchiglia,et al.  Discovering Missing Background Knowledge in Ontology Matching , 2006, ECAI.

[80]  Kevin Chen-Chuan Chang,et al.  Automatic complex schema matching across Web query interfaces: A correlation mining approach , 2006, TODS.

[81]  Aldo Gangemi,et al.  The GALEN CORE Model Schemata for Anatomy: Towards a Re-usable Application-Independent Model of Medical Concepts , 2008 .

[82]  Florian Schintke,et al.  Peer-to-Peer Computing , 2010, Euro-Par.