A Three-Tier Matching Strategy for Predesign Schema Elements

Schema integration is a very complex task in which several schemata are merged into one global concept ual schema. Due to its complexity, computer-based appli cations and tools are needed that support and automate part s of the integration process. In our previous work, we have shown that schema integration on the predesign level allows fo r lower schema complexity, fewer conflicts and better end u ser feedback. In this paper, we focus on applied matchi ng strategies, which are a central element of any semi -automatic integration process. We propose a set of matching m ethods that are suitable for the predesign level and discu ss how they are intertwined and how their results regulate the integration process. As its main contribution, the paper offers an integration of previously presented methods and des cribes exemplary findings from the corresponding prototype. Keywordspredesign modeling; matching; integration

[1]  Peter Bellström.  View Integration in Conceptual Database Design : Problems, Approaches and Solutions , 2006 .

[2]  Laurian M. Chirica,et al.  The entity-relationship model: toward a unified view of data , 1975, SIGF.

[3]  Martha Palmer,et al.  Verb Semantics and Lexical Selection , 1994, ACL.

[4]  George A. Miller.  WordNet: A Lexical Database for English , 1992, HLT.

[5]  Yong Li,et al.  GeRoMeSuite: A System for Holistic Generic Model Management , 2007, VLDB.

[6]  Heinrich C. Mayr,et al.  Integration of Schemas on the Pre-Design Level Using the KCPM-Approach , 2006 .

[7]  Peter Bellström,et al.  A Rule-Based Approach for the Recognition of Similarities and Differences in the Integration of Structural Karlstad Enterprise Modeling Schemata , 2010, PoEM.

[8]  Christian Kop,et al.  OBSE – an approach to Ontology-based Software Engineering in the practice , 2007 .

[9]  Remigijus Gustas,et al.  Towards the Enterprise Engineering Approach for Information System Modelling Across Organisational and Technical Boundaries , 2003, ICEIS.

[10]  Tok Wang Ling,et al.  Resolving Schematic Discrepancy in the Integration of Entity-Relationship Schemas , 2004, ER.

[11]  Peter Bellström,et al.  Towards the Automation of Modeling Language Independent Schema Integration , 2009, 2009 International Conference on Information, Process, and Knowledge Management.

[12]  Peter Bellström,et al.  Recognition and Resolution of Linguistic Conflicts: The Core to a Successful View and Schema Integration , 2007 .

[13]  JÜRGEN VÖHRINGER,et al.  Using Linguistic Knowledge for Fine-tuning Ontologies in the Context of Requirements Engineering , 2010, Int. J. Comput. Linguistics Appl..

[14]  Carlo Strapparava,et al.  Corpus-based and Knowledge-based Measures of Text Semantic Similarity , 2006, AAAI.

[15]  Christian Kop,et al.  Designing a Study for Evaluating User Feedback on Predesign Models , 2009, ISD.

[16]  Luigi Palopoli,et al.  DIKE: a system supporting the semi‐automatic construction of cooperative information systems from heterogeneous databases , 2003, Softw. Pract. Exp..

[17]  Ted Pedersen,et al.  WordNet::Similarity - Measuring the Relatedness of Concepts , 2004, NAACL.

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

[19]  Ted Pedersen,et al.  An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet , 2002, CICLing.

[20]  Peter Bellström,et al.  On the Problem of Semantic Loss in View Integration , 2007, ISD.

[21]  Peter Bellström,et al.  Schema Integration: How to Integrate Static and Dynamic Database Schemata , 2010 .