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Model Management

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Duration

2000-2005

Description

Model Management is a powerful approach to generic metadata management that manipulates  models and mappings between models using high-level operators. It aims at simplifying the development of metadata-intensive applications, such as data integration, software engineering, website management, or network modeling applications. Such applications manipulate a variety of 

  • models (database schemas, XML schemas, UML / ER)diagrams, ontologies, etc.) and
  • mappings between models (SQL view definitions, XSLT transformations,   XML-to-relational shredding specifications, ER-to-SQL DDL mappings, etc.).  

Model Management is a powerful approach to generic metadata management not limited to a specific language or application domain.  Models and mappings are manipulated using high-level algebraic operators, such as Match, Merge, or Compose. These operators are applied to models and mappings as a whole rather than to their individual building blocks. This approach, which was proposed by Phil Bernstein et al., promises to make the programming of metadata-intensive applications substantially easier.

Some of our key contributions are:

  • Study of scenarios related to data warehousing to demonstrate the usefulness of model management (ER 2000)
  • Development of the first prototype implementation of a complete programming environment for model- management, called Rondo, and its use to solve several realistic metadata problems (SIGMOD 2003). An executable demo of Rondo is available for download. 

Related Panel:

Bernstein, P.A., Is Generic Data Management Feasible? Panel discussion, Proc. VLDB 2000, pp. 660-662

 

Project members

  • Prof. Dr. Erhard Rahm
  • Dr. Hong-Hai Do
  • Melnik, Sergey

Publikationen (22)

Dateien Cover Beschreibung Jahr
LEAPME: Learning-based Property Matching with Embeddings
Ayala, D. ; Hernández, I. ; Ruiz, D. ; Rahm, E.
Arxiv 2010.01951
2020 / 10
The Case for Holistic Data Integration
Rahm, E.
Proc. ADBIS, Invited keynote paper, Springer LNCS 9809
2016 / 9
A Clustering-based Approach For Large-scale Ontology Matching
Algergawy, A. ; Maßmann, S. ; Rahm, E.
Proc. ADBIS Conf. 2011, LNCS 6909, pp. 415-428
2011 / 9
Generic Schema Matching, Ten Years Later
Bernstein, P. ; Madhavan, J. ; Rahm, E.
PVLDB, 2011 (VLDB 10 Year Best Paper Award Paper)
2011 / 8
Matching Large Schemas: Approaches and Evaluation
Do, H. ; Rahm, E.
Information Systems, Volume 32, Issue 6, September 2007, Pages 857-885
2007
An Online Bibliography on Schema Evolution
Rahm, E. ; Bernstein, P.
Sigmod Record, Dec. 2006
2006
Schema Matching and Mapping-based Data Integration
Do, H.
Dissertation. Veröffentlich durch Verlag Dr. Müller (VDM), ISBN 3-86550-997-5,
2006
Supporting Executable Mappings in Model Management
Melnik, S. ; Halevy, A. ; Rahm, E.
Proc. SIGMOD 2005, Baltimore, June 2005
2005 / 6
Schema and ontology matching with COMA++
Aumüller, D. ; Do, H. ; Maßmann, S. ; Rahm, E.
SIGMOD Conference
2005 / 6
Generic Model Management: Concepts and Algorithms
Melnik, S.
Springer LNCS 2967
2004

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