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Model Management

Research field Big Data & Model Management
Status completed

Working Group Model Management


The working group Model Management discusses research and applications of model management technologies. Model management aims at developing technologies and mechanisms to support the integration, merging, evolution, and matching of complex data models. This support is required for the management of complex, integrated, distributed, heterogeneous information systems. Basic concepts in model management are models, mappings and operators. Models (e.g. an XML Schema, a schema of a relational database, or an ontology in OWL) describe the structure of data. Mappings represent relationships between elements from different models. Operators are operations on models and mappings (e.g. merging & matching of models, composition of mapping).

The management of metadata is of particular importance for model management. Metadata is data about data and is becoming more and more important as distributed and heterogeneous information systems need to be integrated. Using a metadata-based approach in the design and implementation of an integrated information system increases the flexibility and adaptability of the system, as information about the structure of data models and their dependencies are not hidden in the source code of the system. Instead, this information is captured in semantically rich metadata models, which enable the (re)use of the information in various contexts. Furthermore, a semantically rich representation of data models supports the definition of model management operators.

The working group addresses the following topics in more detail.

Meta Database Systems

The ConceptBase system is a deductive, object-oriented meta database system. It is based on the conceptual modelling language O-Telos. The system is available free-of-charge for non-commercial purposes. Current work focuses on the improvement of the graphical user interface (in particular, the graphical editor), interfaces to other modelling languages (such as XML Schema or OWL) and other database systems, and ongoing improvement of the ConceptBase kernel system.

Formal Representation of Models and Mappings

A fundamental problem of model management is a formal representation of models and mappings between these models. The formal representation should enable the definition of operators in an efficient and correct way. Our current goal is to define a generic meta model that is able to represent data models in various modeling languages (such as SQL DDL, XML Schema, or OWL).

Schema Matching

Mappings between models are required for many operations in model management. The manual construction of such mappings can be a tedious task, if the models contain thousands of elements. Therefore, (semi-)automatic mechanisms are required to support the creation of mappings. We are currently developing a system for the matching of ontologies.

Quality-Oriented Data Integration

Within a company, data is managed in several systems with different data models and characteristics. However, an integrated view of the data is required to get a comprehensive overview of the state of the organization. This might also include the integration of external sources. In this context, the quality of the data in the various sources has also to be considered. Several sources might provide the same data but with different quality characteristics (e.g. correctness, accuracy, response time of the source). An algorithm for the quality-oriented data integration has been developed in this thesis. We currently plan an implementation of this algorithm using Semantic Web and Grid technologies (see below).

Semantic Web

The vision of the Semantic Web is to have semantic annotations of the data, which is available on the web. This supports the search and integration of the data, as the data can be located by their semantical description and not only by their syntactical representation (e.g. keyword based search). Data integration and data quality are also problems in this context. Grid and P2P systems can be seen as the underlying technologies which enable the implementation of distributed information systems based on the idea of the Semantic Web. Research in this field is currently done in the context of the EU IST project SEWASIE.

Joining the Working Group

If you are interested in joining the working group on Model Management, please contact Christoph Quix. Students can join the group as a student assistant (Hiwi) or do their bachelor/diploma/master thesis in this research area. Seminars and lab courses are planned for future terms.

Currently avalable topics for a bachelor/diploma/master thesis are listed below, the same for student research assistant (HiWi) job openings.


The results of this research have been integrated into the model management prototype system GeRoMeSuite that has been presented at VLDB '07.


Research staff



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Project Publications

Christoph Quix, Sandra Geisler, Rihan Hai, Sanchit Alekh

Ontology Matching for Patent Classification

12th International Workshop on Ontology Matching (OM-2017), co-located with the 16th International Semantic Web Conference (ISWC-2017), Vienna, Austria, October 21, 2017.

Christoph Quix, Rihan Hai

Metadata Extraction and Management in Data Lakes with GEMMS

Complex Systems Informatics and Modeling Quarterly, No. 9, pp. 67-83, 2016

Christoph Quix, Rihan Hai, Hongzhi Wang, Verikat N. Gudivada, Laure Berti

Proceedings of the 11th VLDB Workshop on Quality in Databases (QDB'16)

More publications…