Performing Entity Relationship Model Extraction from Data and Schema Information as a Basis for Data Integration

Philipp Schmurr, Andreas Schmidt, Karl-Uwe Stucky, Wolfgang Suess, Veit Hagenmeyer

2024

Abstract

The goal of this work is to allow domain experts to properly perform data integration themselves and not to rely on external resources. This way the long-term data integration quality is not endangered and therefore cost for external resources can be saved. To achieve this, we propose a new approach that enables data integration based on entity-relationship (ER) models derived from arbitrary data sources. ER models are abstract and simply define all entities and relations needed for integration, which makes them easy to understand. Strategies to extract ER models from various standard data sources - relational databases, XML files and OWL data are presented and a concept on how to extend it to arbitrary other data sources is introduced. Furthermore, the extracted models are a foundation to perform graphical data integration into an ontology based model and, thus, contribute to a harmonized knowledge management in heterogeneous data and information environments. It can be summarized as a strategy to improve the interoperability of existing data according to the FAIR principles.

Paper Citation

in Harvard Style

Schmurr P., Schmidt A., Stucky K., Suess W. and Hagenmeyer V. (2024). Performing Entity Relationship Model Extraction from Data and Schema Information as a Basis for Data Integration. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS; ISBN 978-989-758-716-0, SciTePress, pages 316-322. DOI: 10.5220/0013012600003838

in Bibtex Style

@conference{kmis24,
author={Philipp Schmurr and Andreas Schmidt and Karl-Uwe Stucky and Wolfgang Suess and Veit Hagenmeyer},
title={Performing Entity Relationship Model Extraction from Data and Schema Information as a Basis for Data Integration},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS},
year={2024},
pages={316-322},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013012600003838},
isbn={978-989-758-716-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS
TI - Performing Entity Relationship Model Extraction from Data and Schema Information as a Basis for Data Integration
SN - 978-989-758-716-0
AU - Schmurr P.
AU - Schmidt A.
AU - Stucky K.
AU - Suess W.
AU - Hagenmeyer V.
PY - 2024
SP - 316
EP - 322
DO - 10.5220/0013012600003838
PB - SciTePress