Dataset Generation Patterns for Evaluating Knowledge Graph Construction

Markus Schröder, Christian Jilek, Andreas Dengel

In: The Semantic Web: ESWC 2021 Satellite Events. Extended Semantic Web Conference (ESWC-2021) June 6-10 Hersonissos/Virtual Greece Springer 2021.


Confidentiality hinders the publication of authentic, labeled datasets of personal and enterprise data, although they could be useful for evaluating knowledge graph construction approaches in industrial scenarios. Therefore, our plan is to synthetically generate such data in a way that it appears as authentic as possible. Based on our assumption that knowledge workers have certain habits when they produce or manage data, generation patterns could be discovered which can be utilized by data generators to imitate real datasets. In this paper, we initially derived 11 distinct patterns found in real spreadsheets from industry and demonstrate a suitable generator called Data Sprout that is able to reproduce them. We describe how the generator produces spreadsheets in general and what altering effects the implemented patterns have.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence