Rabbani, K., Lissandrini, M., Bonifati, A., & Hose, K. (2024). Transforming RDF Graphs to Property Graphs using Standardized Schemas. In D. Arawal (Ed.), Proceedings of the ACM on Management of Data. ACM. https://doi.org/10.1145/3698817
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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Erschienen in:
Proceedings of the ACM on Management of Data
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Band:
2
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Datum (veröffentlicht):
20-Dez-2024
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Veranstaltungsname:
2024 ACM SIGMOD/PODS Conference
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Veranstaltungszeitraum:
9-Jun-2024 - 14-Jun-2024
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Veranstaltungsort:
Santiago, Chile
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Umfang:
25
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Verlag:
ACM, New York, NY, USA
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Peer Reviewed:
Ja
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Keywords:
Data exchange; Integrity checking; knowledge graphs; PG-Schema; SHACL; schema and data transformation
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Abstract:
Knowledge Graphs can be encoded using different data models. They are especially abundant using RDF and recently also as property graphs. While knowledge graphs in RDF adhere to the subject-predicate-object structure, property graphs utilize multi-labeled nodes and edges, featuring properties as key/value pairs. Both models are employed in various contexts, thus applications often require transforming data from one model to another. To enhance the interoperability of the two models, we present a novel technique, S3PG, to convert RDF knowledge graphs into property graphs exploiting two popular standards to express schema constraints, i.e., SHACL for RDF and PG-Schema for property graphs. S3PG is the first approach capable of transforming large knowledge graphs to property graphs while fully preserving information and semantics. We have evaluated S3PG on real-world large-scale graphs, showing that, while existing methods exhibit lossy transformations (causing a loss of up to 70% of query answers), S3PG consistently achieves 100% accuracy. Moreover, when considering evolving graphs, S3PG exhibits fully monotonic behavior and requires only a fraction of the time to incorporate changes compared to existing methods.
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Forschungsschwerpunkte:
Logic and Computation: 20% Information Systems Engineering: 80%