Abstract
This paper summarizes our research & development activities in building a semantic data management platform for large enterprise data lakes, with a focus on the automotive domain. We demonstrate the use of ontology models to systematically represent, link, and search large amounts of automotive data. Such search capability is an important enabler for Hadoop-based big data analytics and machine learning. These findings are being transferred to a productive system in order to foster the advanced engineering and AI at Bosch Chassis Systems Control (CC), especially in the automated driving area.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Compton, M., et al.: The SSN ontology of the W3C semantic sensor network incubator group. J. Web Semant. 17, 25–32 (2012)
StarDog. http://www.stardog.com. Accessed 13 Mar 2019
Lebo, T., et al.: PROV-O: The PROV Ontology. W3C Recommendation (2013). http://www.w3.org/TR/prov-o/. Accessed 12 Mar 2019
Compton, M., et al.: Sensor data provenance: SSNO and PROV-O together at last. In: Proceedings of 7th International Workshop on Semantic Sensor Networks (SSN), ISWC, pp. 67–82 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Schmid, S., Henson, C., Tran, T. (2019). Using Knowledge Graphs to Search an Enterprise Data Lake. In: Hitzler, P., et al. The Semantic Web: ESWC 2019 Satellite Events. ESWC 2019. Lecture Notes in Computer Science(), vol 11762. Springer, Cham. https://doi.org/10.1007/978-3-030-32327-1_46
Download citation
DOI: https://doi.org/10.1007/978-3-030-32327-1_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32326-4
Online ISBN: 978-3-030-32327-1
eBook Packages: Computer ScienceComputer Science (R0)