A Data Mesh Adaptable Oil and Gas Ontology Based on Open Subsurface Data Universe (OSDU)

Neda Abolhassani, Ana Tudor, Sanjoy Paul

2023

Abstract

Incompatible models, heterogeneous data, and siloed data present challenges for the Oil & Gas industry. Knowledge graphs provide efficient consolidation, improved quality, and universal access to data, addressing these challenges. Developed by major global Oil & Gas and cloud organizations, the Open Subsurface Data Universe (OSDU) platform provides subsurface energy data ingestion, enrichment, and consumption services, as well as metadata storage, indexing, and search services. OSDU data supply chain aligns with the main concepts of the new trending data architecture, Data Mesh, such as federated data governance, decoupling data from applications, and domain specific data products. Data integration in subsurface data industry can be achieved by building a domain knowledge graph based on standard and enriched OSDU framework schemas. A knowledge graph-based solution begins with building a domain ontology. The purpose of this article is to introduce the OSDU ontology, which is publicly available on GitHub under the Apache 2.0 license. This paper discusses OSDU ontology design, development, applications, and evaluation.

Paper Citation

in Harvard Style

Abolhassani N., Tudor A. and Paul S. (2023). A Data Mesh Adaptable Oil and Gas Ontology Based on Open Subsurface Data Universe (OSDU). In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD; ISBN 978-989-758-671-2, SciTePress, pages 29-39. DOI: 10.5220/0012160000003598

in Bibtex Style

@conference{keod23,
author={Neda Abolhassani and Ana Tudor and Sanjoy Paul},
title={A Data Mesh Adaptable Oil and Gas Ontology Based on Open Subsurface Data Universe (OSDU)},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD},
year={2023},
pages={29-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012160000003598},
isbn={978-989-758-671-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD
TI - A Data Mesh Adaptable Oil and Gas Ontology Based on Open Subsurface Data Universe (OSDU)
SN - 978-989-758-671-2
AU - Abolhassani N.
AU - Tudor A.
AU - Paul S.
PY - 2023
SP - 29
EP - 39
DO - 10.5220/0012160000003598
PB - SciTePress