Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.04184 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910042771423232 |
|---|---|
| author | Vidal, Vânia Maria Ponte Pequeno, Valéria Magalhães Casanova, Marco Antonio Arruda, Narciso Brito, Carlos |
| author_facet | Vidal, Vânia Maria Ponte Pequeno, Valéria Magalhães Casanova, Marco Antonio Arruda, Narciso Brito, Carlos |
| contents | Enterprise knowledge graphs (EKGa) are a novel paradigm for consolidating and semantically integrating large numbers of heterogeneous data sources into a comprehensive dataspace. The main goal of an EKG is to provide a data layer that is semantically connected to enterprise data, so that applications can have integrated access to enterprise data sources through that semantic layer. To make legacy relational data sources accessible through the organization's knowledge graph, it is necessary to create an RDF view of the underlying relational data (RDB2RDF view). An RDB2RDF view can be materialized to improve query performance and data availability. However, a materialized RDB2RDF view must be continuously maintained to reflect updates over the relational database. This article proposes a formal framework for constructing the materialized data graph for an RDB2RDF view and for incrementally maintaining the view's data graph. The article also presents an architecture and algorithms for implementing the proposed framework. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_04184 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Publication and Maintenance of Relational Data in Enterprise Knowledge Graphs (Revised Version) Vidal, Vânia Maria Ponte Pequeno, Valéria Magalhães Casanova, Marco Antonio Arruda, Narciso Brito, Carlos Databases Enterprise knowledge graphs (EKGa) are a novel paradigm for consolidating and semantically integrating large numbers of heterogeneous data sources into a comprehensive dataspace. The main goal of an EKG is to provide a data layer that is semantically connected to enterprise data, so that applications can have integrated access to enterprise data sources through that semantic layer. To make legacy relational data sources accessible through the organization's knowledge graph, it is necessary to create an RDF view of the underlying relational data (RDB2RDF view). An RDB2RDF view can be materialized to improve query performance and data availability. However, a materialized RDB2RDF view must be continuously maintained to reflect updates over the relational database. This article proposes a formal framework for constructing the materialized data graph for an RDB2RDF view and for incrementally maintaining the view's data graph. The article also presents an architecture and algorithms for implementing the proposed framework. |
| title | Publication and Maintenance of Relational Data in Enterprise Knowledge Graphs (Revised Version) |
| topic | Databases |
| url | https://arxiv.org/abs/2603.04184 |