Vision Paper: Improving the Accessibility of Port Operations in Supply Chain Management using Graph Data Analysis
- In supply chain management of port operations querying and visualizing network data often requires complex joins, nested queries and predefined reporting templates, which can hinder exploratory analysis and decision-making. When relational databases become too rigid and cumbersome for transactional processing, we envision an alternative approach using graph data models, provided by transforming entities (e.g. containers, vessels, terminals) into nodes and their relationships (e.g. arrival, loading, handling) into edges. To investigate the potential benefits of transforming relational supply chain data into a graph-based model, we designed and implemented a structured approach that integrated data processing, transformation and performance analysis across both relational and graph databases.
| Author: | Mert Ayas, Frank Laarmann, Leif Meier, Katja Zeume |
|---|---|
| URN: | urn:nbn:de:hbz:1010-opus4-49066 |
| ISSN: | 2150-8097 |
| Parent Title (English): | Proceedings of Workshops at the 51st International Conference on Very Large Data Bases (VLDB 2025), London, United Kingdom - September 1-5, 2025. |
| Publisher: | VLDB Endowment |
| Document Type: | Conference Proceeding |
| Language: | English |
| Date of Publication (online): | 2025/09/05 |
| Year of first Publication: | 2025 |
| Publishing Institution: | Westfälische Hochschule Gelsenkirchen Bocholt Recklinghausen |
| Release Date: | 2026/01/07 |
| Tag: | Accessibility; Graph Data; NoSQL Databases; Supply Chain Management |
| Volume: | 2025 |
| Issue: | Vol. 14, No. 1 |
| Page Number: | 6 |
| Institutes: | Fachbereiche / Informatik und Kommunikation |
| Licence (German): | Creative Commons - Namensnennung - Nicht kommerziell - Keine Bearbeitung |



