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.

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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
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