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Logica-TGD: Transforming Graph Databases Logically

  • Evgeny Skvortsov
    ,
  • Yilin Xia
    ,
  • Bertram Ludäscher
    ,
Research Output: Contribution to journal Conference article Peer-review

Abstract

Graph transformations are a powerful computational model for manipulating complex networks, but handling temporal aspects and scalability remain significant challenges. We present a novel approach to implementing these transformations using Logica, an open-source logic programming language and system that operates on parallel databases like DuckDB and BigQuery. Leveraging the parallelism of these engines, our method enhances performance and accessibility, while also offering a practical way to handle time-varying graphs. We illustrate Logica's graph querying and transformation capabilities with several examples, including the computation of the well-founded solution to the classic “Win-Move” game, a declarative program for pathfinding in a dynamic graph, and the application of Logica to the collection of all current facts of Wikidata for taxonomic relations analysis. We argue that clear declarative syntax, built-in visualization and powerful supported engines make Logica a convenient tool for graph transformations.

Bibliographic Information

Output type

Research Output: Contribution to journal Conference article Peer-review

Original language

English

Journal (Volume, Issue Number)

CEUR Workshop Proceedings (Volume 3946)

Publication milestones

  • Published - 2025

Publication status

Published - 2025

ISSN

1613-0073

Publication IDs

  • Scopus: 105002697367