Logica-TGD: Transforming Graph Databases Logically

Fuente: arXiv
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Hauptverfasser: Skvortsov, Evgeny, Xia, Yilin, Ludäscher, Bertram, Bowers, Shawn
Format: Preprint
Veröffentlicht: 2025
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author Skvortsov, Evgeny
Xia, Yilin
Ludäscher, Bertram
Bowers, Shawn
author_facet Skvortsov, Evgeny
Xia, Yilin
Ludäscher, Bertram
Bowers, Shawn
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2503_00568
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Logica-TGD: Transforming Graph Databases Logically
Skvortsov, Evgeny
Xia, Yilin
Ludäscher, Bertram
Bowers, Shawn
Databases
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.
title Logica-TGD: Transforming Graph Databases Logically
topic Databases
url https://arxiv.org/abs/2503.00568