Logica-TGD：逻辑化转换图数据库
Logica-TGD: Transforming Graph Databases Logically
AI总结：
针对图转换的时序处理与可扩展性挑战，提出基于开源逻辑编程语言Logica在并行数据库上实现图转换的方法，提升了性能并支持时变图，验证了其在多种图查询与转换任务中的便捷性。
摘要：
图转换是操纵复杂网络的强大计算模型，但处理时序方面和可扩展性仍是重大挑战。我们提出了一种使用Logica实现这些转换的新方法，Logica是一个开源逻辑编程语言和系统，可在DuckDB和BigQuery等并行数据库上运行。利用这些引擎的并行性，我们的方法提升了性能和可访问性，同时也提供了一种处理时变图的实用方法。我们用几个示例说明了Logica的图查询和转换能力，包括计算经典“Win-Move”博弈的良基解、动态图中寻路的声明式程序，以及将Logica应用于Wikidata所有当前事实的收集以进行分类关系分析。我们认为，清晰的声明式语法、内置可视化和强大的支持引擎使Logica成为图转换的便捷工具。
英文摘要：
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.
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