用多层级图结构统一表达数据的抽象层次，支持动态缩放与分析。
Space of Data through the Lens of Multilevel Graph
- 提出多层级图结构，支持局部到全局的拓扑收缩与展开。
- 在真实梦境报告数据上验证了对非结构化数据的有效性。
- 适合需要灵活抽象的数据分析场景，如跨层次数据探索。
本文针对数据空间固有的复杂性，提出一种新型数据结构——多层级图，可表示从局部到全局多个抽象层次的数据集。该结构配备拓扑收缩与展开两种基本操作，旨在满足现有数据空间定义中对增量抽象与灵活性的要求。我们还构建了一套完整的图结构操作方法，形成稳健的数据分析框架。尽管实证验证集中于非结构化数据，其在结构化数据上的应用也具有内在可行性。通过一个基于真实梦境报告集合的案例，展示了初步结果。
原文摘要 · Abstract (English)
This work seeks to tackle the inherent complexity of dataspaces by introducing a novel data structure that can represent datasets across multiple levels of abstraction, ranging from local to global. We propose the concept of a multilevel graph, which is equipped with two fundamental operations: contraction and expansion of its topology. This multilevel graph is specifically designed to fulfil the requirements for incremental abstraction and flexibility, as outlined in existing definitions of dataspaces. Furthermore, we provide a comprehensive suite of methods for manipulating this graph structure, establishing a robust framework for data analysis. While its effectiveness has been empirically validated for unstructured data, its application to structured data is also inherently viable. Preliminary results are presented through a real-world scenario based on a collection of dream reports.
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