Space of Data through the Lens of Multilevel Graph

• URL: http://arxiv.org/abs/2503.23602v1
• Date: Sun, 30 Mar 2025 21:54:07 GMT
• Title: Space of Data through the Lens of Multilevel Graph
• Authors: Marco Caputo, Michele Russo, Emanuela Merelli,
• Abstract summary: This work seeks to tackle the inherent complexity of dataspaces by introducing a novel data structure.<n>We propose the concept of a multilevel graph, which is equipped with two fundamental operations: contraction and expansion of its topology.<n>We provide a comprehensive suite of methods for manipulating this graph structure, establishing a robust framework for data analysis.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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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