The content discusses the concept of time-varying data structures, introducing categories of narratives as powerful tools for studying temporal graphs and other data structures. The approach offers advantages in consistency with existing theories and generalizability to various categories used in data analysis. The paper emphasizes the importance of relating narratives of different types and systematically connecting them. It also highlights the need for a formal treatment of time-varying data to make it explicit.
The author explores the methods of axioms and data in understanding underlying dynamics, focusing on empirical observations to extract meaningful insights from time-varying systems. The discussion extends to examples like temporal graph theory, emphasizing the connection between time-varying data and hidden dynamical systems.
Furthermore, the content delves into the distinction between temporal and static properties, highlighting challenges in temporalizing notions from traditional static mathematics. It proposes a systematic way to obtain temporal analogues of static properties for a comprehensive theory of temporal data.
The paper concludes by introducing categories of narratives as an object-agnostic theory for time-varying objects that satisfies key desiderata for a mature theory of temporal data. It discusses how standard ideas from temporal graph theory naturally arise within this general framework when instantiated on graphs.
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by Benj... om arxiv.org 02-29-2024
https://arxiv.org/pdf/2402.00206.pdfDiepere vragen