Reproducibility Data and Computational Archive for a Graph-Induced Bathymetric Topology Model

Reproducibility Data and Computational Archive for a Graph-Induced Bathymetric Topology Model This repository contains the computational data and reproducibility materials supporting the study of a graph-induced structural framework for quantitative analysis of bathymetric data. The archive contains the GMRT-derived bathymetric analysis data, structural-signature arrays, standardized structural features, the fixed 2,000-point sample used for pairwise analysis, structural-distance data, geographic-distance data, and scripts used to reproduce the reported computational figures. The structural representation is constructed from local bathymetric neighbourhood information and is used to quantify structural similarity independently of geographic separation. The archived sample indices and pairwise ordering are preserved so that structural and geographic distances correspond to the same set of point pairs. The package includes reproducibility scripts for the reported structural-distance and geographic-distance analyses, including Figures 5 and 6. The archive also contains the computational materials used in the broader analysis and visualization workflow. The study demonstrates the proposed framework on a GMRT-derived bathymetric region. Application to additional GMRT regions and independent multibeam datasets is required to assess transferability and broader applicability of the framework. This archive is intended to support transparent computational verification, reuse of the derived data products, and further development of structural approaches for quantitative bathymetric and seafloor analysis. Contents GMRT-derived bathymetric analysis data Five-dimensional structural-signature data used for the reproducibility analysis Standardization parameters Fixed 2,000-point sample indices Sample structural signatures Pairwise structural distances Geographic distance data Figure reproduction scripts README documentation The archived files should be used together with the associated manuscript to interpret the scientific methodology and results.