Registro de resúmenes

Reunión Anual UGM 2023


SE16-3

 Resumen número: 0511  |  Resumen aceptado  
Presentación oral

Título:

NCDASHBOARD: SOFTWARE FOR EXPLORATORY ANALYSIS AND VISUALIZATION OF LARGE MULTI-DIMENSIONAL EARTH SCIENCE DATASETS

Autor:

Olmo Zavala Romero
Department of Scientific Computing, Florida State University
osz09@fsu.edu

Sesión:

SE16 Ciencias oceanográficas, atmosféricas y sociedad: ¿cómo nos comunicamos? Sesión especial

Resumen:

In the field of geoscience, a demand persists for modern, dynamic tools to streamline the analysis, validation, and visualization of complex numerical models and observational datasets. Existing software like NcView and OWGIS, while valuable, suffers from technological limitations that curtail dynamic functionality and sophisticated data analysis. This project heralds the initial developments of “NcDashboard,” a new exploratory analysis and visualization tool tailored mostly to ocean and atmospheric sciences. By leveraging cutting-edge web development and data science techniques, NcDashboard aims to provide unparalleled features such as synchronized animations, customized statistics, real-time composite field generation, and seamless raster and vector data integration. Built using Python and empowered by libraries like Dash, Plotly, xarray, GeoPandas, and GDAL,

the tool aspires to enhance scientific comprehension by marrying efficient multi-dimensional data handling with dynamic visualization. Even in its nascent stage, NcDashboard facilitates the creation of dynamic web interfaces that simplify the visualization and analysis of fields generated by numerical models, allowing for on-the-fly vertical

profiles and animations all through a single terminal command. In addition, the capability to construct web interfaces offers users the convenience of effortlessly sharing datasets with fellow researchers and the broader community. NcDashboard is poised to revolutionize geoscience research by boosting collaboration, reproducibility, and enabling the smooth exploration of vast and complex datasets.





Reunión Anual UGM 2023
29 de Octubre al 3 de Noviembre
Puerto Vallarta, Jalisco, México