Advanced Cartographic Techniques for Making Sense of Big Dynamic Data

Alexandre Sorokine,Steven Fernandez

doi:10.5194/ica-abs-1-345-2019

Abstract

Abstract. We have demonstrated application of advanced cartographic approaches to visualization of the U.S. electric grid. To address the challenges of high cognitive load of animated maps, we have applied an approach to combine data preprocessing, event detection, and several advanced cartographic techniques. In the future, the proposed methodology can be generalized to other types of dynamic big data.

Highlights

Since most of the big data records have geospatial and temporal reference there is a demand for developing cartographic techniques that would be effective at portraying big data streams for a variety of applications and visual environments
We discuss experimental cartographic techniques that we have developed for dynamic visualization of the data coming from the U.S electric grid
U.S electric grid is a sophisticated network system that consists of thousands of transformers, generators, and millions of loads interconnected through high voltage transmission lines and local distribution systems

Summary

Introduction

U.S electric grid is a sophisticated network system that consists of thousands of transformers, generators, and millions of loads interconnected through high voltage transmission lines and local distribution systems. We discuss experimental cartographic techniques that we have developed for dynamic visualization of the data coming from the U.S electric grid. The visualizations are intended for providing control center operators with up-to-date (down to a second) actionable information on the current state of the grid.

Results

Conclusion