Data Ingestion and Analysis Framework for Geoscience Data

Abstract

Big earth data analytics is an emerging field since environmental sciences are probably going to profit by its different systems supporting the handling of the enormous measure of earth observation data, gained and produced through perceptions. It additionally benefits by giving enormous stockpiling and registering capacities. Be that as it may, big earth data analytics requires explicitly planned instruments to show specificities as far as significance of the geospatial data, intricacy of handling, and wide heterogeneity of information models and arrangements [1]. Data ingestion and analysis framework for geoscience data is the study and implementation of extracting data on the system and processing it for change detection and to increase the interoperability with the help of analytical frameworks which aims at facilitating the understanding of the data in a systematic manner. In this paper, we address the challenges and opportunities in the climate data through the climate data toolbox for MATLAB [2] and how it can be beneficial to resolve various climate-change-related analytical difficulties.

Automating IoT Data Ingestion Enabling Visual Representation

“…In smart cities' environments, different data sources (e.g., Internet of things, IoT, devices, points of interest, POIs, and geographical information systems) can be used to support different objectives (e.g., improving life quality, providing suggestions to city users and operators, and assisting decision makers by means of predictions, simulations, and plans) [3]. One of the major challenges in this context is dealing with the data ingestion process [1, [4][5][6][7], addressing the import and pre-processing of complex multi-dimensional data (historical and real-time data with their metadata, which can be considered as static and real-time data, respectively). Acquired and derived data are stored to be further accessed and exploited for data analytics, dashboards, and visual analytics views [8].…”