Knowledge Discovery from Earth Science Data

2014 ◽  
Author(s):  
Sangram Panigrahi ◽  
Kesari Verma ◽  
Priyanka Tripathi ◽  
Rika Sharma
Keyword(s):  
Knowledge Discovery ◽  
Earth Science ◽  
Science Data ◽  
Earth Science Data

scholarly journals Toward a Collective Agenda on AI for Earth Science Data Analysis

2021 ◽  
Vol 9 (2) ◽  
pp. 88-104
Author(s):  
Devis Tuia ◽  
Ribana Roscher ◽  
Jan Dirk Wegner ◽  
Nathan Jacobs ◽  
Xiaoxiang Zhu ◽  
...  
Keyword(s):  
Data Analysis ◽  
Earth Science ◽  
Science Data ◽  
Earth Science Data

scholarly journals Giovanni: The Bridge Between Data and Science

Eos ◽  
2017 ◽  
Author(s):  
Zhong Liu ◽  
James Acker
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Earth Science ◽  
Remote Sensing Data ◽  
Data Sets ◽  
Science Data ◽  
Web Based ◽  
Sensing Data ◽  
Daunting Task ◽  
Earth Science Data

Using satellite remote sensing data sets can be a daunting task. Giovanni, a Web-based tool, facilitates access, visualization, and exploration for many of NASA’s Earth science data sets.

scholarly journals Smart Environmental Data Infrastructures: Bridging the Gap between Earth Sciences and Citizens

2020 ◽  
Vol 10 (3) ◽  
pp. 856 ◽  
Author(s):  
José R. R. Viqueira ◽  
Sebastián Villarroya ◽  
David Mera ◽  
José A. Taboada
Keyword(s):  
Scientific Community ◽  
Earth Science ◽  
Scientific Information ◽  
Open Data ◽  
Data Access ◽  
Data Representation ◽  
Environmental Data ◽  
Science Data ◽  
Data Infrastructures ◽  
Earth Science Data

The monitoring and forecasting of environmental conditions is a task to which much effort and resources are devoted by the scientific community and relevant authorities. Representative examples arise in meteorology, oceanography, and environmental engineering. As a consequence, high volumes of data are generated, which include data generated by earth observation systems and different kinds of models. Specific data models, formats, vocabularies and data access infrastructures have been developed and are currently being used by the scientific community. Due to this, discovering, accessing and analyzing environmental datasets requires very specific skills, which is an important barrier for their reuse in many other application domains. This paper reviews earth science data representation and access standards and technologies, and identifies the main challenges to overcome in order to enable their integration in semantic open data infrastructures. This would allow non-scientific information technology practitioners to devise new end-user solutions for citizen problems in new application domains.

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