Climate Changes Prediction System Based on Weather Big Data Visualisation

2015 ◽  
pp. 75-86 ◽  
Author(s):  
Antoni Buszta ◽  
Jacek Mazurkiewicz
Keyword(s):  
Big Data ◽  
Climate Changes ◽  
Prediction System ◽  
Data Visualisation

Using Big Data to Improve Safety Performance: An Application of Process Mining to Enhance Data Visualisation

2021 ◽  
Vol 25 ◽  
pp. 100210
Author(s):  
Anastasiia Pika ◽  
Arthur H.M. ter Hofstede ◽  
Robert K. Perrons ◽  
Georg Grossmann ◽  
Markus Stumptner ◽  
...  
Keyword(s):  
Big Data ◽  
Process Mining ◽  
Safety Performance ◽  
Data Visualisation

Big Data Visualisation and Visual Analytics for Music Data Mining

2018 ◽  
Author(s):  
Katrina E. Barkwell ◽  
Alfredo Cuzzocrea ◽  
Carson K. Leung ◽  
Ashley A. Ocran ◽  
Jennifer M. Sanderson ◽  
...  
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Visual Analytics ◽  
Data Visualisation ◽  
Music Data Mining

Towards insight-driven sampling for big data visualisation

2019 ◽  
Vol 39 (7) ◽  
pp. 788-807 ◽  
Author(s):  
Moeti M. Masiane ◽  
Anne Driscoll ◽  
Wuchun Feng ◽  
John Wenskovitch ◽  
Chris North
Keyword(s):  
Big Data ◽  
Data Visualisation

scholarly journals Delay Prediction System for Large-Scale Railway Networks Based on Big Data Analytics

2016 ◽  
pp. 139-150 ◽  
Author(s):  
Luca Oneto ◽  
Emanuele Fumeo ◽  
Giorgio Clerico ◽  
Renzo Canepa ◽  
Federico Papa ◽  
...  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Large Scale ◽  
Big Data Analytics ◽  
Prediction System ◽  
Railway Networks ◽  
Delay Prediction

scholarly journals Big Data Visualisation

2021 ◽  
pp. 169-184
Author(s):  
Miguel Ángel Esbrí ◽  
Eva Klien ◽  
Karel Charvát ◽  
Christian Zinke-Wehlmann ◽  
Javier Hitado ◽  
...  
Keyword(s):  
Big Data ◽  
Research And Development ◽  
Data Visualization ◽  
Geospatial Data ◽  
Software Components ◽  
Data Visualisation ◽  
Big Data Visualization

AbstractIn this chapter, we introduce the topic of big data visualization with a focus on the challenges related to geospatial data. We present several efficient techniques to address these challenges. We then provide examples from the DataBio project of  visualisation solutions. These examples show that there are many technologies and software components available for  big data visualisation, but they also point to limitations and the need for further research and development.

scholarly journals Datamasser og sansemiljøer - Iscenesættelsen af big data mellem information, omslutning og overvågning

2016 ◽  
Vol 31 (59) ◽  
pp. 26
Author(s):  
Ulrik Schmidt
Keyword(s):  
Big Data ◽  
Dynamic Environments ◽  
Digital Culture ◽  
Massive Data ◽  
Data Sets ◽  
Data Visualisation ◽  
Massive Data Sets ◽  
Sensory Environment ◽  
Major Trend ◽  
Everyday Communication

”Data Masses and Sensory Environments” explores a major trend in current digital culture to visualise massive data sets in the form of abstract, dynamic environments. This ‘performative’ staging of big data manifests what we could think of as big data aesthetics proper because it gives the ‘big’ and ‘massive’ properties of big data a direct and perceptible visual expression. Drawing on several recent examples of big data visualisation, the article examines the different manifestations and aesthetic potential of such performative big data aesthetics. It is concluded that the performative ‘massification’ of big data in abstract environments has important implications for our everyday communication with and through data because it potentially generates a conflict between the comprehension of information and a more abstract and defocused ‘ambient’ sensation of being surrounded by a ubiquitous and all-encompassing sensory environment.

scholarly journals Hadoop Paradigm for Satellite Environmental Big Data Processing

2020 ◽  
Vol 11 (1) ◽  
pp. 23-47 ◽  
Author(s):  
Badr-Eddine Boudriki Semlali ◽  
Chaker El Amrani ◽  
Guadalupe Ortiz
Keyword(s):  
Big Data ◽  
Air Quality ◽  
Climate Changes ◽  
Environmental Data ◽  
Decision Makers ◽  
Huge Amount ◽  
Vertical Column ◽  
Data Architecture ◽  
Vertical Column Density ◽  
Major Factors

The important growth of industrial, transport, and agriculture activities, has not led only to the air quality and climate changes issues, but also to the increase of the potential natural disasters. The emission of harmful gases, particularly: the Vertical Column Density (VCD) of CO, SO2 and NOx, is one of the major factors causing the aforementioned environmental problems. Our research aims to contribute finding solution to this hazardous phenomenon, by using remote sensing (RS) techniques to monitor air quality which may help decision makers. However, RS data is not easy to manage, because of their huge amount, high complexity, variety, and velocity, Thus, our manuscript explains the different aspects of the used satellite data. Furthermore, this article has proven that RS data could be regarded as big data. Accordingly, we have adopted the Hadoop big data architecture and explained how to process efficiently RS environmental data.

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