Big Data Harmonization for Intelligent Mobility: A Dynamic Toll-Charging Scenario

2017 ◽  
pp. 76-86
Author(s):  
Paulo Figueiras ◽  
Guilherme Guerreiro ◽  
Ruben Costa ◽  
Luka Bradesko ◽  
Nenad Stojanovic ◽  
...  
Keyword(s):  
Big Data ◽  
Data Harmonization

scholarly journals The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

2020 ◽  
Author(s):  
Sook-Lei Liew ◽  
Artemis Zavaliangos-Petropulu ◽  
Neda Jahanshad ◽  
Catherine E. Lang ◽  
Kathryn S. Hayward ◽  
...  
Keyword(s):  
Big Data ◽  
Working Group ◽  
Large Scale ◽  
Meta Analysis ◽  
Brain Magnetic Resonance Imaging ◽  
Stroke Recovery ◽  
Data Harmonization ◽  
Stroke Research ◽  
Brain And Behavior ◽  
Data Collaboration

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 1,800 stroke patients collected across 32 research sites and 10 countries around the world, comprising the largest multi-site retrospective stroke data collaboration to date. This paper outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multi-site stroke brain magnetic resonance imaging (MRI), behavioral and demographics data. Specifically, the processes for scalable data intake and pre-processing, multi-site data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

scholarly journals Big Data Harmonization-Data Loading and Data Storage

2019 ◽  
Vol 14 (20) ◽  
pp. 7731-7735
Author(s):  
Jigna Patel ◽  
Priyanka Sharma ◽  
Jitali Patel
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Harmonization ◽  
Data Loading

Approximate Incremental Big-Data Harmonization

2013 ◽  
Author(s):  
Puneet Agarwal ◽  
Gautam Shroff ◽  
Pankaj Malhotra
Keyword(s):  
Big Data ◽  
Data Harmonization

Find Out About 'Big Data' to Track Outcomes

ASHA Leader ◽  
2013 ◽  
Vol 18 (2) ◽  
pp. 59-59
Keyword(s):  
Big Data

Find Out About 'Big Data' to Track Outcomes

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

“Big Data in Psychology: Methods and Applications”

2017 ◽  
Vol 225 (3) ◽  
pp. 287-288
Keyword(s):  
Big Data

An associated conference will take place at ZPID – Leibniz Institute for Psychology Information in Trier, Germany, on June 7–9, 2018. For further details, see: http://bigdata2018.leibniz-psychology.org

When the Sample Is the Population: Big Data

PsycCRITIQUES ◽  
2014 ◽  
Vol 59 (2) ◽  
Author(s):  
David J. Pittenger
Keyword(s):  
Big Data
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