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Front Neuroinform. 2014 Aug 26;8:71. doi: 10.3389/fninf.2014.00071. eCollection 2014.

Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools.

Author information

1
The Mind Research Network and LBERI Albuquerque, NM, USA.
2
The Mind Research Network and LBERI Albuquerque, NM, USA ; Department of Psychology, Georgia State University Atlanta, GA, USA.
3
The Mind Research Network and LBERI Albuquerque, NM, USA ; Department of Electrical and Computer Engineering, University of New Mexico Albuquerque, NM, USA.

Abstract

Neuroscientists increasingly need to work with big data in order to derive meaningful results in their field. Collecting, organizing and analyzing this data can be a major hurdle on the road to scientific discovery. This hurdle can be lowered using the same technologies that are currently revolutionizing the way that cultural and social media sites represent and share information with their users. Web application technologies and standards such as RESTful webservices, HTML5 and high-performance in-browser JavaScript engines are being utilized to vastly improve the way that the world accesses and shares information. The neuroscience community can also benefit tremendously from these technologies. We present here a web application that allows users to explore and request the complex datasets that need to be shared among the neuroimaging community. The COINS (Collaborative Informatics and Neuroimaging Suite) Data Exchange uses web application technologies to facilitate data sharing in three phases: Exploration, Request/Communication, and Download. This paper will focus on the first phase, and how intuitive exploration of large and complex datasets is achieved using a framework that centers around asynchronous client-server communication (AJAX) and also exposes a powerful API that can be utilized by other applications to explore available data. First opened to the neuroscience community in August 2012, the Data Exchange has already provided researchers with over 2500 GB of data.

KEYWORDS:

big data; data sharing; javascript; neuroinformatics; open neuroscience; query builder

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