Difference between revisions of "SOCR Events JSS 2015"

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==Overview==
 
==Overview==
The volume and diversity of biomedical data is exponentially increasing with Peta bytes of imaging and genetics data acquired annually. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and data analytic services. Experienced and novice data analysts demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data management, data interrogation, evidence-based biomedical inference, and reproducibility of findings. Novel mathematical algorithms, statistical analyses and computational tools are necessary to cope with this avalanche of data and hardware devices. This session will discuss aspects of Big Data modeling, software implementation, data analytics, high-dimensional visualization and training of skillful researchers.
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The volume and diversity of biomedical data is exponentially increasing with Peta bytes of imaging and genetics data acquired annually. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and data analytic services. Experienced and novice data analysts demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data management, data interrogation, evidence-based biomedical inference, and reproducibility of findings. Novel mathematical algorithms, statistical analyses and computational tools are necessary to cope with this avalanche of data and hardware devices. This session will discuss aspects of Big Data modeling, software implementation, data analytics, high-dimensional visualization and training of skillful researchers. The [[SOCR_Events_JSS_2015#Resources|Resources]] link at the end contains the complete papers/presentations in this session.
  
 
== Organizer==
 
== Organizer==
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* Slides/papers:
 
* Slides/papers:
 
** [http://wiki.socr.umich.edu/images/2/26/Dinov_BigDataChallenges_JSM_2015.pdf Dinov, Management, Modeling & Analytic Challenges of Big Biomedical Data (PDF)] and [http://www.socr.umich.edu/docs/uploads/Dinov_BigDataChallenges_JSM_2015.pptx PPTX/Slides]
 
** [http://wiki.socr.umich.edu/images/2/26/Dinov_BigDataChallenges_JSM_2015.pdf Dinov, Management, Modeling & Analytic Challenges of Big Biomedical Data (PDF)] and [http://www.socr.umich.edu/docs/uploads/Dinov_BigDataChallenges_JSM_2015.pptx PPTX/Slides]
 
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** [http://wiki.socr.umich.edu/images/3/37/Robinson_JSM2015_Espaliers.pdf Robinson, ESPALIERS: A visualization method for Big Data (PDF)] and [http://www.socr.umich.edu/docs/uploads/JSM2015-Espaliers.pptx PPTX/Slides]
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** [http://wiki.socr.umich.edu/images/0/03/Chung_TwinStudy-JSM-2015.08.06-re.pdf Chung, The computational challenges of constructing and visualizing large-scale brain networks (PDF)]
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** [http://wiki.socr.umich.edu/images/d/da/Madduri_JSM_2015.pdf Madduri, Big Data Management and Analysis Using Globus Services (PDF)]
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** [http://wiki.socr.umich.edu/images/2/23/Mozafari_JSM_Aug2015.pdf Mozafari, Large-scale Data Intensive Systems, Big Data, Interactive Data Processing (PDF)] and [http://www.socr.umich.edu/docs/uploads/Mozafari_JSM_Aug2015.pptx PPTX/Slides]
  
 
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{{translate|pageName=http://wiki.socr.umich.edu/index.php?title=SOCR_Events_JSS_2015}}
 
{{translate|pageName=http://wiki.socr.umich.edu/index.php?title=SOCR_Events_JSS_2015}}

Latest revision as of 17:23, 7 August 2015

SOCR News & Events: 2015 JSM Session on Big Data: Modeling, Tools, Analytics, and Training

Overview

The volume and diversity of biomedical data is exponentially increasing with Peta bytes of imaging and genetics data acquired annually. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and data analytic services. Experienced and novice data analysts demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data management, data interrogation, evidence-based biomedical inference, and reproducibility of findings. Novel mathematical algorithms, statistical analyses and computational tools are necessary to cope with this avalanche of data and hardware devices. This session will discuss aspects of Big Data modeling, software implementation, data analytics, high-dimensional visualization and training of skillful researchers. The Resources link at the end contains the complete papers/presentations in this session.

Organizer

Session Logistics

Organizer Name (Dinov) Organizer Email
Session ID#: 211347
Session Sponsor: Section on Statistical Computing
Session Type: Topic-Contributed

Speakers and Topics

Resources




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