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  Title:   BD2K Home Page | Data Science at NIH  
 
  Archival URL:  
http://eot.us.archive.org/eot/20170119113452/http://datascience.nih.gov/bd2k  
  Live URL:   http://datascience.nih.gov/bd2k  
  Coverage:   November 23, 2016 - January 19, 2017  
  Description:   Official website of Data science at NIH, harnessing Big Data to advance research in biomedical sciences coordinated by the NIH Scientific Data Council and the NIH Office of the Associate Director for Data Science (ADDS).  
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  Title:   Data Science at Scale  
 
  Archival URL:  
http://eot.us.archive.org/eot/20161118062009/http://datascience.lanl.gov/index.html  
  Live URL:   http://datascience.lanl.gov/index.html  
  Coverage:   November 18, 2016 - November 18, 2016  
  Description:   Los Alamos National Lab Data Science at Scale Team's Home Page. Extremely large datasets and extremely high-rate data streams are becoming increasingly common due to the operation of Moore's Law as applied to sensors, embedded computing, and traditional high-performance computing. Interactive analysis of these datasets is widely recognized as a new frontier at the interface of information science, mathematics, computer science, and computer engineering. Text searching on the web is an obvious example of a large dataset analysis problem; however, scientific and national security applications require far more sophisticated interactions with data than text searches. These applications represent the 'data to knowledge' challenge posed by extreme-scale datasets in, for example, astrophysics, biology, climate modeling, cyber security, earth sciences, energy security, materials science, nuclear and particle physics, smart networks, and situational awareness. In order to contribute effectively to LANL's overall national security mission, we need a strong capability in Data Science at Scale. This capability rests on robust and integrated efforts in data management and infrastructure, visualization and analysis, high-performance computational statistics, machine learning, uncertainty quantification, and information exploitation. The Data Science at Scale capability provides tools capable of making quantifiably accurate predictions for complex problems with the efficient use and collection of data and computing resources.  
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  Title:   NIST Data Science Evaluation Series | All evaluations  
 
  Archival URL:  
http://eot.us.archive.org/eot/20170125024954/http://datascience.nist.gov/  
  Live URL:   http://datascience.nist.gov/  
  Coverage:   November 23, 2016 - January 25, 2017  
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  Title:   Data Science at NIH |  
 
  Archival URL:  
http://eot.us.archive.org/eot/20161123024832/http://datascience.nih.gov/  
  Live URL:   http://datascience.nih.gov/  
  Coverage:   November 23, 2016 - November 23, 2016  
  Description:   Official website of Data science at NIH, harnessing Big Data to advance research in biomedical sciences coordinated by the NIH Scientific Data Council and the NIH Office of the Associate Director for Data Science (ADDS).  
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  Title:   Data Science at Scale  
 
  Archival URL:  
http://eot.us.archive.org/eot/20161118000126/http://datascience.lanl.gov/  
  Live URL:   http://datascience.lanl.gov/  
  Coverage:   November 18, 2016 - November 18, 2016  
  Description:   Los Alamos National Lab Data Science at Scale Team's Home Page. Extremely large datasets and extremely high-rate data streams are becoming increasingly common due to the operation of Moore's Law as applied to sensors, embedded computing, and traditional high-performance computing. Interactive analysis of these datasets is widely recognized as a new frontier at the interface of information science, mathematics, computer science, and computer engineering. Text searching on the web is an obvious example of a large dataset analysis problem; however, scientific and national security applications require far more sophisticated interactions with data than text searches. These applications represent the 'data to knowledge' challenge posed by extreme-scale datasets in, for example, astrophysics, biology, climate modeling, cyber security, earth sciences, energy security, materials science, nuclear and particle physics, smart networks, and situational awareness. In order to contribute effectively to LANL's overall national security mission, we need a strong capability in Data Science at Scale. This capability rests on robust and integrated efforts in data management and infrastructure, visualization and analysis, high-performance computational statistics, machine learning, uncertainty quantification, and information exploitation. The Data Science at Scale capability provides tools capable of making quantifiably accurate predictions for complex problems with the efficient use and collection of data and computing resources.  
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  Title:   Welcome to JPL's Center for Data Science and Technology — Center for Data Science and Technology  
 
  Archival URL:  
http://eot.us.archive.org/eot/20161118020705/http://datascience.jpl.nasa.gov/  
  Live URL:   http://datascience.jpl.nasa.gov/  
  Coverage:   November 18, 2016 - November 18, 2016  
  Description:   Cutting-edge research and development of the science of data, algorithms, software and its applications.