• asdgsdfg

Interface Symposium 2013

»Interface Symposium 2013


Chapman University Symposium on Big Data and Analytics: 44th Symposium on the Interface of Computing Science and Statistics

Main Theme: Data Science Theory and Practice

Subthemes: Earth Systems Science Data and Health Care Data Systems

Download Full 2013 Program »


April 4-6, 2013 - Chapman University, California, USA
Sandhu Conference Center »
Campus Map & Parking » 


Chapman University and the Interface Foundation of North America cordially invite you to participate in the Chapman University Symposium on Big Data and Analytics: The 44th Symposium on the Interface of Computing Science and Statistics. The joint Chapman-Interface symposium welcomes scientific contribution dealing with Big Data to advance core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large and diverse data sets. Such data handling will accelerate scientific discovery and lead to new fields of inquiry that would otherwise not be possible.

+-About Interface 2013

On March 29, 2012, the Obama administration announced the Big Data Research and Development Initiative. A number of federal agencies including the National Science Foundation, the National Institutes of Health, the Department of Defense, the Department of Energy and the U.S. Geological Survey have committed substantial additional funds to Big Data projects. The White House press release described the goals of the Big Data Initiative “to advance the state-of-the-art core technologies needed to collect, store, preserve, manage, analyze, and share huge quantities of data; to harness these technologies to accelerate the pace of discovery in science and engineering; to strengthen our national security, and transform teaching and learning; and to expand the work force to needed to develop and use Big Data technologies.”

     The Interface Symposia series and statisticians, in general, have long recognized a need for large scale data collection and analysis. Recent interface symposia have focused on data-related themes such as: 1. Future of Statistical Computing: Internet Scale Data, Flexible Modeling, and Visualization; 2. Statistical, Machine Learning, and Visualization Algorithms; 3. Massive Data Sets and Streams; 4. Security and Infrastructure Protection; and 5. Frontiers of Data Mining and Bioinformatics. The 44th Symposium will continue this tradition with Big Data subthemes on Earth Systems Science and Healthcare Systems Challenges and how these subthemes will draw on and participate in the Big Data initiative. Interests include topics such as computational statistics, statistical software, exploratory data analysis, data mining, pattern recognition, scientific visualization and related fields with applications to Earth Systems Science and Healthcare Systems.

     It should be noted that the scale of what is considered Big Data has been increasing steadily. Kilobytes (103), megabytes (106), gigabytes (109), and terabytes (1012) by now are familiar to any researcher using modern computer resources. The Earth Observing System of NASA introduced serious consideration of petabytes (1015). Data collection systems looming on the horizon such as the Large Synoptic Survey Telescope (http://www.lsst.org) promise data on the scale of exabytes (1018). It is conceivable that data collection methods in the future may generate data sets of the scale of zettabytes (1021) and yottabytes (1024). The issue with big data is that computing power doubles every 18 months (Moore’s Law), I/O bandwidth increases about 10% every year, but the amount of data doubles every year. It is clear that conventional distributed systems such as those employed by Google, Facebook, and JPL (distributed active archive centers) must be expanded to include such new technologies as hadoop (http://www.cloudera.com/content/cloudera/en/why-cloudera/hadoop-and-big-data.html) and new analysis methods. The 44th Interface Symposium will focus on aspects of these Big Data issues.

     Earth Systems Science: The new computing technology became a key in the enabling global Earth-observing data for modeling and forecasting of Earth processes. Current Earth science research requires interdisciplinary infrastructures that can support knowledge integration of large data sets. The high performance computing unlocks new opportunities for exploiting "big data" by combining methods from both data exploration and data mining. Session areas of interest include:  data mining/fusion/assimilation, uncertainty analysis, modeling/forecasting with large datasets, sensor webs, and community frameworks. Science topics include handling big data addressing specific phenomena in one of the spheres namely, atmosphere, hydrosphere, biosphere, lithosphere and cryosphere.

     Does Big Data not present healthcare with tremendous opportunities and significant thinking to capture the opportunities? For goals, why not begin with the Institute of Medicine’s recent report on “Best Care at Lower Cost”? Should there not be funding incentives focusing on effective implementation between our Goals and Big-Data Analysis? Is not an engineering bridge which converts costly biomedical research into dependable Healthcare delivery conspicuous by its absence, from Genomics through Translational Medicine to Healthcare? For depth in thinking and acting, should we not accurately state actual quality of information explorations, correlation exploitations, relationship explanations, prediction extrapolations and Healthcare delivery evaluations -- instead of typically ambitious overstatements? Should we not support Healthcare complexity with information systems to manage our Big Data, processes to implement Healthcare delivery, planning to improve Healthcare, data mining to pose Healthcare questions, and finally statistical analysis to find major Healthcare answers? Is not the breadth of Healthcare illustrated by biomedical research, biomedical therapies, medical services, medical practice and Healthcare delivery? Should we not prepare for Big Data Analysis beforehand by actually defining stakeholder needs and reviewing stakeholder resources, as well as capitalizing on our Big Data conclusions afterwards by assessing conclusion quality in stakeholder environment and achieving maximum impacts in stakeholder environment?

+-Call for Participation

Chapman University and the Interface Foundation of North America cordially invite you to participate in the Chapman University Symposium on Big Data and Analytics: The 44th Symposium on the Interface of Computing Science and Statistics. The Interface Foundation is a non-profit educational corporation founded in 1987 to sponsor the conference and publish materials related to the interface including co-publishing the Journal of Computational and Graphical Statistics. For further information about the Interface Foundation of North America, visit the website: http://www.interfacesymposia.org.

     In the joint Chapman-Interface symposium, we will focus on modern problems related to big data and information overload and what we as professional data analysts can contribute to their solutions. Broadly speaking, the program will be organized around two complementary notions: (1) analysis of new data types brought to us by new technological capabilities, and (2) new methods and approaches enabled by modern technology. While these are interesting in their own right, perhaps the most interesting problem of all is how to bridge the gap between them. New data types demand new techniques, and new technology enables new techniques, but are we really using the latter in service of the former? Discipline scientists are often at the frontier of work with new data types, and we encourage them to share their problems and solutions with us whether or not those solutions appeal to traditional statistical or data mining methods.

     The joint Chapman-Interface symposium welcomes scientific contribution dealing with Big Data to advance core scientific and technological means of managing, analyzing, visualizing, and extracting useful information from large and diverse data sets. Such data handling will accelerate scientific discovery and lead to new fields of inquiry that would otherwise not be possible.

Our main theme this year will be on Data Science Theory and Practice

and our subthemes on Earth Systems Science Data and Health Care Data Systems.

Please visit our Session Details page for more information on the themes

Interested in Submitting? Contact Us Directly

+-Committees

Program Chair

Dr. Hesham M. El-Askary, Associate Prof. of Remote Sensing and Earth Systems Science, School of Earth and Environmental Sciences, Schmid College of Science and Technology, Director Graduate Programs Hazards, Global and Environmental change, and Computational Sciences, Center of Excellence in Earth Systems Modeling & Observations, Office: SC#209, email: elaskary@chapman.edu

Technical Program Committee  

Dr. Amy Braverman, Senior Statistician Jet Propulsion Laboratory, California Institute of Technology

Dr. Charles Ichoku, Senior Scientist: Climate and Radiation Laboratory at NASA Goddard Space Flight Center

Dr. David ScottNoah Harding Professor of Statistics Multivariate Data Analysis, Density Estimation, Computer Graphics, Rice University

Dr. David Marchette, Fellow of the AAAS American Association for the Advancement of Science (AAAS), the American Statistical Association (ASA)

Dr. Eric ChiPostdoctoral Fellow Department of Human Genetics, UCLA

Dr. Gennady VerkhivkerProfessor of Computational Biology, Schmid College of Science and Technology

Dr. Hadley WickhamAssistant Professor of Statistics, Dobelman Family Junior Chair Statistics, Rice University

Dr. Heiki HofmannAssociate Prof. Department of Statistics Iowa State University

Dr. Juergen SymanzikAssociate Professor of Mathematics and Statistics Utah State University, Co-Editor of Computational Statistics

Dr. James GentleProfessor of Computational Statistics, George Mason University

Dr. Jeffrey SolkaPrincipal Scientist in the US Government, Part time adjunct professor George Mason University

Dr. Kirk BorneProfessor of Astrophysics and Computational Science, George Mason University Data Scientist, Astrophysicist, Big Data Science Consultant, & Public Speaker

Dr. Richard LevineProfessor and Chair Department of Mathematics and Statistics San Diego State University, Editor, JCGS

Organizing Committee

Ashley Melton, Schmid College of Science & Technology

Carl Minor, Strategic Marketing and Communications

Christina Alexopoulos, Schmid College of Science & Technology

Douglas Dechow, Leatherby Libraries

Erika Curiel, Office of the Chancellor

Jennifer Hunnewell, Schmid College of Science & Technology

Michael Fahy, Schmid College of Science & Technology, representative of SIAM

Norma Landeros, Schmid College of Science & Technology 

Ross Loehner, Strategic Marketing and Communications

Sheri Ledbetter, Strategic Marketing and Communications

Susanna Branch, Office of the Chancellor

  • Featured
  • News
  • Events
  • page loading
    TODAY TOMORROW

    »

    TODAY TOMORROW

    »

    TODAY TOMORROW

    »

    View all News »
  • page loading
    TODAY TOMORROW

    »

    TODAY TOMORROW

    »

    TODAY TOMORROW

    »

    View all Events »

    interface


    Registration Fees

    General Admission
    Full Conference 

    $300 (early bird) $375 (at door)

    General Admission
    One day only 

    $175 (early bird and at door)

    Student with ID - $100

    Chapman Faculty and Staff - $50 

    Register Now


    Venue Information

    • Featured
    • News
    • Events