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SMCDC 2020 : Smoky Mountains Computational Sciences and Engineering Conference Data Challenge
SMCDC 2020 : Smoky Mountains Computational Sciences and Engineering Conference Data Challenge

SMCDC 2020 : Smoky Mountains Computational Sciences and Engineering Conference Data Challenge

Kingsport, Tennesse
Event Date: August 25, 2020 - August 27, 2020
Submission Deadline: July 27, 2020
Notification of Acceptance: August 07, 2020
Camera Ready Version Due: September 15, 2020




About

The 2020 Smoky Mountains Computational Sciences and Engineering Conference (SMC2020) is hosting its fourth annual Data Challenge. For this event, we have enlisted research scientists from across Oak Ridge National Laboratory (ORNL) to be data sponsors and help create data analytics challenges for eminent data sets at the laboratory. The role of our data sponsors is to provide a significant data set and formulate 3 to 5 challenge questions associated with the data set they provide. The challenge questions for each data set will cover multiple difficulty levels, with the first question in each challenge being suitable for a novice, and each question thereafter increasing in difficultly, with the series of questions ending with an advanced/expert level challenge question. These challenges are intended to draw scientists and researchers who may be at the beginning stages of incorporating data analytics into their workflow, to data analytics experts who are interested in applying novel data analytics techniques to data sets that are of national importance. This year there are 7 data challenges, and a team of up to 4 members may take on any of these challenges.


Call for Papers

This call is for papers detailing solutions to data analytics challenges based on eminent data sets at ORNL and beyond. These data sets come from scientific simulations and instruments in physical and chemical sciences, electron microscopy, bioinformatics, neutron sources, urban development, and other areas. The challenge questions for each data set will cover multiple difficulty levels. The first question in each challenge should be suitable for a novice, with each subsequent question increasing in difficulty and the series of questions ending with an advanced/expert level challenge question. This data challenge is part of the Smoky Mountains Computational Sciences and Engineering Conference (SMC2020). The current set of data challenges are available here: http://SMC-DATACHALLENGE.ORNL.GOV.

Scientists and researchers are encouraged to compete in these analytics challenges whether they are at the beginning stages of incorporating data analytics into their workflow or data analytics experts interested in applying novel data analytics techniques to data sets of national importance. Students and professionals will compete in separate categories.



Summary

SMCDC 2020 : Smoky Mountains Computational Sciences and Engineering Conference Data Challenge will take place in Kingsport, Tennesse. It’s a 3 days event starting on Aug 25, 2020 (Tuesday) and will be winded up on Aug 27, 2020 (Thursday).

SMCDC 2020 falls under the following areas: DATA ANALYTICS, MACHINE LEARNING, DATA SCIENCE, etc. Submissions for this Conference can be made by Jul 27, 2020. Authors can expect the result of submission by Aug 07, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Sep 15, 2020 to the official website of the Conference.

Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines.

Other Details of the SMCDC 2020

  • Short Name: SMCDC 2020
  • Full Name: Smoky Mountains Computational Sciences and Engineering Conference Data Challenge
  • Timing: 09:00 AM-06:00 PM (expected)
  • Fees: Check the official website of SMCDC 2020
  • Event Type: Conference
  • Website Link: http://smc-datachallenge.ornl.gov/
  • Location/Address: Kingsport, Tennesse


Credits and Sources

[1] SMCDC 2020 : Smoky Mountains Computational Sciences and Engineering Conference Data Challenge


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