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BTSD 2019 : Workshop on Big Data Tools and Use Cases for Innovative Scientific Discovery (BTSD) 2019 @IEEE BigData 2019 LA, USA

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Link: https://sites.google.com/view/btsd2019/home
 
When Dec 9, 2019 - Dec 9, 2019
Where LA, USA
Abstract Registration Due Sep 13, 2019
Submission Deadline Sep 27, 2019
Notification Due Nov 1, 2019
Final Version Due Dec 9, 2019
Categories    big data   data mining   data science   material science
 

Call For Papers

The First International Workshop on Big Data Tools, Methods, and Use Cases for Innovative Scientific Discovery (BTSD) 2019 in conjunction with 2019 IEEE International Conference on Big Data (IEEE BigData 2019)

December 9-12, 2019 @ Los Angeles, CA, USA

Call for Papers

Introduction to Workshop

Advances in big data technology, artificial intelligence, and machine learning have created so many success stories in a wide range of areas, especially in industry. These success stories have been motivating scientists, who study physics, chemistry, materials, medicine and many more, to explore a new pathway of utilizing big data tools for their scientific activities.

However, there are barriers to overcome. Most existing big data tools, systems, and methodologies have been developed without considering scientific purposes or scientists’ specific requirements. They are not originally developed for scientists who have no or little knowledge of programming or computer science. On the other hand, for computer scientists, understanding the domain problem is often very challenging due to the lack of enough background knowledge.

We expect that big data technologies can play a great role in contributing to scientific innovation in many ways. There are already a lot of ongoing scientific projects around the world that aim to discover novel hypotheses, analyze big multidimensional data which couldn’t be handled by manually, and reduce the time required by complex calculations via machine. This workshop intends to bring domain scientists and computer scientists together while exploring and extending opportunities in the development of big data tools, systems, and methodologies for scientific discovery, to share success stories and lessons learned, and discuss challenges, which if overcome would enable successful collaboration across different domains, especially domain scientists and computer/data scientists.

In this workshop, we discuss the following questions:
- What makes big data tools for scientists different from the existing tools?
- What specific needs and challenges do domain scientists face when they try to adopt big data tools?
- How can computer scientists and domain scientists communicate to define a feasible problem together?
- What are the barriers of using big data for scientific discovery and how do these barriers differ in different science domains?

Research Topics Included in the Workshop
Big data tools, systems, and methods related to, but not limited to:

- Scientific data processing
- Artificial intelligence/Deep neural networks/Machine learning
- Text mining/Graph mining
- Database/Query processing/Query Optimization
- Parallel computation/High-Performance Computing
- Visualization/User Interface/HCI
- Parallelization/Performance/Scalability
- High-Performance Computing ...
that facilitate innovation and discovery in a scientific domain, such as:
- Physics
- Chemistry
- Material science
- Mechanical engineering
- Nuclear engineering
- Biomedical science ...

Use cases, success stories, lessons learned in scientific discovery using big data tools, systems, and methods

Please submit a short paper (up to 4 pages IEEE 2-column format) or full paper (up to 8 page IEEE 2-column format) through the online submission system.

Important Dates
Sep 23, 2019 (Extended): Due date for abstract submission
Sep 27, 2019: Due date for short/full workshop papers submission
Nov 1, 2019: Notification of paper acceptance to authors
Nov 15, 2019: Camera-ready of accepted papers
Dec 9, 2019: Workshop

Workshop Primary Contact
Sangkeun (Matt) Lee, Computational Data Analytics Group, Computer Science and Mathematics Division, Oak Ridge National Laboratory, TN, USA. Tel: +1 865 574 8858 Email: btsd2019@gmail.com

Website
https://sites.google.com/view/btsd2019/home

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