BTSD 2019 : Workshop on Big Data Tools and Use Cases for Innovative Scientific Discovery (BTSD) 2019 @IEEE BigData 2019 LA, USA
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 scientistsÃ¢â‚¬â„¢ 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 couldnÃ¢â‚¬â„¢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
- High-Performance Computing ...
that facilitate innovation and discovery in a scientific domain, such as:
- 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.
Oct 11, 2019 (Extended): Due date for abstract submission
Oct 15, 2019 (Extended): 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: email@example.com