Topics

The two-day conference provides an open forum to discuss the opportunities and challenges of a big scientific data ecosystem, and to explore best practices, standards, architectures and data infrastructures for fostering cross-disciplinary discovery and innovation.

Topics of interest include, but are not limited to:

• Paradigms for enhancing scientific discovery through big data
• Framework for helping the science and AI communities to work together
• Data cleansing and quality assurance of science data
• Data sharing and preservation policy
• Data management challenges posed by big scientific data
• Machine learning methods to facilitate/accelerate scientific discovery
• Streaming data, sensor networks and complex event processing
• Scientific workflow management
• Science platforms: (hardware/software) tools for data discovery and analysis from different angles
• Storage system for large scale scientific applications
• Cloud technology for big scientific applications
• Scientific data visualisation

Paper Submission

The online submission system is: https://easychair.org/conferences/?conf=bigsdm2018. Authors may submit to either the full paper or short paper track. Full papers should be between 10 to 12 pages in length, and short papers between 6 to 8 pages. All submissions must be written in English and conform to the Springer LNCS proceedings format(http://www.springer.com/cn/computer-science/lncs/conference-proceedings-guidelines). Accepted papers will be published in LNCS proceeding.