ICDS 2015 - Second International Conference on Data Science (ICDS)

Second International Conference on Data Science (ICDS) will be held in Sydney, Australia, ON AUGUST 8-9, 2015 in conjunction with the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 10-13, Hilton, Sydney.
The explosion of digital data created by mobile sensors, social media, surveillance, medical imaging, smart grids and the like?combined with new tools for analyzing it all?has brought us a Big Data era. We are facing the great challenges: how to deal with data which is more than we could actually understand and absorb and how to make efficient use of the huge volume of data? From both scientific and practical perspectives, research on "Data Science" goes beyond the contents of Big Data. Data Science can be generally regarded as an interdisciplinary field of using mathematics, statistics, databases, data mining, high-performance computing, knowledge management and virtualization to discover knowledge from data. It should have its own scientific contents, such as axioms, laws and rules, which are fundamentally important for experts in different fields to explore their own interests from data.
The "International symposium/workshop on Dataology and Data Science" has been a platform for researchers from data and some practitioners from industry and government to share their ideas, research results and experiences on studying of data. From 2010 to 2013, it has been annually held in China where more than 300 scholars and industrial professionals from Australia, Canada, China, Japan, UK and USA attended. In order to further expand the preliminary findings and exchanges on this platform, the First International Conference on Data Science (ICDS 2014) was held at the Chinese Academy of Sciences, Beijing.
The second International Conference on Data Science (ICDS 2015) will be held on August 8-9, 2015, by the QCIS Research Centre, University of Technology Sydney. The theme of ICDS 2015 will be: "Global Perspectives on Data Science ". The main topics, but not limited to, are as follows:
Mathematical Issues in Data Science
Big Data Issues and Applications
Data Quality and Data Preparation
Data-driven Scientific Research
Evaluation and Measurement in Data Science
Big Data Mining and Knowledge Management
Case Study of Data Science
Social impacts of Data Science