Data driven scientific discovery is an important emerging paradigm for computing in areas including social, service, Internet of Things, sensor networks, telecommunications, biology, health-care and cloud. Under this paradigm, Data Science is the core that drives new research in many areas, from environmental to social. There are many associated scientific challenges, ranging from data capture, creation, storage, search, sharing, modeling, analysis, and visualization. We mention here the integration across heterogeneous, interdependent complex data resources for real-time decision making, streaming data, collaboration, and ultimately value co-creation among the complex aspects to be addressed. Data science encompasses the areas of data analytics, machine learning, statistics, optimization and managing big data, and has become essential to glean understanding from large data sets and convert data into actionable intelligence, be it the data available to enterprises, Government or on the Web.
International Conference on Data Science and Advanced Analytics (DSAA) started in 2014 aiming to be a flagship in the data science and analytics field. It provides a premier forum that brings together researchers, industry practitioners, as well as potential users of data science and big data analytics. It covers all data science and analytics related areas, including statistical, probabilistic and mathematical methods, machine learning, data and business analytics, data mining and knowledge discovery, infrastructure, storage, retrieval and search, privacy and security, and relevant applications, practices, tools and evaluation. DSAA’2014 was not a fully IEEE supported conference, but was technically co-sponsored by IEEE Computational Intelligence Society (CIS) and ACM through SIGKDD. DSAA became a fully IEEE CIS supported conference from the second edition. The second IEEE DSAA’2015 was held in Paris in 2015 which was also very successful. The third IEEE DSAA’2016 is planned in Montreal. They continue to be technically sponsored by ACM.
IEEE DSAA’2017 will consist of two main Tracks: Research and Application; the Research Track is aimed at collecting contributions related to theoretical foundations of Data Science and Data Analytics. The Application Track is aimed at collecting contributions related to applications of Data Science and Data Analytics in real life scenarios. DSAA’2017 solicits then both theoretical and practical works on data science and advanced analytics. It also inherits the unique features of past successful DSAA, that is the Trends & Controversies session where we invite visionary speakers to outline different insights and views about today and future of data science and advanced analytics, and the Special sessions which replace the traditional workshop and encourage submission of research on emerging topics. DSAA’2017 is also featured by a panel session where we invite internationally well recognized researchers to discuss challenges and important selected topics. Another highlight is the keynote talks. We invite four high profile keynote speakers from both academia and industry, and both domestic and abroad, to deliver insightful talks that best match the scope of data science and advanced analytics. We try to receive as much support as possible from industry to make DSAA’2017 financially secured. For this the conference must be attractive to the sponsors. We inherit the good practice of the invited industrial talk session in which the selected high profile sponsors can give talks without papers. We also plan to give them enough space to set up booths to disseminate their activities. Further, we seek for a possibility of co-locating with our domestic academic activities to attract domestic students for them to give opportunities to visit the sponsors’ booths, which gives another incentive to sponsors.