[CODATA-international] Fwd: [open-science] Invitation to 2016 IEEE Conference on Data Science and Advanced Analytics
Simon CODATA
simon at codata.org
Mon Apr 4 08:25:38 EDT 2016
Members of the CODATA international community may be interested in the conference on Data Science and Advanced Analytics announced below.
With very best wishes,
Simon.
___________________________
DATA SCIENCE TRAINING OPPORTUNITIES - FUNDING AVAILABLE - DEADLINE APPROACHING!
CODATA-RDA School of Research Data Science, hosted at the International Centre of Theoretical Physics, Trieste, Italy, 1-12 August 2016: http://indico.ictp.it/event/7658/ - FUNDING AVAILABLE - DEADLINE 18 April 2016.
CODATA International Training Workshop in Big Data for Science, Beijing, 4-17 July http://www.codata.org/news/105/62/CODATA-International-Training-Workshop-in-Big-Data-for-Science-Beijing-4-17-July - FINDING AVAILABLE - DEADLINE 18 April 2016
___________________________
Dr Simon Hodson | Executive Director CODATA | http://www.codata.org
E-Mail: simon at codata.org | Twitter: @simonhodson99 | Skype: simonhodson99
Blog: http://www.codata.org/blog
Diary: http://bit.ly/simonhodson99-calendar
Tel (Office): +33 1 45 25 04 96 | Tel (Cell): +33 6 86 30 42 59
CODATA (Committee on Data of the International Council for Science), 5 rue Auguste Vacquerie, 75016 Paris, FRANCE
Begin forwarded message:
> From: "Wenfeng Hou" <uts.shawn2014 at gmail.com>
> Subject: [open-science] Invitation to 2016 IEEE Conference on Data Science and Advanced Analytics
> Date: 3 April 2016 02:51:41 CEST
> To: open-science <open-science at lists.okfn.org>
> Reply-To: "uts.shawn2014" <uts.shawn2014 at gmail.com>
>
> =========================================================================================
> IEEE DSAA'2016: Third International Conference on
> Data Science and Advanced Analytics
>
> Montreal, Canada
> October 17-19, 2016
>
> https://www.ualberta.ca/~dsaa16/
> =========================================================================================
>
> Submission Website
> The submission Web site for DSAA'2016 is https://easychair.org/conferences/?conf=dsaa2016.
>
> Important Dates
> Paper Submission deadline: Friday 20 May, 2016, 11:59 PM PDT
> Notification of acceptance: 15 July, 2016
> Final Camera-ready papers due: 19 August, 2016
>
> Publications
> All accepted papers will be published by IEEE and included in the IEEE Xplore Digital Library.
> The conference proceedings will be submitted for EI indexing through INSPEC by IEEE.
> Top quality papers accepted and presented at the conference will be selected for extension and
> publication in the special issues of some international journals, including IEEE TKDE, ACM TKDD,
> ACM TIIS and WWWJ.
>
> Introduction
> Data driven scientific discovery is an important emerging paradigm for computing in areas
> including social computing, services, Internet of Things, sensor networks, telecommunications,
> biology, health-care, and cloud. Under this paradigm, Data Science is the core that drives new
> researches 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. Among the complex aspects to be addressed we mention here the integration
> across heterogeneous, interdependent complex data resources for real-time decision making,
> streaming data, collaboration, and ultimately value co-creation. 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 data available to enterprises, Government or on the Web.
>
> Following the previous two successful editions DSAA'2014, DSAA' 2015, the 3rd IEEE International
> Conference on Data Science and Advanced Analytics (DSAA' 2016) aims to provide a premier forum
> that brings together researchers, industry practitioners, as well as potential users of big data,
> for discussion and exchange of ideas on the latest theoretical developments in Data Science as
> well as on the best practices for a wide range of applications.
>
> DSAA is also technically sponsored by ACM through SIGKDD.
>
> DSAA'2016 will consist of two main tracks: Research and Applications. The Research Track is aimed
> at collecting original contributions related to foundations of Data Science and Data Analytics.
> The Applications Track is aimed at collecting original papers (not published nor under
> consideration at any other venue) describing substantial contributions related to Data Science and
> Data Analytics in real life scenarios. DSAA solicits then both theoretical and practical works on
> data science and advanced analytics.
>
>
> Topics of Interest -- Research Track
>
> General areas of interest to DSAA'2016 include but are not limited to:
> 1. Foundations
> * New mathematical, probabilistic and statistical models and theories
> * New machine learning theories, models and systems
> * New knowledge discovery theories, models and systems
> * Manifold and metric learning, deep learning
> * Scalable analysis and learning
> * Non-iidness learning
> * Heterogeneous data/information integration
> * Data pre-processing, sampling and reduction
> * High dimensional data, feature selection and feature transformation
> * Large scale optimization
> * High performance computing for data analytics
> * Architecture, management and process for data science
>
>
> 2. Data analytics, machine learning and knowledge discovery
> * Learning for streaming data
> * Learning for structured and relational data
> * Intent and insight learning
> * Mining multi-source and mixed-source information
> * Mixed-type and structure data analytics
> * Cross-media data analytics
> * Big data visualization, modeling and analytics
> * Multimedia/stream/text/visual analytics
> * Relation, coupling, link and graph mining
> * Behavior, change, dynamics and variation modeling and analytics
> * Personalization analytics and learning
> * Web/online/social/network mining and learning
> * Structure/group/community/network mining
> * Cloud computing and service data analysis
>
>
> 3. Storage, retrieval and search
> * Data warehouses, cloud architectures
> * Large-scale databases
> * Information and knowledge retrieval, and semantic search
> * Web/social/databases query and search
> * Personalized search and recommendation
> * Human-machine interaction and interfaces
> * Crowdsourcing and collective intelligence
>
>
> 4. Privacy and security
> * Security, trust and risk in big data
> * Data integrity, matching and sharing
> * Privacy and protection standards and policies
> * Privacy preserving big data access/analytics
> * Social impact
>
>
> Topics of Interest -- Applications Track
>
> Papers in this track should motivate, describe and analyse the use Data Analytics tools
> and/or techniques in practical application as well as illustrate their actual impact.
> We seek contributions that address topics such as (but not limited to) the following:
> * Best practices and lessons
> * Data-intensive organizations, business and economy
> * Quality assessment and interestingness metrics
> * Complexity, efficiency and scalability
> * Big data representation and visualization
> * Business intelligence, data-lakes, big-data technologies
> * Large scale application case studies and domain-specific applications, such as but not limited to:
> * Online/social/living/environment data analysis
> * Mobile analytics for hand-held devices
> * Anomaly/fraud/exception/change/event/crisis analysis
> * Large-scale recommender and search systems
> * Data analytics applications in cognitive systems, planning and decision support
> * End-user analytics, data visualization, human-in-the-loop, prescriptive analytics
> * Business/government analytics, such as for financial services, socio-economic activities,
> culture, manufacturing, retail, utilities, telecom, national security, cyber-security,
> e-governance, etc.
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