<html><head><meta http-equiv="Content-Type" content="text/html charset=us-ascii"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;">Members of the CODATA international community may be interested in the conference on Data Science and Advanced Analytics announced below.<div><br></div><div>With very best wishes,</div><div><br></div><div>Simon.<br><div apple-content-edited="true">
<div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;"><div style="orphans: auto; text-align: start; text-indent: 0px; widows: auto; word-wrap: break-word; -webkit-nbsp-mode: space; -webkit-line-break: after-white-space;">___________________________<br><br>DATA SCIENCE TRAINING OPPORTUNITIES - FUNDING AVAILABLE - DEADLINE APPROACHING!<br><br>CODATA-RDA School of Research Data Science, hosted at the International Centre of Theoretical Physics, Trieste, Italy, 1-12 August 2016: <a href="http://indico.ictp.it/event/7658/">http://indico.ictp.it/event/7658/</a> - FUNDING AVAILABLE - DEADLINE 18 April 2016.<br><br>CODATA International Training Workshop in Big Data for Science, Beijing, 4-17 July <a href="http://www.codata.org/news/105/62/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</a> - FINDING AVAILABLE - DEADLINE 18 April 2016<br>___________________________<br>Dr Simon Hodson | Executive Director CODATA | <a href="http://www.codata.org">http://www.codata.org</a><br><br>E-Mail: <a href="mailto:simon@codata.org">simon@codata.org</a> | Twitter: @simonhodson99 | Skype: simonhodson99<br>Blog: <a href="http://www.codata.org/blog">http://www.codata.org/blog</a><br>Diary: <a href="http://bit.ly/simonhodson99-calendar">http://bit.ly/simonhodson99-calendar</a><br>Tel (Office): +33 1 45 25 04 96 | Tel (Cell): +33 6 86 30 42 59<br><br>CODATA (Committee on Data of the International Council for Science), 5 rue Auguste Vacquerie, 75016 Paris, FRANCE</div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
</div>
<div><br><div>Begin forwarded message:</div><br class="Apple-interchange-newline"><blockquote type="cite"><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;"><span style="font-family:'Helvetica'; color:rgba(0, 0, 0, 1.0);"><b>From: </b></span><span style="font-family:'Helvetica';">"Wenfeng Hou" <<a href="mailto:uts.shawn2014@gmail.com">uts.shawn2014@gmail.com</a>><br></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;"><span style="font-family:'Helvetica'; color:rgba(0, 0, 0, 1.0);"><b>Subject: </b></span><span style="font-family:'Helvetica';"><b>[open-science] Invitation to 2016 IEEE Conference on Data Science and Advanced Analytics</b><br></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;"><span style="font-family:'Helvetica'; color:rgba(0, 0, 0, 1.0);"><b>Date: </b></span><span style="font-family:'Helvetica';">3 April 2016 02:51:41 CEST<br></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;"><span style="font-family:'Helvetica'; color:rgba(0, 0, 0, 1.0);"><b>To: </b></span><span style="font-family:'Helvetica';">open-science <<a href="mailto:open-science@lists.okfn.org">open-science@lists.okfn.org</a>><br></span></div><div style="margin-top: 0px; margin-right: 0px; margin-bottom: 0px; margin-left: 0px;"><span style="font-family:'Helvetica'; color:rgba(0, 0, 0, 1.0);"><b>Reply-To: </b></span><span style="font-family:'Helvetica';">"uts.shawn2014" <<a href="mailto:uts.shawn2014@gmail.com">uts.shawn2014@gmail.com</a>><br></span></div><br><div>
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<div>=========================================================================================</div>
<div> IEEE DSAA'2016: Third International Conference on</div>
<div> Data Science and Advanced Analytics</div>
<div> </div>
<div> Montreal, Canada</div>
<div> October 17-19, 2016</div>
<div> </div>
<div> <a href="https://www.ualberta.ca/~dsaa16/">https://www.ualberta.ca/~dsaa16/</a></div>
<div>=========================================================================================</div>
<div> </div>
<div>Submission Website</div>
<div>The submission Web site for DSAA'2016 is <a href="https://easychair.org/conferences/?conf=dsaa2016">https://easychair.org/conferences/?conf=dsaa2016</a>.</div>
<div> </div>
<div>Important Dates</div>
<div>Paper Submission deadline:
Friday 20 May, 2016, 11:59 PM PDT</div>
<div>Notification of acceptance: 15 July, 2016</div>
<div>Final Camera-ready papers due:
19 August, 2016</div>
<div> </div>
<div>Publications</div>
<div>All accepted papers will be published by IEEE and included in the IEEE Xplore Digital Library. </div>
<div>The conference proceedings will be submitted for EI indexing through INSPEC by IEEE. </div>
<div>Top quality papers accepted and presented at the conference will be selected for extension and </div>
<div>publication in the special issues of some international journals, including IEEE TKDE, ACM TKDD, </div>
<div>ACM TIIS and WWWJ.</div>
<div> </div>
<div>Introduction</div>
<div>Data driven scientific discovery is an important emerging paradigm for computing in areas </div>
<div>including social computing, services, Internet of Things, sensor networks, telecommunications, </div>
<div>biology, health-care, and cloud. Under this paradigm, Data Science is the core that drives new </div>
<div>researches in many areas, from environmental to social. There are many associated scientific </div>
<div>challenges, ranging from data capture, creation, storage, search, sharing, modeling, analysis, </div>
<div>and visualization. Among the complex aspects to be addressed we mention here the integration </div>
<div>across heterogeneous, interdependent complex data resources for real-time decision making, </div>
<div>streaming data, collaboration, and ultimately value co-creation. Data science encompasses the </div>
<div>areas of data analytics, machine learning, statistics, optimization and managing big data, and </div>
<div>has become essential to glean understanding from large data sets and convert data into actionable </div>
<div>intelligence, be it data available to enterprises, Government or on the Web.</div>
<div> </div>
<div>Following the previous two successful editions DSAA'2014, DSAA' 2015, the 3rd IEEE International </div>
<div>Conference on Data Science and Advanced Analytics (DSAA' 2016) aims to provide a premier forum </div>
<div>that brings together researchers, industry practitioners, as well as potential users of big data,</div>
<div>for discussion and exchange of ideas on the latest theoretical developments in Data Science as </div>
<div>well as on the best practices for a wide range of applications.</div>
<div> </div>
<div>DSAA is also technically sponsored by ACM through SIGKDD.</div>
<div> </div>
<div>DSAA'2016 will consist of two main tracks: Research and Applications. The Research Track is aimed </div>
<div>at collecting original contributions related to foundations of Data Science and Data Analytics. </div>
<div>The Applications Track is aimed at collecting original papers (not published nor under </div>
<div>consideration at any other venue) describing substantial contributions related to Data Science and </div>
<div>Data Analytics in real life scenarios. DSAA solicits then both theoretical and practical works on </div>
<div>data science and advanced analytics.</div>
<div> </div>
<div> </div>
<div>Topics of Interest -- Research Track</div>
<div> </div>
<div>General areas of interest to DSAA'2016 include but are not limited to:</div>
<div>1. Foundations</div>
<div>* New mathematical, probabilistic and statistical models and theories</div>
<div>* New machine learning theories, models and systems</div>
<div>* New knowledge discovery theories, models and systems</div>
<div>* Manifold and metric learning, deep learning</div>
<div>* Scalable analysis and learning</div>
<div>* Non-iidness learning</div>
<div>* Heterogeneous data/information integration</div>
<div>* Data pre-processing, sampling and reduction</div>
<div>* High dimensional data, feature selection and feature transformation</div>
<div>* Large scale optimization</div>
<div>* High performance computing for data analytics</div>
<div>* Architecture, management and process for data science</div>
<div> </div>
<div> </div>
<div>2. Data analytics, machine learning and knowledge discovery</div>
<div>* Learning for streaming data</div>
<div>* Learning for structured and relational data</div>
<div>* Intent and insight learning</div>
<div>* Mining multi-source and mixed-source information</div>
<div>* Mixed-type and structure data analytics</div>
<div>* Cross-media data analytics</div>
<div>* Big data visualization, modeling and analytics</div>
<div>* Multimedia/stream/text/visual analytics</div>
<div>* Relation, coupling, link and graph mining</div>
<div>* Behavior, change, dynamics and variation modeling and analytics</div>
<div>* Personalization analytics and learning</div>
<div>* Web/online/social/network mining and learning</div>
<div>* Structure/group/community/network mining</div>
<div>* Cloud computing and service data analysis</div>
<div> </div>
<div> </div>
<div>3. Storage, retrieval and search</div>
<div>* Data warehouses, cloud architectures</div>
<div>* Large-scale databases</div>
<div>* Information and knowledge retrieval, and semantic search</div>
<div>* Web/social/databases query and search</div>
<div>* Personalized search and recommendation</div>
<div>* Human-machine interaction and interfaces</div>
<div>* Crowdsourcing and collective intelligence</div>
<div> </div>
<div> </div>
<div>4. Privacy and security</div>
<div>* Security, trust and risk in big data</div>
<div>* Data integrity, matching and sharing</div>
<div>* Privacy and protection standards and policies</div>
<div>* Privacy preserving big data access/analytics</div>
<div>* Social impact</div>
<div> </div>
<div> </div>
<div>Topics of Interest -- Applications Track</div>
<div> </div>
<div>Papers in this track should motivate, describe and analyse the use Data Analytics tools </div>
<div>and/or techniques in practical application as well as illustrate their actual impact.</div>
<div>We seek contributions that address topics such as (but not limited to) the following:</div>
<div>* Best practices and lessons</div>
<div>* Data-intensive organizations, business and economy</div>
<div>* Quality assessment and interestingness metrics</div>
<div>* Complexity, efficiency and scalability</div>
<div>* Big data representation and visualization</div>
<div>* Business intelligence, data-lakes, big-data technologies</div>
<div>* Large scale application case studies and domain-specific applications, such as but not limited to:</div>
<blockquote style="MARGIN-RIGHT: 0px" dir="ltr">
<blockquote style="MARGIN-RIGHT: 0px" dir="ltr">
<div>* Online/social/living/environment data analysis</div>
<div>* Mobile analytics for hand-held devices</div>
<div>* Anomaly/fraud/exception/change/event/crisis analysis</div>
<div>* Large-scale recommender and search systems</div>
<div>* Data analytics applications in cognitive systems, planning and decision support</div>
<div>* End-user analytics, data visualization, human-in-the-loop, prescriptive analytics</div>
<div>* Business/government analytics, such as for financial services, socio-economic activities, </div>
<div> culture, manufacturing, retail, utilities, telecom, national security, cyber-security, </div>
<div> e-governance, etc.</div></blockquote></blockquote></div>
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