[image 01538] Re: CfP for First International Workshop on Data to Decision (D2D 2016)

Masakazu Iwamura masa @ cs.osakafu-u.ac.jp
2015年 11月 4日 (水) 14:19:27 JST


image-MLの皆様、Document-MLの皆様

大阪府立大学の岩村です。

以前ご案内させていただきました D2D 2016 というワークショップの投稿締切が
11月18日に延期になりました。それと共に、ワークショップに採択された論文の
一部はInternational Journal of Big Data Intelligenceにinviteされるそうです。
投稿をご検討いただければ幸いです。


On 2015/10/13 0:09, Masakazu Iwamura wrote:
> image-MLの皆様、Document-MLの皆様
> 
> 大阪府立大学の岩村です。
> 
> 国際ワークショップFirst International Workshop on Data to Decision (D2D
> 2016)のご案内です。
> トピックはデータベース関係を始め、マルチメディアなど、この分野に関係した
> ものも含まれています。
> 投稿をご検討いただければ幸いです。
> 投稿締切は11月1日です。
> 
> 
>    Masakazu Iwamura, Ph.D.
> 	Associate Professor
> 	Dept. of Computer Science and Intelligent Systems
> 	Graduate School of Engineering
> 	Osaka Prefecture University
> 	1-1 Gakuencho, Naka, Sakai, Osaka 599-8531, Japan
> 	Tel  : +81-72-254-9277     Fax  : +81-72-254-8291
> 	Web: http://imlab.jp/~masa/
> 
> 
> ------------------------------------------------------------------------
> CALL FOR PAPERS
> 
> 
> The First International Workshop on Data to Decision (D2D 2016)
> http://ssrg.nicta.com.au/Events/conferences/D2D2016/
> 
> @ Laguna Hills, California, USA.  Feb 3-5, 2016.
> In conjunction with The 10th International Conference on Semantic
> Computing (ICSC2016)
> 
> 
> Overview
> --------
> Computing and networking, data collection and analytics have been
> booming in the recent decades to manifest the coming Big Data era.
> Nowadays, more and more data are being collected and analyzed by
> organizations to make critical decisions. However, many challenges
> remain to be addressed.
> 
> One challenge is that it is not easy to track which versions of a data
> set flow through which versions of the cleaning, transformation and
> analytics to produce the decisions, especially with constantly updating
> heterogeneous data sources, complex human-in-the loop data wrangling,
> and sometimes non-reproducible black-box data analytics and version
> control of big data;
> 
> Another challenge is to support data scientists to easily explore
> subsets of data locally, to share reproducible versions of their
> exploration in the team, and finally to transform the successful
> versions into large-scale deployment for continuously serving the
> learned insights and models of other decision-making systems.
> 
> Yet another challenge is to keep semantically and physically consistence
> of views among distributed and multiple data stores. This can be seen
> from many real-life examples. In the machine learning and data mining
> community, researchers require data to data and data to model links with
> proper provenance of information. In the scientific computing community,
> smart and efficient management of large amounts of data going through
> various computation workflows with some degree of reproducibility is
> also a must. In large scale distributed systems such as clouds, data
> management tends to employ multi-store systems where global data are
> split based on various criteria and then stored into distributed
> multiple stores, thus making the maintenance of consistency difficult.
> 
> In this workshop, we bring together researchers and practitioners to
> share their novel approaches and experiences of managing data to
> decision "pipelines" in a production or exploration environment, the
> transparency and trustworthiness of decision and data, data processing
> and tracking for closing the gap between advanced computing and
> platforms, and data management and engineering for newly emerging
> challenges and topics.
> 
> 
> Topics of interest
> ------------------
> Topics of interest include, but are not limited to:
> 
> - Data to decision management
> - Data transformation and analytics pipelines
> - Workflow management in service and scientific computing
> - Entity resolution/matching and schema matching
> - (Big) Data provenance and lineage
> - Data processing and tracking
> - Semantic issues in data provenance
> - Semantic issues in APIs
> - Data management in data science, AI, data mining and machine learning
> - Data management in exploration environments, production environments,
> and the connection of the two
> - Data and data computing platforms
> - Service oriented architecture for data analytics pipelines
> - Data analytics as services
> - Trustworthiness of data and analytics
> - Reproducible data analytics and decisions
> - Traceability from decisions to data
> - Understanding and explaining of decisions
> - Mining and analysis of contracts and e-contracts
> - Entity matching
> - Data analytics and pipelines
> - Workflow management in service and scientific computing
> - Transactions in web services
> - Semantic issues in analysis and verification of APIs
> - Data provenance and lineage
> - Data automata
> - Data semantics in multimedia processing
> - Functional programming for data processing
> - Approximate computing for big data
> - Experiences and solutions for specific domains including security,
> health, transportation, logistics, e-government, digital economy,
> environment, computational physics and chemistry, astronomy, and other
> branches and applications of data science
> 
> 
> SUBMISSIONS
> ---------------
> The submission and review process will be done using EasyChair
> (https://easychair.org/conferences/?conf=d2d2016).
> 
> Submissions must be no longer than 6 pages (including everything) and adhere
> to the IEEE Computer Society 8.5"x11" two-column camera-ready format. The
> manuscript templates for MS Word and LaTeX can be found at the following
> link:
> http://www.ieee.org/conferences_events/conferences/publishing/templates.html
> 
> All papers will be peer-reviewed by at least 3 PC members and evaluated
> based
> on originality, technical quality and relevance to the workshop.
> 
> 
> IMPORTANT DATES
> ---------------
> - Workshop paper submissions: Nov 1, 2015
> - Notification to authors: Dec 1, 2015
> - Camera-ready: Jan 10, 2016
> 
> 
> General Co-Chairs
> -----------------
> - Liming Zhu, Data61/CSIRO/University of New South Wales/The University
> of Sydney, Australia
> - Jagan Sankaranarayanan, NEC Labs America, USA
> 
> 
> Program Committee
> -----------------
> - Daniel W. Sun (Chair), Data61/CSIRO, Australia
> - Joseph Antony, Australian National University, Australia
> - Alan Fekete, University of Sydney, Australia
> - Masakazu Iwamura, Osaka Prefecture University, Japan
> - Ian Gorton, Northeastern University, USA
> - Guoqiang Li, Shanghai Jiao Tong University, China
> - Rong-Hua Li, Shenzhen University, China
> - Baiyang Liu, Facebook, USA
> - Min Luo, NTT, Japan
> - Adam Jatowt, Kyoto University, Japan
> - Jason X. Jin, PayPal Inc., USA
> - Jianquan Liu, NEC Central Research Labs, Japan
> - Baoning Niu, Taiyuan University of Technology, China
> - Leon Osterwell, University of Massachusetts Amherst, USA
> - Oliver Obst, Data61/CSIRO, Australia
> - Jianbin Qin, University of New South Wales, Australia
> - Rajiv Ranjan, Newcastle University, U.K.
> - Salman Shaikh, University of Tsukuba, Japan
> - Chih-Hua Tai, National Taipei University, Taiwan
> - Nenad Tomasev, Google, USA
> - Tatsuhiro Tsuchiya, Osaka University, Japan
> - Damien Watkins, Data61/CSIRO, Australia
> - Jianwen Xiang, Wuhan University of Technology, China
> - Bin Yang, Rakuten Institute of Technology, Japan
> 
> 
> Organizing Committee
> --------------------
> - Daniel W. Sun, Data61/CSIRO/University of New South Wales, Australia
> - Jianquan Liu, NEC Central Research Labs, Japan
> 


-- 

  Masakazu Iwamura, Ph.D.
	Associate Professor
	Dept. of Computer Science and Intelligent Systems
	Graduate School of Engineering
	Osaka Prefecture University
	1-1 Gakuencho, Naka, Sakai, Osaka 599-8531, Japan
	Tel  : +81-72-254-9277     Fax  : +81-72-254-8291
	Web: http://imlab.jp/~masa/


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