[AISWorld] CFP: VLDB 2016 Real-Time Business Intelligence Workshop (BIRTE 2016)
Castellanos, Malu G
malu.castellanos at hpe.com
Mon Mar 21 15:24:09 EDT 2016
CALL FOR PAPERS
BIRTE 2016
Tenth International Workshop on Real-Time Business Intelligence
http://db.cs.pitt.edu/birte2016/
September 5, 2016
In conjunction with VLDB 2016
New Delhi, India
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Celebrating 10 years of bridging Academic and Industrial Innovation!
HIGHLIGHTS
3 keynotes by Rakesh Agrawal, Surajit Chauduri and C Mohan.
1 invited talk by Stratos Idreos
1 industrial invited talk (Google)
IMPORTANT DATES
* Abstracts due: June 3, 2016
* Papers due: June 8, 2016 at 5 PM PST
* Notification of acceptance: July 15, 2016
* Camera-ready copies: August 15, 2016
DESCRIPTION
In today's competitive and highly dynamic environment, analyzing data to understand how the business is performing and to predict outcomes and trends has become critical. The traditional approach to reporting is no longer adequate. Instead users now demand easy-to-use intelligent platforms and applications capable of analyzing real-time data to provide insight and actionable information at the right time. The end goal is to support better and timelier decision making, enabled by the availability of up-to-date, high-quality information.
Although there has been progress in this direction and many companies are introducing products towards meeting this goal, there is still a long way to go. In particular, the whole lifecycle of business intelligence requires innovative techniques and methodologies capable of dealing with the requirements imposed by these new generation of BI applications. From the capture of real-time business data to the transformation and delivery of actionable information, all the stages of the Business Intelligence (BI) cycle call for new algorithms and paradigms to support value-added functionalities. These functionalities include dynamic integration of real-time data feeds from operational sources, optimization and evolution of ETL transformations and analytical models, and dynamic generation of adaptive real-time dashboards, just to name a few.
The series of BIRTE workshops, starting in 2006, have always been held in conjunction with VLDB. The series aims to provide a forum to discuss topics related to this emerging field and set research directions towards making business intelligence more real-time. Following the success of previous BIRTE editions (2006, 2008-2013) submissions for research, industrial, position, and demo papers on relevant topics are encouraged.
TOPICS OF INTEREST
Areas of particular interest for the workshop include (but are not limited to) the following, as THEY RELATE TO REAL-TIME BUSINESS INTELLIGENCE:
- Analytics as a service
- Analytics for Linked Data/semantic web
- Big Data systems and applications for high-velocity data
- Case studies and experience (lessons, pitfalls, guidelines) from real-time BI practice
- Challenges from advanced domains, e.g., energy data or sensor data
- Cloud intelligence
- Collaborative real-time BI
- Crowdsourcing and crowd intelligence
- Data capture in real-time
- Data mining, analytics, and OLAP for real-time decision support
- Data quality and cleansing
- Event-driven analytics
- Integration of prediction models with real-time and historical data
- Integration of open and private data
- Linking business strategies with real-time BI
- Novel architectures for real-time BI
- Optimization, performance, and scalability
- Privacy and security in real-time BI
- Real-time ETL, ELT, and beyond
- Streaming data, streaming engines
- Tuning and management of the real-time data warehouse
- Visualizing real-time data and information
We call for research, industrial, position, and demo submissions covering these topics of interest. Papers describing real-time BI systems, platforms, and applications are especially welcome.
SUBMISSION GUIDELINES
Papers should follow the LNCS format (see http://www.springer.com/computer/lncs?SGWID=0-164-6-791344-0l for details). The length of research and industrial papers should not exceed 16 pages, whereas the maximum page limit for position papers and demo papers are 8 and 4 pages, respectively. Papers in PDF should be submitted electronically to the review web site https://cmt.research.microsoft.com/BIRTE2015.
PROCEEDINGS
As in previous years, post-proceedings will be published as a LNBIP volume by Springer-Verlag.
ORGANIZERS
* General Chair
Meichun Hsu, Hewlett-Packard, USA
* PC Chairs
Malu Castellanos, Hewlett-Packard, USA
Panos K. Chrysanthis, University of Pittsburgh, USA
* PC Members (tentative)
Roger Barga, Amazon, USA
Alejandro Buchmann, Technische Universität Darmstadt, Germany
Christof Bornhoevd, RMS, USA
Damianos Chatziantoniou, AAthens University of Economics and Business, Greece
Shimin Chen, Chinese Academy of Sciences, China
Howard Ho, IBM, USA
Wolfgang Lehner, Dresden University of Technology, Germany
Olga Papaemmanouli, Brandeis University, USA
Evaggelia Pitoura, University of Ioannina, Greece
Krithi Ramamritham, IIT Bombay, India
Karthik Ramasamy, Twitter, USA
Mohamed Sharaf, Queensland University, Australia
Eric Simon, SAP-BO, France
Nesime Tatbul, Intel Labs and MIT, USA
* Proceedings Chair
Kostas Pelechrinis, University of Pittsburgh, USA
* Web Master
Anatoli Shein, University of Pittsburgh, USA
ABOUT VLDB
Very Large Data Base Endowment Inc. (VLDB Endowment) is a non-profit organization incorporated in the United States for the sole purpose of promoting and exchanging scholarly work in databases and related fields throughout the world. One of its vehicles for achieving its objectives is the sponsorship and support of the annual VLDB conference, a premier annual international forum for database researchers, vendors, practitioners, application developers, and users. VLDB 2015 will take place at the Hilton Waikoloa Village on the beautiful Kohala Coast on the northwestern side of the Big Island of Hawai'i. Hawai'i Island is the largest of the Hawaiian Islands; it is also referred to as the "Orchid Island" and more famously defined by its size as the Big Island, making it an especially appropriate setting for a conference whose concerns include Big Data.
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