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BDSDST 2016 : Workshop on Big Data, Smart Data and Semantic Technologies

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Link: https://www.fzi.de/en/news/bdsdst-2016/
 
When Sep 30, 2016 - Sep 30, 2016
Where Klagenfurt, Austria
Submission Deadline May 22, 2016
Notification Due Jun 6, 2016
Final Version Due Jun 27, 2016
Categories    big data   smart data   semantic   logistics
 

Call For Papers

CALL FOR PAPERS

2nd International Workshop on Big Data, Smart Data and Semantic Technologies (BDSDST 2016) at INFORMATIK 2016

https://www.fzi.de/en/news/bdsdst-2016/

INFORMATIK 2016, Klagenfurt, Austria, September 26 – 30, 2016
BDSDST Workshop, September 30, 2016, 09:00 - 17:30h
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IMPORTANT DATES
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Paper submission deadline: May 22, 2016 (extended)
Author notification: June 6, 2016
Camera ready version: June 27, 2016
Workshop: September 30, 2016

AIMS
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In modern societies, almost every individual is using technology for entertainment, communication or business purposes. Depending on roles and goals, as well on the application domain, the variety of data people work with is becoming more and more complex. At the same time, the growing technical possibilities to gather and aggregate multi-modal data from sensors and different services allow for evidence-based information systems enabling both humans and machines to make well-informed decisions.

These large and complex data sets, commonly characterized by high data volume, high variety of the data types and data sources, high velocity of the incoming data and the expected information output (real-time requirement) as well as the uncertainty about the veracity of the data, are known as Big Data. These characteristics make it difficult to process the data using existing data management applications and traditional information technologies. On the other hand, when processed and analyzed properly, Big Data is transformed into “Smart” Data and might carry huge amounts of useful information, which was not accessible beforehand and allows for better-founded, more robust predictions and improved decision-making in almost any domain. That is why new predictive and prescriptive analytic approaches are continuously increasing in importance.

Besides new analytic approaches, novel information technologies such as semantic technologies are necessary in order to exploit the full potential of the gathered data. Unlike traditional information technology where the meaning of data and their relationships are predefined and “hard-wired” into data formats and applications, semantic technologies encode meanings explicitly and independent from concrete formats and application logic. This enables machines and people likewise to understand, share, and reason over semantically represented data. Semantic technologies provide an abstraction layer on top of existing ICT infrastructures and facilitate the interrelation and integration of data, content, and processes in meaningful ways, which is very important when dealing with high amounts of heterogeneous data.

We believe that using Big and Smart Data as well as methods and tools based on semantic technologies will provide more transparency, enable precise and well-founded decisions and improve planning processes, which will result in more efficient and user-centric processes and systems, especially in the application areas listed subsequently.

TOPICS
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The BDSDST 2016 workshop aims at bringing together researchers and practitioners using Big and Smart Data and/or semantic technologies and support technology transfer from foundational research into practice.
We invite submissions from - but not limited to - the following domains:

* Transport logistics
* Production planning and control
* Production scheduling
* Process planning and monitoring
* Maintenance logistics
* Service parts demand analytics
* Supply chain management
* Smart Factory
* Integration and visualization of sensor and mobility data
* Data-driven supply chain and traffic optimization
* Risk and congestion management
* Disruption management
* Mobility service analytics
* Traffic flow modelling and analytics
* Emission modelling, analytics, simulation and visualization
* Public transportation
* Open Data
* Prescriptive analytics
* Complex Event Processing
* Ambient Intelligence
* Cognitive Systems
* Information Integration
* Machine Learning
* Mobile Information Systems
* Context-aware Computing
* Text Mining
* Service-oriented Computing
* Grid and Cloud Computing
* Technology-enhanced learning
* Automation
* Energy consumption modelling, monitoring and analytics
* smartEnergy
* Smart Grid
* eGovernment
* eMobility
* eHealth

In addition to general usage of Big Data and semantic technologies, a focus on improving the transparency, usability and auditability of processes and systems, is especially encouraged.

INTENDED AUDIENCE
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As participants of the workshop, we expect researchers and practitioners from various fields in research and industry. The program committee will comprise a substantial number of participants from industry.

SUBMISSION
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Contributions are limited to 14 pages for full papers and to 8 pages for short papers, work in progress papers and industrial papers.
The contributions will be reviewed by several program committee members each. Accepted papers have to be presented at the workshop by at least one author.

- Submissions must be in PDF format and follow the LNI style guidelines (https://www.gi.de/index.php?id=171).
- Accepted papers will appear in the (electronic) Lecture Notes in Informatics (LNI, http://www.gi.de/service/publikationen/lni/).
- Contributions shall be submitted via EasyChair online submission system at https://easychair.org/conferences/?conf=bdsdst2016.

ORGANIZING COMMITTEE
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Nico Rödder, FZI Research Center for Information Technology, Karlsruhe, Germany
Natalja Kleiner, FZI Forschungszentrum Informatik, Karlsruhe, Germany
Suad Sejdovic, FZI Forschungszentrum Informatik, Karlsruhe, Germany
Stefan Zander, FZI Forschungszentrum Informatik, Karlsruhe, Germany
Stefan Jähnichen, FZI Research Center for Information Technology, Berlin Branch, Germany
Rudi Studer, Karlsruher Institut für Technologie (KIT), Karlsruhe, Germany

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