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NOBIDS 2016 : 2nd Norwegian Big Data Symposium


When Nov 15, 2016 - Nov 15, 2016
Where Trondheim, Norway
Submission Deadline Oct 10, 2016
Notification Due Oct 20, 2016
Final Version Due Nov 7, 2016
Categories    computer science   big data

Call For Papers

NOBIDS 2016 welcomes the submission of original research and application papers dealing with all aspects of Big Data.

The impact of Big Data and large-scale data infrastructures is now visible in science, business, government and civil society. Companies store more data than anyone could imagine just a few years back, and the proliferation of open linked data has made it possible to share well-defined data across organizational and geographical boundaries. Big data and data analytics are rapidly expanding research areas that are of great importance to both industry and academia. The focus is on scalable techniques for intelligent data production, collection, classification, storing, integration, analysis and visualization. Big Data is multi-disciplinary of nature and is closely linked to industrial innovation and value creation.

The 2nd Norwegian Big Data Symposium (NOBIDS) focuses on Big Data applications and Big Data research from all disciplines, and it aims to bring researchers and industry practitioners together to exchange ideas, establish collaborations and share experiences. There are already a number of successful applications of Big Data solutions in Scandinavian companies. A central objective of the symposium is to create an interdisciplinary community that addresses industry-relevant issues in Big Data and promotes fruitful collaboration between researchers, companies and practitioners. The symposium itself is divided into an industry track and a research track:
Industrial track: Invited speeches on industrial Big Data applications in Scandinavia
Research track: Scientific papers on Big Data and its possible applications

Topics of interests for the research track of NOBIDS 2016 include but are not limited to:
- Industrial applications of big data and data analytics
- Large-scale recommender systems and personalization
- News recommender systems and news analytics
- Cloud/grid/stream computing for big data
- New programming models and platforms for big data computing
- Large-scale semantics and open linked data
- News summarization, classification and sentiment analysis
- User intelligence and user profiling
- Social media systems
- User experience and visualization of big data
- Big data on mobile platforms
- Privacy issues in big data
- Evaluation of big data applications

Long papers: Up to 8 pages, including references
Short papers: Up to 4 pages, including references
Demo papers: 2-4 pages, including references

Accepted papers will be published online in a CEUR workshop proceedings. At least one author of each accepted paper must attend the workshop. A selection of the best papers will be invited to publish in a special issue of an NTNU Open Access journal on big data and analytics.

There is no registration fee for NOBIDS 2016. Participation is free of charge, though the participants are encouraged to register also for the NxtMedia conference the day after.

Related Resources

IEEE Big Data 2018   2018 IEEE International Conference on Big Data
ICMLB 2018   International Conference on Machine Learning and Big Data 2018
ICDIM 2018   Thirteenth International Conference on Digital Information Management (ICDIM 2018)
GreeNet Symposium - SGNC 2018   9th Symposium on Green Networking and Computing (SGNC 2018)
BDCAT 2018   5th IEEE/ACM International Conference on Big Data Computing, Applications and Technologies
DISP 2018   Special Issue on Data Intelligence in Security and Privacy, Journal of Information Security and Applications
UCC 2018   11th IEEE/ACM International Conference on Utility and Cloud Computing
PST 2018   The Sixteen International Conference on Privacy, Security and Trust (PST)
SI: Big Data Exploration, Visualization 2018   Special Issue on Big Data Exploration, Visualization and Analytics
ACIIDS 2018   10th Asian Conference on Intelligent Information and Database Systems