The 3rd Norwegian Big Data Symposium - NOBIDS 2017 welcomes the submission of original research and application papers dealing with all aspects of Big Data and also the speacial theme "Fake News".

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 3rd Norwegian Big Data Symposium (NOBIDS) focuses on Big Data applications and Big Data research from all disciplines. This year NOBIDS has a special focus on fake news. As the term “fake news” became popular within the last years, it is a growing problem to distinguish the real news within the great churn of online news. The effect of social media both as a source of news and the media for spreading the existing news cannot be underestimated. Recently, detection of fake news is mostly done by the manual work of professional journalists while there is also a lot of research going on towards the automatic detection of fake news. Worldwide efforts to professionally and easily spot the fake news, brings the journalists and computer scientists together. NOBIDS 2017 aims to bring researchers and industry practitioners together to exchange ideas, establish collaborations and share experiences within the special theme of fake news.

NOBIDS 2017 will be held in conjunction with the NxtMedia Conference in Trondheim.

Topics of Interest

Topics of interests for the research track of NOBIDS 2017 include but are not limited to:

    Fake news detection
    Deception and click-bait detection
    News classification
    Detection of trusted news sources
    News verification
    Industrial applications of big data and data analytics
    Handling Big data V's:  Volume, Velocity, Variety and Veracity
    Big data management and life cycle support
    Big data systems and architectures
    New programming models and platforms for big data computing
    Cloud/grid/stream computing for big data
    Big data on mobile platforms
    Large-scale semantics and open linked data
    Big data analytics
    Big data and AI/machine learning and cognitive computing
    Big data and Natural Language Processing
    Big data and High Performance Computing
    Large-scale recommender systems and personalization
    News recommender systems and news analytics
    News summarization, classification and sentiment analysis
    User experience and visualization of big data
    User intelligence and user profiling
    Social media systems
    Big data anonymisation, privacy and security
    Data driven innovation
    Combining open and protected data
    Business models for big data
    Legal aspects of open and protected data
    Evaluation of big data applications
    Big data benchmarking