Call for Papers

The 3rd Workshop on “New Methods and Tools for Big Data (MT4BD-2016)” will welcome paper submissions introducing and implementing methods and tools to address various algorithms and methods for processing, modeling and mining of big data and applications. This workshop will provide a forum for the exchange of ideas between theoreticians and practitioners.

Authors are invited to electronically submit original, English-language research contributions no longer than 10 pages formatted according to the Springer LNCS style, or experience reports. Submitted papers must present unpublished work, not being considered for publication in other journals or conferences. Submitted papers will be refereed by at least three reviewers for quality, correctness, originality, and relevance. Notification and reviews will be communicated via email. Accepted papers will be presented at the conference and included in the proceedings, which will be published by SPRINGER in the IFIP AICT Lecture Notes in Computer Science, and they will be available on site. It is important though to follow the instructions in this page to ensure that your paper will be included in the proceedings.
A paper may not be included in the proceedings if the requirements are not met, or if the registration fee is not received by the deadline of the submission of the camera-ready. Based on the reviewers’ comments and on the presentation, and after a second peer review process, a number of selected papers will be published in a special issue of a scientific Journal with high Impact Factor.


Topics of interest include, but are not limited to, the following new techniques and applications relevant to the big data topic:

  • Big Data Analytics;
    • Business intelligence and analytics;
    • Interactive Visualization Technologies and Visual Analytics;
    • Personalization;
    • Semantics;
    • Knowledge representation and reasoning;
    • Data mining;
    • Human Collaboration (crowdsourcing)
  • Tools and Applications:
    • E-commerce;
    • E-learning;
    • Smart Health and Wellbeing;
    • Smart Cities;
    • Ontologies for Big Data;
    • Sensors Networks;
    • Industrial Automation;
    • Systems Biology and Bioinformatics;
    • Network-based and Personalized Medicine;
    • Geoinformatics;
    • Financial Forecasting and Trading;
    • Security
  • Big Data Architectures and Frameworks
    • Cloud computing;
    • Grid computing;
    • Large-scale triple stores;
    • Reasoning over streaming data;
    • Data storage and processing frameworks;
    • Security and privacy;