MoBiD 2016
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The fifth International Workshop on Modeling and Management of Big Data (MoBiD)
Gifu, Japan, 14-17 November 2016

In conjunction with the 35th International Conference on Conceptual Modelling (ER2016)



Due to the enormous amount of data present and growing in the Web and other data sources such as sensors and social networks, there has been an increasing interest in incorporating these huge amounts of external and unstructured data, normally referred to as "Big Data", into traditional applications. This necessity has made that traditional database systems and processing need to evolve and accommodate them to this new situation. We view that several key themes with the Big Data trend include (i) managing big data projects to discover business values; (ii) developing an architecture for a big data environment to conceptualize goals, tasks, and problem-solving methods to apply to domains; (iii) exploring problem-solving methods for big data; (iv) using a cloud for managing large-scale external and internal data; and (v) providing an easy-to-use but powerful services to access/manage/analyze the big data in the cloud.

Therefore, this new era of Big Data and cloud environment requires conceptualization and methods to effectively manage big data and accomplish intended business goals. Thus, the objective of MoBiD'16 is to be an international forum for exchanging ideas on the latest and best proposals for modeling and managing big data in this new data-drive paradigm. Papers focusing on novel applications and using conceptual modeling approaches for any aspects of Big Data such as MapReduce, Hadoop and its ecosystems, Big Data Analytics, social networking, security and privacy, data science approaches, etc. are highly encouraged. The workshop will be a forum for researchers and practitioners who are interested in the different facets related to the use of the conceptual modeling approaches for the development of next generation applications based on Big Data.


mobid2016 [at]   |   Last updated: 18:36 26/02/2016
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