CFP: Special Issue "Big Data: Multidimensional Design and Modeling"
Mathematics (ISSN 2227-7390)
This special issue belongs to the section "Mathematics and Computer Science".
Impact factor: 1.747
30 September 2021

Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website.
Big Data refers to great volumes of data, which generate and transfer very rapidly, and are too unstructured for the traditional information systems to handle. In less than a decade, Big Data has been established as a fundamental and essential component of information systems and, especially, decision-support systems. The combination of Big Data and Data Mining has created new business opportunities and new solutions to difficult problems.

Big Data usually relies on relational and non-relational data models. However, the existing paradigms for data modelling are neither sufficient in quantity nor suitable to deal with Big Data requirements. The volume, velocity, and variety of Big Data demand new modelling techniques and frameworks to be able to cope with the challenges of Big Data. For that reason, it is essential to rethink the existing modelling approaches, and either enhance the existing ones or develop new ones.

The purpose of this Special Issue is to compile a collection of scientific papers addressing the latest developments and efforts in the modelling of Big Data by the research community. Papers combining a high academic standard coupled with a practical focus on the field are welcomed.
The topics of this special issues include but not limited to:
* Conceptual, Logical and Physical Design of Big Data
* Metadata and Applications in Big Data
* Big Data Warehousing
* Big Data Mining
* Modeling of NoSQL databases
Dr. Sergio Luján-Mora (Department of Software and Computing Systems, University of Alicante, Spain)
See the Special Issue website ( for more information.