This paper presents and delves into the architecture and intricacies of SeDaSOMA, a
sophisticated framework supporting Se rendipitous, Da ta-as-aS ervice-oriented, O pen big …

We propose a sampling-based method, called RSP-Hist, to construct approximate equi-
width histograms and help data scientists explore the probability distribution of big data on …

When exploring big volumes of data, one of the challenging aspects is their diversity of
origin. Multiple files that have not yet been ingested into a database system may contain …

In recent years, the volume of spatial data has rapidly grown, so it is crucial to process them
in an efficient manner. The level of parallel processing in big data platforms such as Hadoop …

When exploring big volumes of data, one of the challenging aspects is their diversity of
origin. Multiple files that have not yet been ingested into a database system may contain …

Nowadays, big data management and analytics are gaining momentum within the research
community, stirred-up by both sophisticated theoretical models and pragmatic achievements …

The amount of digital data has grown exponentially in recent years, and this trend is on an
upward trajectory. While this amount of data brings with it the possibility of gaining valuable …