Abstract Methods for Approximate Query Processing (AQP) are essential for dealing with
massive data. They are often the only means of providing interactive response times when …

In the last two decades, interactive visualization and analysis have become a central tool in
data-driven decision making. Concurrently to the contributions in data visualization …

Large-scale distributed computing environments provide a vast amount of heterogeneous
computing resources from different sources for resource sharing and distributed computing …

Data compression is a key technique for reducing the cost of data transfer from storage to
compute nodes. Increasingly, modern data scales necessitate lossy compression …

This paper structures a novel vision for OLAPby fundamentally redefining several of the
pillars on which OLAP has been based for the last 20 years. We redefine OLAP queries, in …

Several innovative applications could be advantageously placed within social networks, to
be effective, attractive, and pervasive. Examples of application domains that could benefit …

In this paper, we investigate the problem of visualizing multidimensional data cubes, and
propose a novel technique for supporting advanced OLAP visualization of such data …

An innovative event-based lossy compression model for effective and efficient OLAP over
data streams, called ECM-DS, is presented and experimentally assessed in this paper. The …

The problem of representing and querying sensor-network data issues new research
challenges, as traditional techniques and architectures used for managing relational and …

Efficiently supporting advanced OLAP visualization of multidimensional data cubes is a
novel and challenging research topic, which results to be of interest for a large family of data …