The variety of data is one of the most challenging issues for the research and practice in
data management systems. The data are naturally organized in different formats and …

Most of the current graph database systems have been designed to support property graphs.
Surprisingly, there is no standard specification of the database model behind such systems …

The abundance of interconnected data has fueled the design and implementation of graph
generators reproducing real-world linking properties or gauging the effectiveness of graph …

Graph is a fundamental data structure that captures relationships between different data
entities. In practice, graphs are widely used for modeling complicated data in different …

Graph data management concerns the research and development of powerful technologies
for storing, processing and analyzing large volumes of graph data. This chapter presents an …

We live in an age of so-called Big Data. The radical expansion and integration of
computation, networking, digital devices, and data storage has provided a robust platform for …

We are generating data more than ever. The ubiquity of the Internet has dramatically
changed the size, speed, and nature of the generated data. Almost every human became a …

On one hand, compared with traditional relational and XML models, graphs have more
expressive power and are widely used today. On the other hand, various applications of …

PHYLODB is a modular and extensible framework for large-scale phylogenetic analyses of
sequence based ty** data, which are essential for understanding epidemics evolution. It …

Sensor networks have recently gained a lot of attention from the research community.
Sensors are significantly resource-constrained devices and last till the depletion of their …