Graph databases have gained renewed interest in the last years, due to its applications in
areas such as the Semantic Web and Social Networks Analysis. We study the problem of …

Query languages for graph databases started to be investigated some 25 years ago. With
much current data, such as linked data on the Web and social network data, being graph …

We report on a community effort between industry and academia to shape the future of
graph query languages. We argue that existing graph database management systems …

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 …

In today's knowledge-, service-, and cloud-based economy, businesses accumulate massive
amounts of data from a variety of sources. In order to understand businesses one may need …

The execution of a business process (BP) in today's enterprises may involve a workflow and
multiple IT systems and services. Often no complete, up-to-date documentation of the model …

The significance of regular path queries (RPQs) on graph-like data structures has grown
steadily over the past decade. RPQs are, often in restricted forms, part of graph-oriented …

Graphs are an intuitive way to model complex relationships between real-world data objects.
Thus, graph analytics plays an important role in research and industry. As graphs often …

With the inception of the Twitter microblogging platform in 2006, a myriad of research efforts
have emerged studying different aspects of the Twittersphere. Each study exploits its own …

Graphs are essential modeling and analytical objects for representing information networks.
Existing approaches, in on-line analytical processing on graphs, took the first step by …