We live in an era of accelerating data generation. The sizes of datasets keep growing and so does their structure. Despite the continuously growing capacity of computers real-world datasets surpass the limits of in-memory processing of even larger commercially available computers, and so data manipulation and analysis has to be aided by the use of databases.

The growth of published science in recent years has escalated the difficulty that human and algorithmic agents face in reasoning over …

Science is an engine of innovation and economic growth and a pathway to prosperity for countries around the world. The increasing …

In this article we present an unsupervised low-frequency method aimed at detecting and disaggregating the power used by Cumulative …

Adoption of smart meters is a major milestone on the path of European transition to smart energy. The residential sector in France …

Scientific Named Entity Referent Extraction is often more complicated than traditional Named Entity Recognition (NER). For example, in …

The ever-increasing amount of published academic results poses a challenge in interpretation and validation of these publications and …

The ever-increasing amount of published science poses a challenge in interpretation and validation of these publications and the …

A Gentle Introduction to Knowledge Graphs

In this talk we discuss utility of graph databases using the example of ArangoDB.