Challenges & Objectives


datAcron addresses core challenges related to the European Big Data Vision towards increasing our abilities to acquire, integrate, process, analyze and visualize data-in-motion and data-at-rest.


The datAcron core challenges are

Distributed management and querying of integrated spatiotemporal RDF data-at-rest and data-in-motion in integrated manners:

datAcron will advance RDF data processing and spatio-temporal query answering for very large numbers of real-world triples and spatiotemporal queries, providing also native support for trajectory data, handling (semantic) trajectories as first-class citizens in data processing. In situ data processing and link discovery for data integration are critical technologies to those targets.

Detection and prediction of trajectories of moving entities in the Aviation and Maritime Domains

datAcron will develop novel methods for real-time trajectory reconstruction, aiming at efficient large-scale mobility data analytics.
Real-time trajectories forecasting for the aviation and maritime domains aim to a short forecasting horizon.

Recognition and Forecasting of Complex Events in the Aviation and Maritime Domains

datAcron will develop methods for event recognition under uncertainty in noisy settings, aiming at processing very large number of events/second with complex event definitions.
In doing so, optimization of complex events patterns’ structure and parameters by means of machine learning methods for constructing event patterns is within datAcron objectives.

Visual Analytics in the Aviation and Maritime Domains

datAcron aims to develop a general visual analytics infrastructure supporting all steps of analysis through appropriate interactive visualizations, including both generic components and components tailored for specific applications.


Real-time detection and prediction of trajectories,

Detection and prediction of important events related to moving entities,

Advanced visual analytics methods, over multiple heterogeneous, voluminous, fluctuating, and noisy data streams from moving entities,

Real-time in-situ processing of multiple data streams,

Provision of integrated views of streaming data with archival data,

Provision of advanced solutions formanaging spatio-temporal data.