Boost4.0 is the biggest European initiative in Big Data for Industry 4.0. With a 20M€ budget and leveraging 100M€ of private investment, Boost 4.0 will lead the construction of the European Industrial Data Space to improve the competitiveness of Industry 4.0 and will guide the European manufacturing industry in the introduction of Big Data in the factory, providing the industrial sector with the necessary tools to obtain the maximum benefit of Big Data.

Linked-Data-basierte Kriminalanalyse (Linked Data based crime analysis)

Smoothed Analysis of Structured Machine Learning Algorithms from Knowledge Graphs.

Exploiting Oceans of Data for Maritime Applications

A Benchmark for Symbolic Supervised Machine Learning from Expressive Structured Data

A shared platform for Opening Scholarly Communication in the Social Sciences.

Domain Specific Languages for Machine Learning algorithms.

A framework for Machine Learning in Semantic Knowledge Graphs.

Benchmarking sensor data to Internet-based Geo-Services

The business engine for IoT pilots: Turning the Internet of things in Europe into an economically successful and socially accepted vibrant ecosystem.

Preserving the Evolving Data Web: Making Open / Linked Data Diachronic

A Light-Weight Interchange Format for Machine Learning Experiments

Enabling Linked Data and Analytics for SMEs by renovating public sector information

Open Data Incubator for Europe

Cognitive Robotics.

Scalable Linking and Integration of Big POI data

Experimental Analysis of Class CS Problems.

The project aims to provide a generic framework and concrete tools for supporting financial transparency, thus enhancing accountability within public administrations and reducing the possibility of corruption. A key challenge for is to provide a framework that is scalable, easy-to-use, flexible, and attractive. We will apply the project concept to three pilot scenarios targeting three different applications related to public spending: journalism, transparency initiatives and citizenship engagement. This project will involve various stakeholders, including but not limited to public administrations, citizens, NGOs, media organisations and public service companies.

Deep Fact Validation

Holistic Benchmarking of Big Linked Data

Open access infrastructure for research in Europe to manage and monitor the outcomes of European funded research.

European Data Science Academy

Big Data Europe will undertake the foundational work for enabling European companies to build innovative multilingual products and services based on semantically interoperable, large-scale, multi-lingual data assets and knowledge, available under a variety of licenses and business models

WDAqua (Answering Questions using Web Data) is a Marie Skłodowska-Curie Innovative Training Network (ITN).

The power of the qrowd combined with RDF

Question Answering over RDF Knowledge Graphs

An Open, Extensible Benchmarking Suite for Cross Domain RDF Data Management Systems


A shared framework that supports communities to create presentations collaboratively

SeReCo (Semantics, Coordination and Reasoning) is a German-French doctoral college. Its scientific purpose of SeReCo is to explore the spectrum of technologies related to semantics, reasoning and coordination in distributed and open environments (such as the Web).

Open Source Algorithms for Distributed Data Processing for Large-scale RDF Knowledge Graphs