The Project

NeEDS Project Summary

NeEDS responds to the massive scientific and technological challenges that the very rapidly growing field of Data Science has created for users and producers of data in Europe and world-wide. The challenges stem from the complexity of the data, the completely novel questions posed to data scientists, as well as the need of non-experts to visualize and interact with the knowledge extracted from data in order to aid data-driven decision-making. Companies and public sector bodies around Europe find they cannot build up the required capabilities quickly enough, and Europe is remarkably behind US academia in increasing Data Science capacity. NeEDS provides an integrated modelling and computing environment that facilitates data analysis and data visualization to enhance interaction. NeEDS brings together an excellent  interdisciplinary research team that integrates expertise from three relevant academic disciplines, Mathematical Optimization, Visualization and Network Science, and is excellently placed to tackle the challenges. NeEDS develops mathematical models, yielding results which are interpretable, easy-to-visualize, and flexible enough to incorporate user knowledge from complex data. These models require the numerical resolution of computationally demanding Mixed Integer Nonlinear Programming formulations, and for this purpose NeEDS develops innovative mathematical optimization based heuristics.

The NeEDS consortium consists of four academic beneficiaries, nine industrial beneficiaries (from industry sectors ranging from energy, retailing, insurance to banking, as well as national statistical offices), two academic partners and one industrial partner from five EU countries, USA and Latin America with strong and complementary expertise. With this composition, NeEDS is in a unique position to deliver cutting-edge multidisciplinary research to advance academic thinking on Data Science in Europe, and to improve the Data Science capabilities of industry and the public sector.

NeEDS Objectives

This network addresses the urgent need for an integrated modelling and computing environment that facilitates data processing, data analysis and data communication (in the form of visualization and human-computer interaction) to aid decision making.

The main scientific and technological objectives of NeEDS are to develop innovative mathematical optimization models and high performance algorithms

  • for novel applications involving Network Science;
  • to ensure Interpretability, fulfilling the right-to-explanation in algorithmic decision making required by the EU as of 2018, but also required when nonexperts are to interact with data analysis tools;
  • to deal with the challenges posed by Complex Data such as time-evolving data, spatial data, and process data;
  • to Extract Knowledge from data by jointly addressing data processing and data analysis.

NeEDS bridges the disciplines of Computer Science, Business Analytics, Mathematical Optimization and Statistics to achieve a breakthrough that requires an interdisciplinary approach, namely, the development of computational methods that are easy-to-interpret and easy-to-interact with, that run under strict time regulations, and that can cope with uncertainty in data fluctuation.


NeEDS Research Work Packages

Work Package 1 (Lead: Katholieke Universiteit Leuven)
Developing innovative tools to tackle Network data

Work Package 2 (Lead – Copenhagen Business School)
Cutting-edge modelling to enhance Interpretability

Work Package 3 (Lead: University of Oxford)
Addressing the challenges of Complex data arising in Industry

Work Package 4 (Lead: University of Seville)
Innovative Extraction of knowledge by jointly addressing data processing and data analysis