The digital transformation is rapidly reshaping the landscape for users and producers of data across Europe and globally. New technologies for data processing, analysis, and communication are essential to support data-driven decision-making. However, companies and public sector institutions across Europe often lack the ability to build the necessary capabilities quickly enough. Addressing this challenge is central to the multidisciplinary and intersectoral NeEDS consortium.
All NeEDS partners share the common goal of strengthening European innovation capacity in Data Science. Industrial participants have emphasized that building more Data Science expertise is vital to the long-term success of their enterprises and the broader European economy. NeEDS' research is also relevant to citizens, who generate data through mobile use and social networks, consume data visualizations, and are influenced by models based on data such as demographics, finances, and education levels. This generates demand for user-friendly visualization tools and models that comply with the EU’s right-to-explanation regulation introduced in 2018.
Scientifically and technologically, challenges arise from complex raw data (e.g. large-scale, network-type, time-evolving, hierarchical, multivariate, unstructured, or noisy), new demands (e.g. interpretable or personalized models, or models under strict time constraints), and the need for nonexperts to visualize and interact with extracted knowledge. Meeting these challenges requires innovative mathematical modeling and advanced numerical optimization methods to create new Data Science tools that outperform the current state-of-the-art and become core skills for an increasingly mobile workforce.
NeEDS achieved its objectives through international and intersectoral mobility of both experienced and early-stage innovation and research staff. Over 100 person-months of secondments were implemented, involving researchers from academia and industry across Europe, the USA, and Latin America. These secondments enabled knowledge exchange between disciplines (Business Analytics, Computer Science, Operations Research), sectors (academia and industry), and locations. PhD students and postdocs tackled real-world challenges from industry and the public sector and developed valuable transferable skills. Industry professionals upgraded their competencies with the latest academic developments in Data Science. Senior academic and industry colleagues engaged in knowledge transfer activities, enhancing mutual understanding—especially regarding Explainable Artificial Intelligence. Short videos of these secondments are available on the NeEDS website and have been actively promoted on social media.
Further objectives were achieved through NeEDS events, including modeling weeks, PhD schools, workshops, and conferences. During modeling weeks and hackathons, PhD students worked in teams under the supervision of academic and industry professionals to solve real-world problems presented by NeEDS’ industrial partners and others. These events offered students valuable career development opportunities and gave companies exposure to emerging talent.
NeEDS has contributed to advancing the state-of-the-art in Data Science by addressing open research questions. It has developed and released open-source software tools, expanding the toolkit available to researchers and practitioners. It has also enhanced knowledge transfer between academic and industrial stakeholders, helping to build stronger Data Science capacity across Europe
