NeEDS · Research and Innovation Staff Exchange Network of European Data Scientists
„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“
- Период
- 2019-01-01 → 2024-10-31
- Финансиране от ЕС
- 1 168 400 €
- Участници
- 15
- Схема
- MSCA-RISE
Линиите свързват координатора с партньорите.
Накратко на български
Математическото моделиране и числената оптимизация помагат за обработката на сложни данни, като например големи мрежи или неструктурирана информация. Това позволява създаването на по-разбираеми инструменти за визуализация, които помагат на бизнеса и гражданите да вземат по-добри решения.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Research and Innovation Staff Exchange Network of European Data Scientists
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
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
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. NeEDS consists of four academic beneficiaries, eight 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.
Оригинален текст от CORDIS (на английски).
Участници
- COPENHAGEN BUSINESS SCHOOL · FrederiksbergКоординаторДания
- AGEAS SA · Bruxelles / BrusselБелгия
- BANCO DEL ESTADO DE CHILE · SantiagoЧили
- CARTO GEOGRAPHIC INFORMATION SYSTEM SOCIEDAD LIMITADA · SEVILLAИспания
- CENTRAAL BUREAU VOOR DE STATISTIEK · DEN HAAGНидерландия
- DANMARKS STATISTIK · KOBENHAVNДания
- DSB · TAASTRUPДания
- DUKE UNIVERSITY · Durham NcСъединени щати
- INETUM ESPAÑA S.A. · MadridИспания
- KATHOLIEKE UNIVERSITEIT LEUVEN · LeuvenБелгия
- REPSOL SA · MadridИспания
- TESCO STORES LIMITED · Welwyn Garden CityОбединеното кралство
- THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD · OxfordОбединеното кралство
- UNIVERSIDAD DE CHILE · SantiagoЧили
- UNIVERSIDAD DE SEVILLA · SevillaИспания
Връзки
- Виж в CORDIS
- DOI: 10.3030/822214
- http://www.riseneeds.eu
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5028fb127&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5028fe639&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5028ffd6c&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e502901b82&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e508ca5d88&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50f12f816&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50f3a1b09&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50f3cfe3a&appId=PPGMS
- https://ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e50f47bb37&appId=PPGMS
Данни: CORDIS, © Европейски съюз
