{"id":79405,"date":"2026-06-03T14:38:40","date_gmt":"2026-06-03T12:38:40","guid":{"rendered":"https:\/\/www.embl.org\/news\/?p=79405"},"modified":"2026-06-03T14:38:45","modified_gmt":"2026-06-03T12:38:45","slug":"the-scientists-behind-the-data-investing-in-europes-data-stewardship-workforce","status":"publish","type":"post","link":"https:\/\/www.embl.org\/news\/connections\/the-scientists-behind-the-data-investing-in-europes-data-stewardship-workforce\/","title":{"rendered":"The scientists behind the data: investing in Europe\u2019s data stewardship workforce"},"content":{"rendered":"\n

By Isabela Paredes Cisneros and Lisa Vollmar<\/em> <\/p>\n\n\n\n

Research data is only as valuable as the expertise and culture that support it. Yet across Europe, the professionals most responsible for enabling high-quality, reusable research data \u2013 data stewards \u2013 often work without standardised career paths, consistent training, or formal recognition. A new Horizon Europe project is designed to change that.<\/p>\n\n\n\n

STARDAST \u2013 STewardship And Recognition for DAta Science Talent<\/em> \u2013 is a four-year, \u20ac8 million Coordination and Support Action coordinated by the European Molecular Biology Laboratory (EMBL) and set to begin in September 2026. <\/p>\n\n\n\n

Bringing together 19 partner institutions across nine countries, including research infrastructures, universities, and companies, STARDAST combines expertise from life sciences, particle physics, linguistics, translational medicine, biodiversity, digital humanities, and industry R&D within a single, coordinated framework. <\/p>\n\n\n\n

EMBL will coordinate the project and lead its management and cascading grants operations, drawing on the expertise of its Data Science Centre<\/a>, a dedicated hub for managing, analysing, and sharing research data at scale. The centre supports researchers at EMBL through providing data management infrastructure, consulting, training, and community-building in data science.<\/p>\n\n\n\n

“Through STARDAST, we aim to bring visibility, structure, and career perspectives to the data stewardship profession, while fostering a broader conversation about how scientific support roles are recognised and valued across disciplines and sectors,” said Lisanna Paladin, Community and Internal Support Lead at EMBL\u2019s Data Science Centre. <\/em><\/p>\n\n\n\n

\u201cIn biology, discovery increasingly depends on connecting data across experiments, technologies, institutions, and biological fields,\u201d said Jan Korbel, EMBL\u2019s Head of Data Science and interim Head of EMBL Heidelberg. \u201cThis can only work if we invest in the people who ensure that research data are managed responsibly, described consistently and openly, and made AI-ready. STARDAST recognises data stewardship as an essential foundation for the future of data-driven biology.\u201d <\/p>\n\n\n\n

With its innovative approach, STARDAST places data stewards at the centre of the project: as co-creators of curricula, infrastructure tools, and policy frameworks. A central objective of STARDAST is to strengthen career development by establishing clear, structured pathways from entry-level roles to advanced positions for data stewards across sectors. At the same time, it equips researchers at all career stages with the open science competencies required in modern research.<\/p>\n\n\n\n

\u201cA strong data culture and upskilling are key elements of our company\u2019s Data & AI strategy,\u201d said Boris Adryan, Director of Data & AI Academy for Merck, one of the industry partners of the project. \u201cWe\u2019re hoping to bring the experience of the past five years to STARDAST, focusing on essential skills for data stewards in academia and industry.\u201d<\/p>\n\n\n\n

The project will develop a coordinated cross-disciplinary curriculum for data steward training, support competence centres across Europe, and embed open science and FAIR (Findable, Accessible, Interoperable, Reusable) principles throughout the research workforce. Beyond the consortium itself, STARDAST\u2019s reach extends through the membership networks of EMBL, CERN, Euro-BioImaging, CLARIN, and DARIAH to more than 25 European countries and over 70 countries globally.

The project pursues three long-term impacts: to establish sustainable pan-European infrastructure for FAIR and open science data practices, to improve research quality through standardised data stewardship, and to drive a cultural shift in which data curation and open science are formally recognised and rewarded within research careers.<\/p>\n\n\n\n

STARDAST is funded by the European Union under Horizon Europe Grant Agreement No. 101268773. Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

EMBL is coordinating STARDAST, a new \u20ac8M Horizon Europe project to strengthen data stewardship careers, FAIR data practices, and open science across Europe.<\/p>\n","protected":false},"author":120,"featured_media":79417,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[17595],"tags":[5780,19521,43,1748],"embl_taxonomy":[17359,11950],"class_list":["post-79405","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-connections","tag-data-science","tag-data-science-centre","tag-heidelberg","tag-press-release","embl_taxonomy-data-science-centre","embl_taxonomy-open-science-at-embl"],"acf":{"vfwp-news_embl_taxonomy":[17359,11950],"featured":true,"show_featured_image":false,"field_target_display":"embl","field_article_language":{"value":"english","label":"English"},"article_intro":"

EMBL brings together international partners to professionalise research data management across domains and sectors<\/p>\n","related_links":[{"link_description":"EMBL Data Science Centre","link_url":"https:\/\/www.embl.org\/about\/info\/data-science-centre\/"}],"source_article":false,"in_this_article":false,"press_contact":"EMBL Generic","article_translations":false,"languages":"","vf_locked":false},"embl_taxonomy_terms":[{"uuid":"a:3:{i:0;s:36:\"302cfdf7-365b-462a-be65-82c7b783ebf7\";i:1;s:36:\"e6ac6e6e-6386-48ff-9a0b-618e391d09bb\";i:2;s:36:\"25fd580e-8c10-43a9-bfc6-18d623679223\";}","parents":[],"name":["Data Science Centre"],"slug":"data-science-centre","description":"What > Research > Data Science Centre"},{"uuid":"a:3:{i:0;s:36:\"302cfdf7-365b-462a-be65-82c7b783ebf7\";i:1;s:36:\"bc1eaadd-1f50-4140-8e9b-e58fc33a39fc\";i:2;s:36:\"01c833a7-6d73-487f-8ef2-21cf5c82bc28\";}","parents":[],"name":["Open science at EMBL"],"slug":"open-science-at-embl","description":"What > About EMBL > 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