{"id":107117,"date":"2025-09-08T09:41:28","date_gmt":"2025-09-08T09:41:28","guid":{"rendered":"https:\/\/council.science\/?post_type=publications&#038;p=107117"},"modified":"2025-10-07T10:39:44","modified_gmt":"2025-10-07T10:39:44","slug":"data-and-ai-for-science","status":"publish","type":"publications","link":"https:\/\/council.science\/publications\/data-and-ai-for-science\/","title":{"rendered":"Data and AI for science: Key considerations"},"content":{"rendered":"\n<div class=\"wp-block-group has-background\" style=\"background-color:#f9f9f9\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<p><strong>The paper is part of a series of three primers that explore various technical dimensions of AI and its impact on science:<\/strong><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><a href=\"https:\/\/council.science\/wp-content\/uploads\/2025\/10\/Types-of-AI-and-their-use-in-science-2.pdf\">Types of AI in science<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/council.science\/publications\/environmental-impact-of-ai-in-science\/\">Considerations on the environmental impact of AI in science<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/council.science\/publications\/data-and-ai-for-science\/\">Data for AI in science<\/a><\/li>\n<\/ol>\n<\/div><\/div>\n\n\n\n<div style=\"height:73px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p><strong>The first section <\/strong>introduces the foundational concepts and discusses the advantages and challenges of making scientific data AI-ready. <\/p>\n\n\n\n<p><strong>The second section <\/strong>examines the key considerations for data readiness for AI, and conversely, AI to curate data. We build on data standards while discussing AI-specific considerations such as machine-readability and bias mitigation, while highlighting ethical and environmental considerations around data readiness for AI in science. <\/p>\n\n\n\n<p><strong>The third section<\/strong> discusses data readiness within the framework of Open Science, presents two case studies that illustrate how Open Science practices can support AI-readiness for scientific research.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Recommendations<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Convergence to existing data frameworks and standards<\/strong>, for example, FAIR-R and Croissant, should be used by scientists and data stewards.<\/li>\n\n\n\n<li><strong>Data governance structures<\/strong> should go beyond technical standards to promote equity, access to compute resources, and capacity-building.<\/li>\n\n\n\n<li><strong>Investment in data infrastructure and skills development <\/strong>is a prerequisite for efficient and competitive use of AI in science.<\/li>\n\n\n\n<li>Recognition of <strong>data stewardship careers<\/strong> in science, and incentives to encourage these skills, is a cornerstone implementation pathway of the above investment.<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<div class=\"wp-block-columns is-layout-flex wp-container-core-columns-is-layout-9d6595d7 wp-block-columns-is-layout-flex\">\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:20%\">\n<figure class=\"wp-block-image size-full\"><a href=\"https:\/\/council.science\/wp-content\/uploads\/2025\/09\/Data-and-AI-for-Science-FINAL.pdf\"><img loading=\"lazy\" decoding=\"async\" width=\"446\" height=\"632\" src=\"https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1.png\" alt=\"\" class=\"wp-image-107126\" srcset=\"https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1.png 446w, https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1-212x300.png 212w, https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1-71x100.png 71w, https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1-141x200.png 141w, https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1-255x362.png 255w, https:\/\/council.science\/wp-content\/uploads\/2025\/09\/image-1-382x542.png 382w\" sizes=\"auto, (max-width: 446px) 100vw, 446px\" \/><\/a><\/figure>\n<\/div>\n\n\n\n<div class=\"wp-block-column is-layout-flow wp-block-column-is-layout-flow\" style=\"flex-basis:80%\">\n<p><strong>Data and AI for science: Key considerations<\/strong><\/p>\n\n\n\n<p>September 2025<\/p>\n\n\n\n<p>DOI: 10.24948\/2025.11<\/p>\n\n\n\n<div class=\"wp-block-buttons is-layout-flex wp-block-buttons-is-layout-flex\"><div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/council.science\/wp-content\/uploads\/2025\/09\/Data-and-AI-for-Science-FINAL.pdf\" data-content=\"Download\">Download<\/a><\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<p><em>This work was carried out with the aid of a grant from the International Development Research Centre (IDRC), Ottawa, Canada. The views expressed herein do not necessarily represent those of IDRC or its Board of Governors.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper provides an overview of the technical, ethical and environmental factors to consider when preparing scientific data for artificial intelligence (AI), and how these factors align with the \u2018Open Science\u2019 movement. The information presented is relevant to researchers, data practitioners, scientific bodies and policy-makers for science.<\/p>\n","protected":false},"featured_media":107128,"parent":0,"menu_order":0,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":""},"tags":[293,47],"publication-committee":[],"region":[],"publication-type":[469],"tag":[],"class_list":["post-107117","publications","type-publications","status-publish","has-post-thumbnail","hentry","tag-artificial-intelligence","tag-data","publication-type-discussion-paper"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.0 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Data and AI for science: Key considerations - International Science Council<\/title>\n<meta name=\"description\" content=\"This paper provides an overview of the technical, ethical and environmental factors to consider when preparing scientific data for artificial intelligence (AI), and how these factors align with the \u2018Open Science\u2019 movement. 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