{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T00:47:06Z","timestamp":1785890826973,"version":"3.56.0"},"reference-count":24,"publisher":"Elsevier BV","issue":"6","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T00:00:00Z","timestamp":1776988800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007917","name":"Agricultural Research Service","doi-asserted-by":"publisher","award":["58-8050-3-003"],"award-info":[{"award-number":["58-8050-3-003"]}],"id":[{"id":"10.13039\/100007917","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["cell.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Patterns"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.patter.2026.101566","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T15:03:06Z","timestamp":1781276586000},"page":"101566","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Five views on the foundations of data science"],"prefix":"10.1016","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6103-7745","authenticated-orcid":false,"given":"Bruce S.","family":"Kristal","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6476-2165","authenticated-orcid":false,"given":"Melissa D.","family":"McCradden","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2167-1343","authenticated-orcid":false,"given":"Jeyan","family":"Thiyagalingam","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2717-5033","authenticated-orcid":false,"given":"Zijun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carole","family":"Goble","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patter.2026.101566_bib1","series-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems NIPS\u201917","first-page":"6000","article-title":"Attention is all you need","author":"Vaswani","year":"2017"},{"key":"10.1016\/j.patter.2026.101566_bib2","unstructured":"Gelman, A., and Loken, E. (2013). \u201cThe garden of forking paths: Why multiple comparisons can be a problem, even when there is no \u201cfishing expedition \u201d or \u201cp-hacking \u201d and the research hypothesis was posited ahead of time. https:\/\/sites.stat.columbia.edu\/gelman\/research\/unpublished\/forking.pdf."},{"key":"10.1016\/j.patter.2026.101566_bib3","first-page":"370","article-title":"LII. An essay towards solving a problem in the doctrine of chances. By the late Rev. Mr. Bayes, F. R. S. communicated by Mr. Price, in a letter to John Canton, A. M. F. R. S","volume":"53","author":"Bayes","year":"1763","journal-title":"Philos. Trans. R. Soc. Lond."},{"key":"10.1016\/j.patter.2026.101566_bib4","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1109\/4235.585893","article-title":"No free lunch theorems for optimization","volume":"1","author":"Wolpert","year":"1997","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.patter.2026.101566_bib5","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1214\/ss\/1009213726","article-title":"Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)","volume":"16","author":"Breiman","year":"2001","journal-title":"Stat. Sci."},{"key":"10.1016\/j.patter.2026.101566_bib6","doi-asserted-by":"crossref","DOI":"10.1016\/j.patter.2020.100066","article-title":"The Discomfort of Death Counts: Mourning through the Distorted Lens of Reported COVID-19 Death Data","volume":"1","author":"Raji","year":"2020","journal-title":"Patterns"},{"key":"10.1016\/j.patter.2026.101566_bib7","series-title":"He Matapihi ki te Mana Raraunga\u201d - Conceptualising Big Data through a M\u0101ori lens","author":"Hudson","year":"2017"},{"key":"10.1016\/j.patter.2026.101566_bib8","doi-asserted-by":"crossref","DOI":"10.1038\/sdata.2016.18","article-title":"The FAIR Guiding Principles for scientific data management and stewardship","volume":"3","author":"Wilkinson","year":"2016","journal-title":"Sci. Data"},{"key":"10.1016\/j.patter.2026.101566_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.patter.2021.100205","article-title":"Algorithmic injustice: a relational ethics approach","volume":"2","author":"Birhane","year":"2021","journal-title":"Patterns"},{"key":"10.1016\/j.patter.2026.101566_bib10","series-title":"Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency","first-page":"1505","article-title":"What\u2019s fair is \u22ef fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning","author":"McCradden","year":"2023"},{"key":"10.1016\/j.patter.2026.101566_bib11","article-title":"Artificial intelligence in medicine: Overcoming or recapitulating structural challenges to improving patient care?","volume":"3","author":"London","year":"2022","journal-title":"Cell Rep. Med."},{"key":"10.1016\/j.patter.2026.101566_bib12","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1038\/s41746-021-00524-2","article-title":"Clinical impact and quality of randomized controlled trials involving interventions evaluating artificial intelligence prediction tools: a systematic review","volume":"4","author":"Zhou","year":"2021","journal-title":"npj Digit. Med."},{"key":"10.1016\/j.patter.2026.101566_bib13","doi-asserted-by":"crossref","DOI":"10.1016\/j.patter.2023.100864","article-title":"A normative framework for artificial intelligence as a sociotechnical system in healthcare","volume":"4","author":"McCradden","year":"2023","journal-title":"Patterns"},{"key":"10.1016\/j.patter.2026.101566_bib14","series-title":"ICLR 2020 Workshop on Integration of Deep Neural Models and Differential Equations","article-title":"Neural Operator: Graph Kernel Network for Partial Differential Equations","author":"Anandkumar","year":"2020"},{"key":"10.1016\/j.patter.2026.101566_bib15","series-title":"ICLR 2021 - 9th International Conference on Learning Representations","article-title":"Fourier Neural Operator for Parametric Partial Differential Equations","author":"Li","year":"2020"},{"key":"10.1016\/j.patter.2026.101566_bib16","series-title":"2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings","article-title":"Auto-Encoding Variational Bayes","author":"Kingma","year":"2013"},{"key":"10.1016\/j.patter.2026.101566_bib17","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"Lecun","year":"2015","journal-title":"Nature"},{"key":"10.1016\/j.patter.2026.101566_bib18","series-title":"Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.patter.2026.101566_bib19","first-page":"1","article-title":"Domain-Adversarial Training of Neural Networks","volume":"17","author":"Ganin","year":"2016","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.patter.2026.101566_bib20","series-title":"Proceedings of the 31st International Conference on Neural Information Processing Systems","first-page":"4768","article-title":"A unified approach to interpreting model predictions.","author":"Lundberg","year":"2017"},{"key":"10.1016\/j.patter.2026.101566_bib21","doi-asserted-by":"crossref","first-page":"686","DOI":"10.1016\/j.jcp.2018.10.045","article-title":"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations","volume":"378","author":"Raissi","year":"2019","journal-title":"J. Comput. Phys."},{"key":"10.1016\/j.patter.2026.101566_bib22","article-title":"AI-readiness for Biomedical Data: Bridge2AI Recommendations","author":"Clark","year":"2026","journal-title":"Preprint at bioRxiv"},{"key":"10.1016\/j.patter.2026.101566_bib23","article-title":"From Data Creator to Data Reuser: Distance Matters","volume":"7","author":"Borgman","year":"2025","journal-title":"Harv. Data Sci. Rev."},{"key":"10.1016\/j.patter.2026.101566_bib24","doi-asserted-by":"crossref","DOI":"10.1016\/j.patter.2021.100370","article-title":"An automated solution for measuring the progress toward FAIR research data","volume":"2","author":"Devaraju","year":"2021","journal-title":"Patterns"}],"container-title":["Patterns"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2666389926000759?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2666389926000759?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T23:54:21Z","timestamp":1785887661000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2666389926000759"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":24,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["S2666389926000759"],"URL":"https:\/\/doi.org\/10.1016\/j.patter.2026.101566","relation":{},"ISSN":["2666-3899"],"issn-type":[{"value":"2666-3899","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Five views on the foundations of data science","name":"articletitle","label":"Article Title"},{"value":"Patterns","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patter.2026.101566","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"simple-article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"101566"}}