{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T05:41:11Z","timestamp":1772343671288,"version":"3.50.1"},"reference-count":126,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T00:00:00Z","timestamp":1762300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hong Kong Research Grant Council Theme-based Research Scheme","award":["T43-513\/23-N"],"award-info":[{"award-number":["T43-513\/23-N"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Data"],"abstract":"<jats:p>The transformative potential of big data across various industries has been demonstrated. However, the data held by different stakeholders often lack interoperability, resulting in isolated data silos that limit the overall value. Collaborative data efforts can enhance the total value beyond the sum of individual parts. Thus, big data sharing is crucial for transitioning from isolated data silos to integrated data ecosystems, thereby maximizing the value of big data. Despite its potential, big data sharing faces numerous challenges, including data heterogeneity, the absence of pricing models, and concerns about data security. A substantial body of research has been dedicated to addressing these issues. This paper offers the first comprehensive survey that formally defines and delves into the technical details of big data sharing. Initially, we formally define big data sharing as the act of data sharers to share big data so that the sharees can find, access, and use it in the agreed ways and differentiate it from related concepts such as open data, data exchange, and big data trading. We clarify the general procedures, benefits, requirements, and applications associated with big data sharing. Subsequently, we examine existing big data-sharing platforms, categorizing them into data-hosting centers, data aggregation centers, and decentralized solutions. We then identify the challenges in developing big data-sharing solutions and provide explanations of the existing approaches to these challenges. Finally, the survey concludes with a discussion on future research directions. This survey presents the latest developments and research in the field of big data sharing and aims to inspire further scholarly inquiry.<\/jats:p>","DOI":"10.3390\/data10110182","type":"journal-article","created":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T13:19:29Z","timestamp":1762348769000},"page":"182","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Big Data Sharing: A Comprehensive Survey"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4727-4856","authenticated-orcid":false,"given":"Shan","family":"Jiang","sequence":"first","affiliation":[{"name":"School of Software Engineering, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ajagbe, S.A., Mudali, P., and Adigun, M.O. 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