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Based on harnessing the power of millions of volunteers globally, the data production process is decentralized and reflects a mosaic of individual contributors\u2019 skills, motivations, and experiences. Linus\u2019 Law, a widespread assumption within open-source communities, suggests that data quality increases with the number of contributors. In this paper, we evaluate Linus\u2019 Law as applied to the co-production of volunteered geographic information using an agent-based model and examine the effects of knowledge level, variability, and prioritization on emergent production patterns and overall data quality. Our results demonstrate how diminishing returns and the experience of contributors limit Linus\u2019 Law as an intrinsic assessment of data quality.<\/jats:p>","DOI":"10.1007\/s10588-023-09383-6","type":"journal-article","created":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T02:01:45Z","timestamp":1692583305000},"page":"173-186","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Is more always better? 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