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The “network effect” (i.e., leveraging connections of connections) is frequently discussed by startup founders and venture capitalists. But the phrase is not typically uttered by researchers and grant funding agencies. While the business set deliberately strives to maximize customer bases and conquer markets, the scientific community cautiously works on promoting collaboration, and debates what to consider an interdisciplinary science.
Counter to that, and thanks to grassroots efforts, the past decade has seen an unprecedented growth of open sharing culture in many computational fields such as machine learning or artificial intelligence more broadly. This culture encouraged early sharing of preprints, code implementations, and online educational materials. All that sharing accelerated the pace of research as reflected in increased numbers of published papers, a dramatically reduced gap between original and follow-up work, an influx of enthusiastic young researchers, and previously unheard-of vertical and horizontal “collaboration mobility.” Computational scientists ...
