分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-27 合作期刊: 《数据智能（英文）》
摘要： Is the evolution of how science is done primarily heuristic or driven by policy makers? Reading the intriguing story of the inception of the European Open Science Cloud (EOSC) by J-C Burgelman one could assume the latter. But the story also reveals that the policy makers shaping of concepts and planning of funding models is a mere reaction to the turns of the broad stream of research. Looking from the science side the trend towards data intensive science started for sure already in the 90s with advancements in particularly sensor technologies rapidly increasing the amount of data collected. The development of Charge-coupled Devices (CCDs) and its impact on astronomy is the often-cited example but it was a trend building up all over experimental research taking benefit of developments within fast electronics and communication, or leaps in efficiency when shifting experimental technology, e.g. going from chromatography methods to fluoresces based methods for genome sequencing. On top of it the introduction of parallel supercomputers almost completely built out of commercial off-the-shelf components enabled the possibility to actually analyse and produce data in an unprecedented cost-efficient way.
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