A growing gap between progress in biological knowledge and improved health outcomes inspired the new discipline of translational medicine, in which the application of new knowledge is an explicit part of a research plan. Abramson and Parashar argue that a similar gap between complex computational technologies and ever-more-challenging applications demands an analogous discipline of translational computer science, in which the deliberate movement of research results into large-scale practice becomes a central research focus rather than an afterthought. We revisit from this perspective the development and application of grid computing from the mid-1990s onwards, and find that a translational framing is useful for understanding the technology’s development and impact. We discuss how the development of grid computing infrastructure, and the Globus Toolkit, in particular, benefited from a translational approach. We identify lessons learned that can be applied to other translational computer science initiatives.

生物学知识进步与健康状况改善之间的差距越来越大，激发了转化医学新学科的兴起，在新学科中，新知识的应用是研究计划的明确组成部分。Abramson和Parashar认为，复杂的计算技术和越来越具有挑战性的应用程序之间的相似鸿沟要求转换计算机科学领域具有相似的学科，在该学科中，将研究结果有意识地转移到大规模实践中成为了研究的重点而不是事后思考。 。我们从这个角度重新审视了1990年代中期以来网格计算的开发和应用，发现转换框架对于理解技术的发展和影响很有用。我们讨论了网格计算基础架构的发展，特别是Globus Toolkit受益于翻译方法。我们确定可以应用于其他转换计算机科学计划的经验教训。