  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.
