The 10 attributes that drive adoption and diffusion of computational tools in e-science

As the computational movement gains more traction in the scientific community, there is an increasing need to understand what drives adoption and diffusion of tools. This investigation reveals what makes a computational tool more easily adopted by users within the e-science community. Guided by Rogers's [1] Diffusion of Innovations theory, we set out to identify the innovation attributes of a range of computational tools across domains. Based on 135 interviews with domain scientists, computational technologists, and supercomputer center administrators across the U.S. and a small portion from Europe, systematic analysis revealed 10 key attributes of tools. They are: driven by needs, organized access, trialability, observability, relative advantage, simplicity, compatibility, community-driven, well-documented, and adaptability. We discuss the attributes in the form of questions stakeholders should keep in mind while designing and promoting the tools. We also present diffusion strategies associated with each attribute. The 10 attributes and associated questions can serve as a checklist for e-science projects that aim to promote their computation tools beyond the incubators. This paper is submitted to the "Software and Software Environments" track because it has implications for engagement of user communities.