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

Kerk F. Kee, Mona Sleiman, Michelle Williams, Dominique Stewart

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations


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.

Original languageEnglish
Title of host publicationProceedings of XSEDE 2016
Subtitle of host publicationDiversity, Big Data, and Science at Scale
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450347556
StatePublished - Jul 17 2016
EventConference on Diversity, Big Data, and Science at Scale, XSEDE 2016 - Miami, United States
Duration: Jul 17 2016Jul 21 2016

Publication series

NameACM International Conference Proceeding Series


ConferenceConference on Diversity, Big Data, and Science at Scale, XSEDE 2016
Country/TerritoryUnited States


  • Diffusion of Innovations theory
  • Innovation attributes
  • Qualitative organizational studies
  • Science & technology studies
  • Strategic diffusion
  • Technology adoption


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