Embracing disciplinary diversity in visualization

  author   = {Losev, Tatiana and Raynor, Justin and Carpendale, Sheelagh and Tory, Melanie},
  journal  = {IEEE Computer Graphics and Applications},
  title    = {Embracing disciplinary diversity in visualization},
  year     = {2022},
  note     = {Preprint: \url{https://osf.io/kdws9/}},
  number   = {6},
  pages    = {64--71},
  volume   = {42},
  abstract = {Visualization is inherently diverse and is employed in countless domains to enable meaningful interactions with data. There is tremendous opportunity in embracing disciplinary diversity to widen the pool of contributions to visualization design, research, and practice. We describe a few examples of diverse approaches: scientific method, design studies, tool building, participatory research, and co-design with communities, data storytelling, and autographic design. We discuss opening the aperture, pushing back on what we, as a community, deem acceptable and rigorous, and what can be gained through greater inclusivity of approaches.},
  doi      = {10.1109/MCG.2022.3209605},
  series   = {CGA},

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