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Design Knowledge in Data Visualization: Mapping the Epistemic Landscape — arXiv:2608.08270

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.08270
License (as archived): CC0-1.0
Archived: 2026-10-19T08:59:33.166Z
SHA-256 of the archived text: 1c507991f230fed147d65d1258e65f3a927194672408c807a151c3bce63abadc
Stable URL of this page: https://metraipolis.com/documento/dc_33d239481bfa

How to cite

Design Knowledge in Data Visualization: Mapping the Epistemic Landscape — arXiv:2608.08270 — arXiv (en), https://arxiv.org/abs/2608.08270 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_33d239481bfa (Metraipolis archive dc_33d239481bfa, sha256 1c507991f230fed147d65d1258e65f3a927194672408c807a151c3bce63abadc)

BibTeX

@misc{dc33d239481bfa,
  title = {Design Knowledge in Data Visualization: Mapping the Epistemic Landscape — arXiv:2608.08270},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.08270},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_33d239481bfa; sha256 1c507991f230fed147d65d1258e65f3a927194672408c807a151c3bce63abadc},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.08270. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Data visualization research has developed many influential forms of design knowledge, including perceptual principles, design guidelines, process models, and formalized representations of design constraints. These contributions have been effective at articulating explicit, portable, and codified forms of knowledge. Yet the broader landscape on which visualization design depends remains less clearly articulated, especially with respect to intermediate-level knowledge, precedents, tacit repertoires, and situated forms of knowing. In this paper, we draw on design theory to map this broader landscape of design knowledge in data visualization. Through this lens, we show how visualization research has built substantial strengths in some regions while leaving others comparatively underarticulated. We further argue that visualization design depends not only on knowledge artifacts such as theories, guidelines, and patterns, but also on knowledge-in-use---the situated interpretation, adaptation, and coordination of multiple forms of knowing in concrete design situations. This broader account has implications for how the field conceptualizes design expertise, evaluates and develops scholarly contributions, and approaches AI-assisted design. Rather than treating visualization design as either fully formalizable or wholly resistant to computational support, we argue for a differentiated view in which computational systems can support some forms of design knowing, while others remain inseparable from human judgment, contextual interpretation, and the ongoing reorganization of design work in practice.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-08-11 in cs.HC).
Categorie arXiv: Human-Computer Interaction (cs.HC).
Pagina del lavoro: https://arxiv.org/abs/2608.08270 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-19T08:54:55.997Z dalla pagina https://arxiv.org/catchup/cs.HC/2026-08-11?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).