Article:
Accounting for Visual Bias in Tangible Data Design

dc.creatorResch, Gabby
dc.date.accessioned2021-05-06T14:08:17Z
dc.date.available2021-05-06T14:08:17Z
dc.date.issued2019
dc.description.abstractData engagement has become an important facet of engaged citizenship. While this is celebrated by those who advocate for expanding participatory channels in civic experience, others have rightfully expressed concern about the complicated dimensions of balancing access with data literacy. If engaged citizenship increasingly requires the ability to interpret civic data through city dashboards and open data portals, then there is a concomitant requirement for diverse populations to develop critical perspectives on data representation (what is commonly referred to as data visualisation, information graphics, etc.). Effective data representations are used to ground conversations, communicate policy ideas and substantiate arguments about important civic issues, but they are also frequently used to deceive and mislead. Expanding statistical, graphical, digital and media literacy is a necessary component of fostering a critical data culture, but who are the beneficiaries of expanded models of literacy and modes of civic engagement? Which communities are invalidated in the design of civic data interfaces? In this article, I summarise the results of a design study undertaken to inform the development of accessible data representation techniques. In this study, I conducted fourteen 2-h participatory design-inspired interview sessions with blind and visually impaired citizens. These sessions, in which I iteratively developed new physical data objects and assessed their interpretability, leveraged a public transit dataset made available by the City of Toronto through its open data portal. While ostensibly “open,” this dataset was initially published in a format that was exclusively visual, excluding blind and visually impaired citizens from engaging with it. What I discovered through the study was that the process of translating 2D, screen-based civic dashboards and data visualisations into tangible objects has the capacity to reintroduce visual biases in ways that data designers may not generally be aware of.en
dc.identifier.doihttp://dx.doi.org/10.25969/mediarep/15784
dc.identifier.urihttps://mediarep.org/handle/doc/16619
dc.languageeng
dc.publishertranscript
dc.publisher.placeBielefeld
dc.relation.isPartOfissn:2364-2114
dc.relation.ispartofseriesDigital Culture & Society
dc.rightsCreative Commons Attribution Non Commercial No Derivatives 4.0 Generic
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectDatenanalysede
dc.subjectDatenvisualisierungde
dc.subjecttangible Datenrepräsentationde
dc.subjectDatenkompetenzde
dc.subjectDatenliteralitätde
dc.subjectdata analysisen
dc.subjectdata visualisationen
dc.subjecttangible data representationen
dc.subjectdata literacyen
dc.subject.ddcddc:791
dc.titleAccounting for Visual Bias in Tangible Data Designen
dc.typearticle
dc.type.statuspublishedVersion
dspace.entity.typeArticleen
local.coverpage2021-05-29T02:33:04
local.identifier.firstpublisheddoi:https://doi.org/10.14361/dcs-2019-0104
local.source.epage59
local.source.issue1
local.source.issueTitleInequalities and Divides in Digital Cultures
local.source.spage43
local.source.volume5

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