https://wiki.responsibledata.io/api.php?action=feedcontributions&user=Kanarinka&feedformat=atomResponsible Data Wiki - User contributions [en]2024-03-29T08:04:48ZUser contributionsMediaWiki 1.23.4https://wiki.responsibledata.io/Rdviz-cultureRdviz-culture2016-01-15T23:37:37Z<p>Kanarinka: added my twitter</p>
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<div><br />
== Outputs ==<br />
''Description of a minimum viable product, aspirational output, stretch goals, etc.''<br />
Collaborative website: The Inclusive Data Visualization Project<br />
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Tabs<br />
* What is inclusive data visualization?<br />
** Here we ask visitors to submit their comments about what they think of when it comes to having an inclusive data visualization field<br />
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* Exclusion by Access<br />
** Problem: Data visualization can exclude due to issues of access, including<br />
*** bandwidth and connectivity<br />
*** language/layout of tools and resources<br />
*** discriminatory hiring practices<br />
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* Exclusion by Misrepresentation<br />
** Problem: Data visualization can exclude by misrepresenting people, along the dimensions of<br />
*** gender<br />
*** ethnicity<br />
*** location<br />
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* Exclusions by Extraction<br />
** Problem: Data visualization can exclude by taking and not giving back<br />
*** form is not legible to the community<br />
*** dataviz is not shared at all<br />
*** doesn't engage the community (about, but not for or by)<br />
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* Each page has space for case studies, tools, resources, and other links<br />
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== Notes ==<br />
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Culture (producers and consumers)<br />
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Possible Outputs<br />
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* Cultural checklist or guide<br />
* Mentorship program (physical/virtual meetup space)<br />
* Human-centered design for dataviz<br />
* Manifesto<br />
** Active discussion tool/platform (wiki?)<br />
** Open source tools<br />
** “The Manifesto of the Missing People”<br />
* kids, African, Asian, etc.<br />
* here is the list of people who are not here<br />
* how do we start to include them?<br />
* Resources of/for people who have agreed to abide by it<br />
* “I’ve agreed to commit to this as part of my practice”<br />
* Tap into featured people who are already in the conversation<br />
** The Inclusive Data Visualization Project<br />
* Tell by showing—case studies; blog posts<br />
* Tools<br />
* Link dump/Resource page<br />
* Checklist <br />
* Access—low bandwidth, no English<br />
* Not seeing themselves in the data—gender, race<br />
* Seeing themselves in the eyes of others<br />
* “a sketchpad for people to say, ‘this is what I think inclusive data visualization looks like.’” ← as a sheet on the science project<br />
* Who is this for? <br />
* Practitioners <br />
* What do we want them to do? <br />
* This is what we know; what do you know?<br />
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* Mission statement<br />
* Series of blog posts<br />
* Research agenda (wiki?)<br />
* Early ed. Curriculum<br />
** Baseline data/graph literacy<br />
** Exercises targeted to different cultures<br />
** Treat data visualization as a core standard<br />
* Post-secondary education<br />
** Interdisciplinary?<br />
* Different dataviz mediums and how they are used and understood by different groups<br />
** most efficient engagement tools for different groups<br />
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== Audience ==<br />
''Personas, use cases, context''<br />
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== Next steps ==<br />
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== Contributors ==<br />
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Catherine Dignazio<br />
catherine_dignazio@emerson.edu<br />
@kanarinka<br />
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Kate Hotler<br />
@KateLovesUX<br />
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Andrew McWilliams<br />
@jahyadotnet<br />
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Jon Schwabish<br />
@jschwabish<br />
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Gabi Sobliye<br />
@seeingsideways<br />
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== Resources (we <3 links!) ==<br />
* http://civicmediaproject.org/works/civic-media-project/index<br />
* http://helpmeviz.com/<br />
* http://www.amazon.com/Whistling-Vivaldi-Stereotypes-Affect-Issues/dp/0393339726<br />
* https://civic.mit.edu/feminist-data-visualization</div>Kanarinkahttps://wiki.responsibledata.io/RdfvizRdfviz2016-01-15T23:37:01Z<p>Kanarinka: renamed culture to inclusion because that's what we actually addressed</p>
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[[File:RDFVIZ-icon.png|thumb]]<br />
This wiki was created for the participants of the Responsible Data Forum on Data visualization. We will use this for ongoing creating, sharing and collaborating.<br />
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== Information for participants ==<br />
Please make sure to send all notes and materials that are not already captured in the wiki to [mailto:notes@responsibledata.io notes@responsibledata.io]<br />
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=== Hashtags and Twitter accounts ===<br />
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Hashtags: #RDFviz and #responsibledata<br />
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[https://twitter.com/engnroom/lists/rdfviz-attendants/members Twitter list of participants]<br />
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== Spectrogram statements ==<br />
[[File:Rdfviz-spectrogram.jpg|thumb]]<br />
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=== Statements we used ===<br />
* Misleading viz for advocacy can be justified<br />
* Anyone, regardless of background, should be free and empowered to visualize data and share widely<br />
* Data visualization should always be able to be interpreted without accompanying narrative<br />
* Potential impact is more important than marginal risk<br />
* Bad dataviz is better than no dataviz<br />
* Only rigorous statistical inference should be visualized at all<br />
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=== Other statements ===<br />
* Dataviz should provoke empathy/concern<br />
* It's ok to simplify data in visualization<br />
* Visualization without uncertainty is useless<br />
* The better the visualization, the less it has a point of view<br />
* Pie charts can be useful<br />
* Dataviz should be fact-checked<br />
* Dataviz should have an emotional impact to be meaningful in storytelling<br />
* Your axes should always be labelled<br />
* Dataviz is the best way of making an argument<br />
* The more people visualize data, the better<br />
* People know how to read dataviz<br />
* Aesthetics are critical to good dataviz<br />
* Indigenous voices don't need to be visualized in this project<br />
* Objectivity is the holy grail of dataviz<br />
* The process of construction of a dataviz is more important than the outcome<br />
* The eudcational value of a viz/report/data is wholly determined by its impact on future events<br />
* Infographics are not responsible data visualization<br />
*Ethical data visualization discussions should only focus on the visual<br />
* There should be no figurative representation in data visualization<br />
* Convenience samples should not be visualized<br />
* Web mercator is great<br />
* All data should be open for viz<br />
* A good dataviz opens its data and code<br />
* All things can be visualized<br />
* Majority of dataviz is ultimately useless, if not harmful<br />
* Visualization always has a point of view<br />
* It is possible to anonymize data and still have it be useful<br />
* Everyone should learn how to visualize data<br />
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== Theme clustering ==<br />
[[File:Mushon-cluster.jpeg|400px]]<br />
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* [https://www.dropbox.com/s/ehlficyjmlv4cdm/15-01-2016%20Clustering.pdf?dl=0 View all post-its online] <br />
* [https://www.dropbox.com/s/5emkt4ss8igwqid/15-01-2016%20Clustering.zip?dl=0 Download all post-its (large download)]<br />
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== Working groups ==<br />
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=== [[ rdviz-culture | Inclusion ]] ===<br />
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=== [[ rdviz-literacy | Literacy ]] ===<br />
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=== [[ rdviz-risk | Risk ]] ===<br />
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=== [[ rdviz-transparency | Transparency ]] ===<br />
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=== [[ rdviz-uncertainty | Uncertainty ]] ===<br />
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=== [[ rdviz-goals | Goals]] ===<br />
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[[Category:RDF dataviz]]</div>Kanarinka