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Interactive plots and the spectrum of data visualization

Agah Karakuzu


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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Agah Karakuzu</dc:creator>
  <dc:date>2020-01-24</dc:date>
  <dc:description>If you can print something into a static PDF, it means that you are allowed to share data (at least) on that level. So why hide those data points in scatter plots, for example?

In this presentation, I tried to breakdown the components of a data visualization practice that facilitates the creation of "repeatable" figures.  

Bonus: Useful resources to create eye-candy infographics. </dc:description>
  <dc:identifier>https://zenodo.org/record/3841775</dc:identifier>
  <dc:identifier>10.5281/zenodo.3841775</dc:identifier>
  <dc:identifier>oai:zenodo.org:3841775</dc:identifier>
  <dc:relation>doi:10.5281/zenodo.3626744</dc:relation>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights>
  <dc:subject>Data visualization, interactive figures, plotly, dash, dashboards, data art, interactive experience, reproducibility, open science, open source</dc:subject>
  <dc:title>Interactive plots and the spectrum of data visualization</dc:title>
  <dc:type>info:eu-repo/semantics/lecture</dc:type>
  <dc:type>presentation</dc:type>
</oai_dc:dc>
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