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Presentation . 2021
License: CC BY
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License: CC BY
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Data visualization and crowdsourced research: experiments in collective storytelling

Authors: Steele, Anne Lee;

Data visualization and crowdsourced research: experiments in collective storytelling

Abstract

These days, everyone seems to trying to harness the power of the crowd. Amnesty International’s “Decoders” brings together “digital volunteers to tackle human rights abuses around the world”. Bellingcat crowdsources information for their online investigations, and has transformed their newsroom into an open source project. Amazon’s Mechanical Turk has long altered how research is conducted through their crowdsourcing marketplace. These tools have paved the way for new kinds of journalism and research, where theoretically anyone can contribute to projects from anywhere around the world. However, while crowdsourcing has grown as a source of data, visual storytelling has usually been left out in the process. Online tools like Datawrapper and Tableau have made data visualization easier than ever, but because storytelling with data is computationally expensive – and usually custom-made for the story – the crowdsourcing process has usually been completed before it is turned into a visual design. They don’t usually walk in lockstep with each other. This talk will attempt to bridge this gap, if only just a little. It reviews a project called supply-chains.us, which is building a sustainable open-source database that anyone can contribute to, with an integrated visualization that updates over time. This talk will describe how the project was built, why visual storytelling is important for research, and how open-source projects can be an opportunity for collective storytelling.

Keywords

csv conf, supply chains

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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