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Statistics Coded – Storytelling through literate programming and runnable computing

Authors: Barrenada, Lasai; Bonamino, Luca; Derayati, Rezvan; Farias da Silva, Erico; Girardi, Mattia; Gojsic, Damir; Hadj Hassen, Sarah; +8 Authors

Statistics Coded – Storytelling through literate programming and runnable computing

Abstract

This paper introduces the so-called Statistics Coded as a way to disseminate outputs that document and share statistical processes beyond just data, but also including code, algorithms, protocols and workflows. It is introduced as a new way to communicate and interact with the public in order to improve the perception and awareness of as well as the trust in Official Statistics. The Statistics Coded enable users interactively dialoguing with data, explore, reuse and contribute to statistical products. They help them as well sharing best practices, learning from each other, and adopt common methodologies, fostering Statistical Literacy in the public. Inspired by the Open Source Software, Citizen Science and Open Science communities, the Statistics Coded present substantial promises for Citizen Statistics and the interaction between National Statistical Institutes, data users and data producers.

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Keywords

Reusability & Reproducibility, Data exploration & analysis, Do-It-Yourself Statistics, Statistical literacy, Co-design & Co-creation, Co-design & Co-creation, Reusability & Reproducibility, Data exploration & analysis, Participation & collaboration, Participation & collaboration

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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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0
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111
8
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