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How Frictionless Data can help grease your data

Authors: Granados, Monica; Zhao, Lily;

How Frictionless Data can help grease your data

Abstract

I think we have all been subject to other people’s data - the frustration and the disappointment that follows when we determine that the data is unusable. The Frictionless Data initiative at Open Knowledge Foundation aims to reduce friction in working with data, with a goal to make it effortless to transport data among different tools and platforms for further analysis, and with an emphasis on reproducible research and open data. As inaugural Reproducible Research Fellows of the program, we will demonstrate how we have applied the principles and tools of Frictionless Data to our own research data on the octopus trade and open access bibliometric data to make our data more reusable by others. This talk is aimed at all data wranglers, and along the way we will talk about our experience in the fellowship, what were some difficulties, and about our triumphs.

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open science

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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!
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