4 ms·

What I find a bit jarring is the lack of journalistic intent in the verification of data. I know that all data visualisations start at the source - the data. T

What I find a bit jarring is the lack of journalistic intent in the verification of data. I know that all data visualisations start at the source - the data. The data comes from somewhere, and I'd really like to see data-engineer-journalists be a bit more skeptical about where that data comes from and how it was collected / sampled / modified before going into visualisations. I think that's the one part of the journalist's toolkit that hasn't made its way into the coding side yet - the ability to step back and say do we trust this data? How do we verify? Can we talk to the people who collected this? If it's collected by a government agency, under who's funding was this done? How do we fact check a graph that composes of an aggregate of population statistics, for example? In old school narrative journalism, someone (usually an intern) calls up all the sources, looks into the government departments who gives the stats, tries to find third parties from universities or other non-related parties to cross reference ideas, statements, facts. How do we do that in a data driven world? It's a good angle and someone ought look into it. Potential for more data-driven stories.

danielsf 11y ago
Author of the Medium post here... This point comes up a lot...there's a tension in making the data say something interesting that will get traffic/spread, which might undermine the rigor that goes into real data-analysis/data science/academic work. IMO, as long as we disclose the source and preface the biases/problems, I'm ok with data that isn't perfect (after all, there's no such thing as a perfect data set). The lyrical analysis that I did for rappers would never work in academia...the data set wasn't strong enough. But, it was good enough for the Internet as a side-project, and I think that most readers understood the integrity issues with the data (which I also highlighted in the narrative). But yea, really good points about journalistic standards for coders who write journalism-esque content.

danielsf 11y ago

Author of the Medium post here... This point comes up a lot...there's a tension in making the data say something interesting that will get traffic/spread, which might undermine the rigor that goes into real data-analysis/data science/academic work. IMO, as long as we disclose the source and preface the biases/problems, I'm ok with data that isn't perfect (after all, there's no such thing as a perfect data set). The lyrical analysis that I did for rappers would never work in academia...the data set wasn't strong enough. But, it was good enough for the Internet as a side-project, and I think that most readers understood the integrity issues with the data (which I also highlighted in the narrative). But yea, really good points about journalistic standards for coders who write journalism-esque content.