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Comment by thebent | Hacker News Reader

Would love to better expose our data set. It’s a bit tricky however: we’re specifically interested in enterprise software engineering (the patterns of which differ radically from the open source world).

In order to dig into enterprise data, we sort of need to have a ToS that only allows us to talking abstractly about aggregate data.

Any thoughts on how we might navigate that?

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You don't have to expose the raw dataset explicitly, but you do need to describe your methodology (moreso than an arbitrary "impact" score; give a formula) and give actual numbers for the analysis, and not just argue a "strong correlation" with a highly arbitrary matrix of attributes.

It's a marketing article - trying to explain their product to potential customers, not a scientific publication.

I'm not saying that you are necessarily wrong but I do wonder if making an article like this more like a formal publication will actually make it better or worse at it's real goal which is presumably to sell more.

Yes, the standards of an marketing article are nonacademic, but you can't make a article containing a data driven argument and skimp on both the data and the argument.

There is no downside to a legitimate marketing article to make the underlying data and analysis available to those who want to drill down. If it is valid, you stand a chance of persuading the skeptics.

More importantly, calling something a marketing article does not immunize it from critical analysis, and especially not on a forum such as HN.

I don't know if it's respectable to doll up a marketing article like journalism, let alone scientific research.

They go into slightly more detail on factors that influence the impact rating in a linked post. It still doesn't explain what formula or weightings they use. https://blog.gitprime.com/impact-a-better-way-to-measure-cod...

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