Show HN: Our Bayes Impact Hackathon Project, MineData.org | Hacker News Reader

Show HN: Our Bayes Impact Hackathon Project, MineData.org

minedata.org

56 pointsphilip120917 comments

1. Let me say that it's great to see more hackers work on issues of civic interest. The data from the government, like most things in life, is messy...but the more eyes we have on it, the better potential there is for public good to come from transparent.

2. This seems like a textbook case of mapping things that don't need to be mapped. I understand this is a hackathon and showing off a simple table will cause you to lose...but the map is indecipherable...it's only because it's a commonly-used template that I can make an assumption what the zoomed-out numbers mean. But the major flaw is that the purportedly important number, the "lives-at-risk" score, is completely buried. There's no way to make an easy comparison ...I can't even tell how many mines are actually considered dangerous. I think if your aim is to shed light on what are the most dangerous mines, according to your analysis, you should at least put up a table of 50 mines, listed in descending order of "lives-at-risk"

3. What alternative methodologies did you try, and how do they compare to your score? I would guess that a simple indexing of days-since-last-inspection and number of major violations (and some factoring in of type of mine) would also be a good indicator of how risky a mine currently is.

> I understand this is a hackathon and showing off a simple table will cause you to lose

It should be noted that this particular hackathon is a data hackathon. If showing data at a data hackathon is not welcomed, that would be very ironic.

Unfortunately, "maps" or "interactive web app" have become too synonymous with "display of data"

This was unfortunately truer than it should have been. I saw two cases where truly predictive models on cleaned data sets were beaten by less informative mappings of uncleaned data.

The Github link at the bottom of the page 404's for me. https://github.com/tmsgost/Bayes_Imact

Seems to just be a misspelled "Impact": https://github.com/tmsgost/Bayes_Impact

Just pushed a fix. Thanks!

I am confused as to what data is being shown on the map. What do the numbers / colours indicate?

Is it merely plotting the number/location of mines, or does it show the "lives-at-risk" score?

It's density of mines - plotting all 6000 doesn't provide useful information. Scroll in and the pins will expand. Clicking on them will give you a link to our analysis for that mine.

I'm getting NaN on their "Calculate Lives-At-Risk Score" form.

It's working now!

How are you calculating the Lives-At-Risk Score?

The video on the analysis page explains it:

http://www.minedata.org/analysis/

We'll get the source scripts in git soon.

The Lives-At-Risk score aims to estimate the number of lives that would have been lost since the opening of a mine, in the absence of any inspections.

We decompose this into 2 parts: 1) The number of lives that have been lost, and 2) the number of lives that could have been lost.

We measure 1) using past accidents, and 2) using safety violations. We normalize safety violations according to their likelihood of occurrence, severity relative to fatality and number of people affected, as assessed by the Mine Safety and Health Administration inspectors.

Lives-At-Risk is then the sum of 1) and 2).

The IPython notebook for the calculation is now in the repo:

https://github.com/tmsgost/Bayes_Impact/blob/master/explorat...

Here's the notebook on NBViewer: http://nbviewer.ipython.org/github/tmsgost/Bayes_Impact/blob...

If you want to tag a tweet about this with #bayeshack, there is a prize for most popular project on social.

and here I thought it was about land mines.

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