I\u2019ve been working on a small project to estimate and standardize the cost of ongoing global conflicts into a usable dataset.<\/p>\n
The goal is to take disparate public sources (SIPRI, World Bank, government data, etc.) and normalize them into something consistent, then convert into time-based metrics (per day \/ hour \/ minute).<\/p>\n
Current structure (simplified):<\/p>\n
– conflict \/ region<\/p>\n
– estimated annual cost<\/p>\n
– derived daily \/ hourly \/ per-minute rates<\/p>\n
– last updated timestamp<\/p>\n
– source references<\/p>\n
A couple of challenges I\u2019m running into:<\/p>\n
– separating baseline military spending vs conflict-attributable cost<\/p>\n
– inconsistent data quality across regions<\/p>\n
– how to represent uncertainty without making the dataset unusable<\/p>\n
I\u2019ve put a simple front-end on top of it here:<\/p>\n
https:\/\/conflictcost.org<\/a><\/p>\n Would really appreciate input on:<\/p>\n – how you\u2019d structure this dataset differently<\/p>\n – whether there are better source datasets I should be using<\/p>\n – how you\u2019d handle uncertainty \/ confidence levels in something like this<\/p>\n Happy to share more detail if helpful.<\/p>\n<\/div>\n submitted by \/u\/eisseseisses <\/a>
[link]<\/a><\/span> [comments]<\/a><\/span><\/p>
