Policy Priority Inference, SDGs, Turing Institute, GPRAMA & StratML

This sounds like a very good project: Policy Priority Inference (PPI) - 
the software uses agent-based modeling to predict what would happen if 
policymakers spent money on one project rather than another.

Apparently, it will be applied to the UN's Sustainable Development Goals 
(SDGs).  However, as the article 
<https://www.technologyreview.com/2020/05/29/1002404/united-nations-computer-agents-simulation-boost-global-sustainable-development-goals/> 
points out: "Models are only as good as the data put into them ... and 
some governments will be more willing than others to provide it."

The performance of such models could be greatly enhanced via application 
of the good practice set forth for U.S. federal agencies in section 10 
<https://www.linkedin.com/pulse/open-machine-readable-government-owen-ambur/> 
of the GPRA Modernization Act (GPRAMA).

It will be interesting to see whether the PPI pilot governments -- 
Mexico, Uruguay & Colombia -- as well as the UK’s Department for 
International Development will publish their performance reports in an 
open, standard, machine-readable format.  Imagine the gains in insight 
that could be achieved if all public agencies and NGOs were to do so 
around the world.

In the meantime, the Alan Turing Institute's about statement is now 
available in StratML format at https://stratml.us/drybridge/index.htm#ATI2

BTW, of course, I am highly biased, but with so many brilliant people 
and well-funded organizations focusing on AI, it seems to me the 
greatest value we might add is to encourage and enable them to publish 
their plans in StratML format. It would be nice to think the W3C might 
be up to the challenge of leadership in that regard.

Owen