What data infrastructure, broadly speaking, would make OWID’s work much easier and help your team investigate interesting and new data categories? For instance, what data have you found really hard to get a hold of in the past? What important data categories are particularly important but poorly organized out in the wild?
Better data publishing practices are probably the number 1 answer. My team spends heaps of time importing data that is hard to access and process, poorly documented, or contains obvious mistakes. This applies to virtually every type of data publisher, whether government, big international organizations, NGOs, companies, research teams…
Better data harmonization between governments would also be tremendously helpful. Across many topics, national agencies tend to record and analyze things differently, making the resulting figures hard to compare. Organizations like the UN, WHO, World Bank, and OECD, work hard to bridge the gap between national methodologies. Still, a world where governments would stop reinventing the wheel whenever they need to measure something would be great!
There are categories of data that are indeed still relatively inaccessible. One example is satellite data, which is “gatekept” by technological difficulty, and the existing commercial data is costly. High-quality open-domain satellite data would be an excellent opportunity to measure trends like land use, economic activity, pollution, etc.
Global energy data has also been in a strange situation for the last few years, with the data locked behind a paywall by the International Energy Agency. We’ve been campaigning publicly for this to change, and there have been encouraging signs from the IEA, but nothing concrete has happened yet.
What data infrastructure, broadly speaking, would make OWID’s work much easier and help your team investigate interesting and new data categories? For instance, what data have you found really hard to get a hold of in the past? What important data categories are particularly important but poorly organized out in the wild?
Better data publishing practices are probably the number 1 answer. My team spends heaps of time importing data that is hard to access and process, poorly documented, or contains obvious mistakes. This applies to virtually every type of data publisher, whether government, big international organizations, NGOs, companies, research teams…
Better data harmonization between governments would also be tremendously helpful. Across many topics, national agencies tend to record and analyze things differently, making the resulting figures hard to compare. Organizations like the UN, WHO, World Bank, and OECD, work hard to bridge the gap between national methodologies. Still, a world where governments would stop reinventing the wheel whenever they need to measure something would be great!
There are categories of data that are indeed still relatively inaccessible. One example is satellite data, which is “gatekept” by technological difficulty, and the existing commercial data is costly. High-quality open-domain satellite data would be an excellent opportunity to measure trends like land use, economic activity, pollution, etc.
Global energy data has also been in a strange situation for the last few years, with the data locked behind a paywall by the International Energy Agency. We’ve been campaigning publicly for this to change, and there have been encouraging signs from the IEA, but nothing concrete has happened yet.