For 2021, the Metabolism of Cities team has developed a priority plan in order to focus most of our energy on a specific project. After lengthy discussions within our team, we have decided to prioritize taking our Data Hub to the next level. Most importantly, after last year's focus on setting up the data collection and data processing tools and courses, we now want to look at the next phase. What do we do with data? How can we create analytical tools and academic applications that make the most out of the data hub? This is what we want to look into. The following core objectives have been defined.

MFA integration

Currently, the system allows for individual datasets to be uploaded. While it is technically possible to upload material flow analysis (MFA) data, the system does not yet provide the tools to classify data accordingly. We should be able to automatically calculate indicators, to identify data gaps, and to visualise the MFA as a whole (including sankey diagrams). Ideally, we would also allow people to create and manage their own private projects, where they can upload their own datasets without them necessarily becoming part of the public data repository (unless they want to). This is a bit like the OMAT system we had before.

Multi-scale integration

Our reference spaces can record data and information about any scale... from enterprise level to country level. It is now time to fully integrate a number of these different scales. The IRP has released a global material flows database at country-level. This can be used to add MFA data to all countries in our system. Secondly, we should load the economy-wide MFAs done on city level (many of which exist in the academic literature), and encourage our colleagues at Metabolism of Islands to also load these into their system. Once we have these different scales loaded with data, we can start connecting the scales, in order to record the relationship between e.g. a city, a province/state, a country, and a continent. Downscaling (or upscaling) should be possible, as a way to estimate numbers if accurate data is not (readily) available.

API and data export development

It should be possible to export data from our website into other applications. A low-hanging fruit is to export our data in a standard CSV format, and to integrate them with Jupyter notebooks, which would allow researchers to run more advanced analyses and modeling tools written in Python, using our data and this open source platform. We can also consider options for people to embed our charts, maps, and data onto their website (akin to how Our World in Data allows you to embed their charts).

NOTE: we will be adding relevant tasks in the list below over the coming weeks (April 2021). Please stay tuned for this.