Data analysis plays a crucial role in helping cities become more sustainable. The access to a national public database on energy and sustainability is now possible thanks to Meta Explorer, a platform launched by researchers from the Laboratory of Industrial Ecology and Sustainability (LEIS) at IN+ – Center for Innovation, Technology and Policy Research. The main objective of Meta Explorer is to make this information more accessible to everyone and to add a georeferenced data visualization tool, to better inform local public entities and help formulate public policies.
“The platform aims to provide users with a holistic analysis of how each municipality is evolving in each sector, and not only a case-by-case analysis”, stresses Diana Neves, one of the researchers involved in the project. With this platform, the team decided to create a national database for the assessment of sustainability, making the data available in a treated and systematic way”, she adds.
The information is aggregated into different topics – electricity, buildings, mobility, waste management, resource productivity, final and primary energy – allowing the user to gradually adjust their search to the indicators available in each section.
Although the data is public, it was dispersed and in need of treatment, making it now more useful for researchers and research projects. “Meta Explorer aims to be a tool for dialogue with local and government entities, to help design public policies on energy transition, based on energy systems modeling and urban metabolism”, highlights the IN+ researcher.
This project was developed collaboratively and without funding. It emerges as an internal response to the need to improve LEIS researchers’ programming and data science skills. “We started an online joint Python learning process, establishing several intermediate goals, and with a tangible goal – the platform”, says the IN+ researcher.
“We hope to be able to raise funding to develop the platform in a more professional way and increase its functionalities, either in geographic scale granularity, or by developing new indicators, for example, socioeconomic conditions”, shares Diana Neves.
