Kontakt: Germán Johannsen
The data economy offers great potential for emerging economies to achieve sustainable development goals (SDGs). However, data-sharing policies must be properly framed to leverage this potential. This is the starting premise of the international research project led by the Max Planck Institute for Innovation and Competition, in collaboration with international partners, called "Data Sharing in Emerging Economies". The project aims to define a holistic normative regulatory theory on promoting data sharing that will help to fulfil SDGs. Furthermore, it aims to develop specific policies for data sharing in emerging economies and, ultimately, provide assistance for possible legal reforms. The partners taking part in the project are Université Virtuelle du Sénégal, BML Munjal University of India, and Mackenzie University of Brazil.
For Brazil, the project’s main focus is on Climate Action (SDG 13) due to its relevance for the country and the world, the limited progress in environmental goals reported so far, and the great potential to advance in this area by fostering the data economy. Given the scope of the topic, the project is narrowed down to address environmental issues from a territorial perspective, taking into account the interrelation between agricultural production, transportation processes, and product consumption in cities. This opens up questions on how agribusiness and (city) consumption impact climate change, a matter related to economic growth (SDG 8) and responsible consumption and production (SDG 12). It also raises questions about the impact of climate change on rural and urban life, which connects to issues of deforestation and life on land (SDG 15), and how to promote sustainable and clean cities (SDG 11). All of these are relevant topics on the Brazilian policy agenda.
In its first stage, the project will be focused on the Amazon and São Paulo regions, each with its own rural/urban dynamics, but also interconnected along the national agribusiness product value chain. As evidence shows, agribusiness is one of Brazil’s main economic sectors, accounting for about 21% of GDP in 2018. It is also one of the sectors with the greatest potential to reduce greenhouse gases (GHG). A major source of pollution is beef herds, whose exploitation also relates to illegal deforestation actions. As noted by the OECD, while combating illegal deforestation is a priority, digital technologies based on big data and machine learning are also key to increasing farming efficiency and thus contributing to climate action. Finding more evidence on how data-sharing initiatives can promote green production and growth, as well as what the policy and technical challenges are to making this happen, are concrete goals of the project.
So is identifying the extent to which data-sharing initiatives may help to foster a greener consumption culture. Evidence shows that cities are responsible for rapid GHG effects. How products are transported to urban areas, what the consumption habits of individuals are, and how waste is disposed of and/or reused, are key questions related to goods’ life cycle and their environmental impact. The project aims to explore data-related initiatives with the potential to mitigate the impact of consumption and waste in São Paulo. So far, indicators and programs related to climate action exist, as well as some initiatives, like platforms for agriculture product traceability that can improve the consumer decision-making process and tax collection. The project aims to identify further data-related initiatives —market and non-market based— that can benefit from data sharing, such as platforms to collate data on food loss, waste, and surplus, or data sharing for the process of waste-separate collection.
This exploratory research will take the form of a workshop with stakeholders from academia, the public sector, civil society, and industry. It will be held on 15-16 December 2022, at the premises of the Mackenzie University in São Paulo. Stakeholders are kindly invited to contribute by providing insights regarding: (1) business models used and market realities; (2) existing legal and technical impediments to data sharing; and/or (3) the role they foresee of policy- and lawmakers for any future policy or legislative action.