Visualization of raw material supply chains using the EU criticality datasets
Europe relies on reliable and robust knowledge on materials stocks and flows to promote innovation along the entire value chain of raw materials. The EU criticality assessment examines, every three years, issues of supply risk and economic importance of a number of non-food and non-energy candidate materials from the perspective of the European Union. The most recent criticality assessment was published in 20171. The data collected during this assessment provide a good basis for further visualizations of material supply chains and structuring additional information in the form of material and country factsheets in the EU’s Raw Materials Information System (RMIS). This study uses the existing datasets from the 2017 EU criticality assessment to visualize 74 material supply chains and shows interconnections between them. Firstly, the data sets are rearranged into a simple graph with nodes representing the countries, materials, product applications, and sectors involved in materials supply and use. The weighted edges (links) represent relationships between them, i.e., the production of materials by countries and the flow of materials into product applications and subsequent economic sectors. Secondly, because mapping the critical raw materials data considers the links between countries, materials, product applications, and sectors, the resulting graphs can also be analysed using network statistics (based on their connectivity). For this, degree centrality (a count of the number of incoming or outgoing links of a node) is used to highlight more interconnected nodes (“key actors”) in the supply and use of materials. This allows, e.g., detection of countries providing a large number of different (raw) materials4, materials finding widespread downstream uses, or product applications relying on a large number of materials. Results show that arranging data according to the proposed data structure provides a simple, yet powerful, tool to map supply chains for 74 materials with only minor adjustments to the existing data sets necessary. The resulting graphs can be readily integrated into the RMIS to provide users with insights into the origin (countries) of materials and their downstream flows into product applications and economic sectors. Furthermore, overlaying multiple material supply chains with each other allows the visualization of interconnections between materials supply chains and to view the network from the perspective of individual nodes (e.g., a sector).
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