Electric vehicle advances highlight niobium's value

Significance Having fallen since 2019, the price of benchmark ferroniobium has rebounded by more than 20% since the first quarter of 2021. Investors’ excitement is tempered by the fact that the mineral is relatively scarce. There are currently only three primary niobium mines in the world. Impacts Tanzania, home to rich niobium resources, has seen a return of investor interest since the inauguration of President Samia Hassan. Echion Technologies, a Cambridge University spin-off creating niobium oxide-based materials for anodes, has closed its first funding round. Malawi has granted a mining license to the Kanyika project and could become the world’s fourth largest niobium producer.

Setting Crunchbase for Data Science: Preprocessing, Data Integration and Feature Engineering

In order to support equity investors in their decision-making process, researchers are exploring the potential of machine learning algorithms to predict the financial success of startup ventures. In this context, a key role is played by the significance of the data used, which should reflect most of the variables considered by investors in their screening and evaluation activity. This paper provides a detailed description of the data management process that can be followed to obtain such a dataset. Using Crunchbase as the main data source, other databases have been integrated to enrich the information content and support the feature engineering process. Specifically, the following sources has been considered: USPTO PatentsView, Kauffman Indicators of Entrepreneurship, Academic Ranking of World Universities, CB Insights ranking of top-investors. The final dataset contains the profiles of 138,637 US-based ventures founded between 2000 and 2019. For each company the elements assessed by equity investors have been analyzed. Among others, the following specific areas were considered for each company: location, industry, founding team, intellectual property and funding round history. Data related to each area have been formalized in a series of features ready to be used in a machine learning context.