Knowledge Graphs are a recent and promising incarnation of database methodologies and technology, which is attracting increasing use within domains characterized by the presence of many interconnected entities, interacting via complex dynamics.
While the convergence towards a consolidated definition has not been reached yet, underlying the different notions of KGs, there is the use of graph-based data models and systems in complex domains, where the need for handling and operationalizing specific and frequently complex domain knowledge calls for smart Knowledge Representation and Reasoning (KRR) paradigms and solutions, including logic-based reasoning, graph embeddings, graph neural networks, probabilistic reasoning, handling of uncertainty, modeling of temporal graphs, and many more.
Among the broad variety of fields where KGs are finding use and adoption, their impact on the economic and financial sector will be undoubtedly a long-lasting one, due to a close fit between technology and business, as witnessed by: i) the presence of large or extreme-scale stores of economic and financial data with inherent network structure; ii) the natural emergence of complex economic, financial and more in general societal network dynamics to be modeled and captured; iii) an articulated regulatory body that defines the interactions between the involved entities (e.g., the Basel III regulation, the European Central Bank legal frameworks covering many fields such as prudential supervision of credit institutions, the Investment Firm Directive, the MiFID/MiFIR and PSD2 directives, etc.).
EcoFinKG wants to reduce the distance between the database and economics/finance communities, sustaining new research-backed economic and financial applications that awarely use and demystify state-of-the-art data technology.