A media-driven knowledge graph describing Estonia's economic development and its governance solutions

This research project focuses on creating a knowledge graph to describe the development of the Estonian economy and technology through media content, while also addressing the governance and management challenges of such decentralized knowledge graphs. The project builds on the concept of the Semantic Web, where data structures link entities such as individuals, institutions, and topics, allowing for the exploration of their relationships and dynamics over time. A previous pilot study on cultural topics highlighted the need to extend knowledge graphs across various media sources and topics, with this project focusing on economic and technology journalism. The primary objective is to develop a linked dataset combining content from the Estonian Public Broadcasting (ERR) and the Estonian National Library's Digar database. This dataset will map Estonian entrepreneurs, other economic actors, institutions, places and topics, while linking them to economic data from Statistics Estonia and Eurostat. This will allow for the analysis of economic trends and the prediction of patterns in the spread of ideas and innovations. Additionally, the new knowledge graph will support the training of generative AI models specific to Estonia, improving machine learning models' sensitivity to cultural and economic contexts. The project also addresses the challenges of managing and governing knowledge graphs, such as ensuring data quality, security, and interoperability across various institutions. It seeks technical and legal solutions for adding data and defining usage rights, especially when the dataset is used in commercial applications. This project will provide broader benefits for the development of Estonia's data economy by publishing the datasets as open data, enabling the creation of new research and IT services, and offering significant public value.