Driller, JanaTrang, Simon Thanh-NamKlein, MaikeKrupka, DanielWinter, CorneliaGergeleit, MartinMartin, Ludger2024-10-212024-10-212024978-3-88579-746-32944-7682https://dl.gi.de/handle/20.500.12116/45139This study investigates the use of knowledge graphs to address challenges in ESG metrics extraction and reporting. However, collecting and processing ESG data from diverse IT systems is complex. Knowledge graphs offer a solution by enabling semantic modelling and data integration. This research employs a design science approach to develop a prototype knowledge graph, enhancing the accuracy and consistency of ESG reporting. The study contributes both theoretically, by advancing knowledge graph frameworks, and practically, by providing a tool for efficient ESG data management and reporting.enESG-MetricsKnowledge GraphsIT-SystemsText/Conference Paper10.18420/inf2024_1621617-54682944-7682