EmpiRE-Compass: A Neuro-Symbolic Dashboard for Navigating the Knowledge Landscape of Empirical Research Practice in Requirements Engineering

About the Project EmpiRE-Compass is a neuro-symbolic dashboard that facilitates the exploration, synthesis, and reuse of knowledge about empirical research practice in Requirements Engineering (RE). It integrates two complementary layers: A symbolic layer based on the Open Research Knowledge Graph (ORKG) for structured, machine-actionable knowledge, and a neural layer leveraging large language models (LLMs) to answer both predefined and custom competency questions. This dual approach enables researchers to navigate the evolving knowledge landscape of empirical research practice in RE, identify reusable insights across publications, and promote Open Science through transparent, interoperable knowledge representations. EmpiRE-Compass currently focuses on two themes: Empirical research practices in RE using KG-EmpiRE, and empirical research practices in Natural Language Processing for RE using the NLP4RE ID Card. Key Features EmpiRE-Compass offers a rich set of capabilities to support exploration, synthesis, and reuse of knowledge about empirical research practice in RE. Its exploratory visual analytics provide detailed insights into the state and evolution of the field through interactive charts and distributions. The platform’s neuro-symbolic synthesis combines structured knowledge graphs with neural large language models to answer competency questions, interpret findings, and support contextual knowledge integration. All structured data, SPARQL queries, analyses, and interpretations are openly available to foster replicable research and long-term reuse. EmpiRE-Compass is built on FAIR principles — ensuring that knowledge is findable, accessible, interoperable, and reusable — and is grounded in Open Science values of transparency, ethical attribution, and collaborative maintenance. Developed on top of the ORKG and supported by TIB, the platform is designed for community-driven contributions and long-term sustainability.