A Claim-Centric Dataset for evaluating the contribution of Low-Temperature Plasma Science in Green Plasma Technologies

The surge in green energy initiatives has amplified interest in low-temperature plasma (LTP) based renewable energy technologies due to their potential for sustainable solutions. A structured framework is critically needed to systematically assess the current state-of-the-art, past research trends, and future potential of LTP in green energy, enabling comprehensive analysis and informed decision-making. Recognizing claims as fundamental units of scientific discourse, we introduce the first structured dataset focusing on claim extraction from scientific literature on LTP. Our approach involves a robust pipeline which includes converting scientific articles into pre-processed text, applying advanced natural language processing techniques, and utilizing a white-box weak supervision method for interpretable extraction of both numerical and qualitative claims. This claim dataset aims to provide the LTP community, policymakers, and stakeholders with a granular view of research progress, thematic trends, and emerging research areas, and ultimately aiding in evidence-based decision-making and fostering data-driven collaboration for future research directions in this area.