Many Open Source Software (OSS) maintainers experience burnout due to the constant need to support and answer questions from newcomers. This leads to slower response times and unanswered queries, discouraging newcomers and ultimately hindering community growth. Research indicates that conversational agents trained on community data can answer common questions, thus reducing the workload for maintainers. However, developers require real questions from newcomers extracted from an actual project to test the efficacy and guide the development of such chatbots. To support the development of conversational agents for newcomer onboarding, we curated a dataset of varied questions from the JabRef OSS project. This dataset paper details our collection process, describes the data, and offers reflections on future research. We expect that this dataset can foster further research focused on developing chatbots to assist newcomers.