The DNS maps human-readable identifiers to computer-friendly identifiers and relies on a reverse tree architecture to achieve this mapping. Backed by economic incentives, the DNS has become increasingly complex with data being shared among multiple au- tonomous stakeholders. The diversity of autonomous stakeholders limits data collection, access and sharing to researchers. For in- stance, each of stakeholder controls limited parts of the DNS space, thereby limiting analysis of real-world DNS behaviour. We aim to design and develop a software framework to unify diverse and large-scale public DNS data sources. The platform will facilitate the access to public DNS data by providing an efficient way of processing and analyzing large amounts of distributed data regard- less of the DNS data format. Thus, the framework will help enable reproducibility in DNS studies.