The field of data integration and blockchain research is moving towards increased interoperability and accessibility. Researchers are developing platforms and frameworks that enable the seamless discovery, integration, and visualization of information from different domains. This is being achieved through the adoption of globally recognized ontologies and interoperable data standards, which allows for the democratization of data use and enables researchers, policymakers, and the public to gain meaningful insights and make informed decisions. Furthermore, the development of affordable and high-quality blockchain data collection frameworks is transforming the field by providing a practical alternative for researchers and developers with limited budgets. Additionally, the integration of large language models into qualitative research is being explored, with a focus on responsible and transparent usage. Noteworthy papers include: LLM-Assisted Thematic Analysis, which investigates the opportunities and limitations of integrating large language models into thematic analysis. Multiple Sides of 36 Coins, which presents a longitudinal measurement study of 36 public blockchain networks, providing insights into network size, IPv4 versus IPv6 usage, and geographic concentration.