The field of data-driven research is witnessing a significant shift towards innovative methods of data discovery, reuse, and analysis. Researchers are developing new approaches to extract insights from large volumes of data, including the use of semantic queries, knowledge graphs, and narrative pattern mining. These advancements are enabling researchers to uncover precise connections and relationships within complex data sets, ultimately leading to more accurate and reliable scientific information. Notably, the integration of data reuse and repurposing is becoming increasingly important, with a focus on standardizing metadata, providing contextual documentation, and facilitating communication between data creators and reusers. Noteworthy papers include: Climate Data for Power Systems Applications, which demonstrates the efficacy of data repurposing for analyzing wildfire smoke impact on solar photovoltaic energy production. Querying Climate Knowledge introduces a domain-specific Knowledge Graph that supports structured, semantic queries for climate researchers.