The Web of Science Core Collection is a vast citation network representing the global landscape of science since 1900. For decades, researchers have explored this rich dataset to answer key questions about the nature of scientific discovery and innovation and to empower big data analytics. The Web of Science Core Collection contains metadata on the entire scholarly publishing landscape including over 20,000 peer reviewed journals, 180,000 conferences, and 80,000 books across all sciences, social sciences, and arts & humanities. It contains over a billion cited references, forming a giant network of interconnections between scientists, their institutions, and their disciplines. The data represent science globally, enabling the exploration of changing R&D patterns as emerging economies grow their research footprint and collaboration trends evolve. Big data techniques have opened the analytical possibilities for citation data beyond the traditional bibliometric studies into network analyses that combine citation data with datasets from other disciplines. Citation data are used by researchers in information science, computer science, business, economics, public policy, and network studies to answer questions related to scientific funding, innovation, scientific workforce, team science, etc. We will discuss the characteristics of Web of Science Core Collection data, how it is structured, and common types of analysis conducted. A sample of the raw data will be provided in advance. Participants are encouraged to explore the data in advance and bring questions to the workshop. The instructor will run through common use cases using the data.