Background: New technology and increased collaboration have revolutionized how scientists work with data. This creates a need to identify new aspects of working with scientific data that are important for K-12 students to learn. Purpose: To address this need, we conducted a study with practicing scientists and K-12 science teachers. The purpose of the study is to identify new aspects of working with scientific data and the strategies involved in those aspects, which are potentially important for students to learn. The research questions are: (1) How do scientists work with data in their scientific inquiry? (2) What strategies used by scientists to work with data do not commonly appear in the science teachers' class? Sample: In the study, 15 practicing scientists and 11 science teachers each participated in a one-on-one interview; and 40 practicing scientists and 175 science teachers each completed a survey. Design and methods: We first developed an initial model of working with data based on relevant literature. Next, we conducted a two-stage sequential study. At the exploration stage, we interviewed 15 practicing scientists and 11 science teachers and used the interview data to revise the initial model. At the investigation stage, we conducted surveys with 40 practicing scientists and 175 science teachers. Based on the survey data, we revised and finalized the model. Results: The study generated an empirically grounded model that contains five aspects of working with scientific data: purposes of data analysis, planning data collection, organizing and reducing data, representing data, and interpreting analysis results. For each aspect, we identified the strategies used by scientists and investigated whether and how those strategies were taught in science classrooms. Conclusion: The results provide a foundation for future research on whether and how the new aspects of working with data can be taught in K-12 science classrooms.