These use cases describe how scientists analyze large amounts of scientific data. The data is typically large in volume (larger than one would use on a personal or business computer), but is organized and stored in different ways for different kinds of research. Data might be generated by a single source (a large simulation, for example) or it might come from many sources (observational results from many different instruments or different research teams). The methods of analysis also vary from field to field and problem to problem.
Use Case ID | Title | Use Case Description |
---|---|---|
DA-01 | Discover data analysis resources and documentation | |
DA-02 | Prepare data for analysis | |
DA-03 | Analyze data from research instruments | |
DA-04 | Analyze data generated by a simulation | |
DA-05 | Steer a large computation while it runs | |
DA-06 | Time-critical data analysis | |
DA-07 | Run an interactive data science application using a community resource for back-end computation |
Use Case ID | Title | Use Case Description |
---|---|---|
DA-01 | Discover data analysis resources and documentation | |
DA-02 | Prepare data for analysis | |
DA-03 | Analyze data from research instruments | |
DA-04 | Analyze data generated by a simulation | |
DA-05 | Steer a large computation while it runs | |
DA-06 | Time-critical data analysis | |
DA-07 | Run an interactive data science application using a community resource for back-end computation |