Results from the JWST Data Analysis User Survey
Between June 7 and August 2, 2019, we conducted an online user survey focused on our users’ needs and expectations for JWST data analysis software and training. Well over 400 users completed the survey, and the median time spent on the survey was just over 5 minutes. We greatly appreciate the response – our surveys represent a fundamental way for us make data-driven decisions.
Here is a summary of some of the survey results:
- 59% of respondents identified as faculty/staff, with the remaining being students or postdocs. We saw a similar distribution in our previous survey.
- Python is the most common language used, but more than 50% of respondents also use other major platforms (IRAF/IDL/Fortran+C) some of the time. Postdocs and students use Python at a significantly higher rate.
- Based on previous experience with other space observatories, almost 70% of users expect to start their data analysis efforts from individual, calibrated, or uncalibrated exposures. The JWST pipeline will produce higher-level products from the beginning of the mission.
- Almost 80% of users expect to download their JWST data from the archive and analyze it on a local machine.
- Users prioritize training specific to JWST, as opposed to general training in Python and non-specific analysis tools.
- Users identify a critical need for training materials that are available when needed (written documentation, help desk, colleagues, video tutorials). Scheduled training workshops are only identified as critically important by 10-20% of the community.
The results of the survey are already being used by STScI, the JWST project at GSFC, and the JWST Users Committee to help direct and prioritize efforts to develop software for use with JWST data. Follow this website and our JWST Observer social media channels for updates on the development of JWST data analysis tools.
To see the numbers for yourself, you can find more information in the slides presented to the JSTUC during their September 2019 meeting.