Survey - draft - merged version
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Which "frontier" is your data analysis associated with? (See https://snowmass21.org/ for details) *
What specific experiment/project is your analysis associated with? *
What best describes your current position? *
What fraction of your time do you spend on analysis? *
What year was your first analysis? (Only need to indicate the year) *
MM
/
DD
/
YYYY
Briefly describe your current involvement in analysis and what your analysis focuses on. *
What data storage format do you run most of your own code on? *
How much storage space do you need for the files you create for the analysis? (in GB)
What are the final outputs you make? (check all that apply)
What language(s) do you use to analyze data? *
Required
Which of these packages do you use in your workflow? *
Required
Do you use any of the following in your job submission? *
Required
Rank the importance of the following computing resources to your analysis. *
Not important
Somewhat important
Very important
Critical
Smartphone/tablet
Personal laptop
Workstation
"Group" cluster (not shared with lab/university)
University/lab cluster CPU
University/lab cluster storage
Grid CPU
Grid storage
Rate how easy it is to deal with the following elements in your analysis. *
Super simple
Not bad
Annoying
Very frustrating
Dataset bookkeeping
Data retrieval
Storage of job outputs
Submission of jobs
Diagnosing failed jobs
Testing & validating code
Sharing code with collaborators
Sharing job environments with collaborators
Sharing datasets with collaborators
Coordinating development with collaborators
Documenting code & workflow
Getting started again after a pause
Reproducing someone else's results
What types of collaborative software do you use while writing/running analysis?
What's your favorite piece of software that you wish others knew more about? What's great about it?
If you could improve one thing in your analysis chain, what would it be?
How did you learn to do analysis? Was it formal (classes, etc.) or informal (e.g. got examples from others)? What was useful, and what was missing?
If you had 10 times your current data volume to analyze, what would go wrong?
If you are interested in giving a brief report at the virtual Computing Frontier meeting (Aug 10-11), please leave your email below.
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