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Business Case
Almost everyone is likely to work with data at the JGI. Increasing data literacy at the JGI will should help people to make more rational decisions informed by using data. A first step to this is identifying which areas people feel they need help with to then target for improvement.
Child Pages
- 2017-12-06 Data science check in meeting notes
- 2017-11-22 Data science check in meeting notes
- 2017-10-20 Meeting notes - JGI data science progress check in
- 2017-10-05 Data Science All hands run through Meeting notes
- 2017-10-02 Meeting notes - JGI data science progress check in
- Analysis of JGI data science survey
- 2017-09-27 Meeting notes - JGI data science progress check in
- 2017-09-20 Meeting notes - JGI data science progress check in
- 2017-08-17 Meeting notes - JGI data science progress check in
Objective Statement
- Identify operational, skill and tool inefficiencies within the JGI. What are the roadblocks and barriers people are having? This could be access to the right data, right tools, right skills, or right people.
- Keeping people engaged by identifying which learning styles are important and work for them.
- Ensuring that people know that this is a JGI wide initiative, and there is support people for using their time for this.
Project Statement
The project will be completed when we have determined key areas related to data that can be targeted for improvement at the JGI.
Project Scope
No solutions will be implemented yet, only identifying the areas for improvement first. This limits the scope of the project and should help make it easier to complete.
1 Comment
Mike Barton
I am marking this project complete because it has completed its aims of "Identify operational, skill and tool inefficiencies related to data within the JGI". After running the JGI data science survey we have identified two main areas to focus on: