Innovation Lab: Process
We work collaboratively to help you find solutions to data science and big data problems. We can assist you on your proposal by helping create a use case prototype. And although we are not a help desk, the option to support your prototype once your proposal has been selected can be written into the proposal budget. We can partner with you on a proposal if that makes it more competitive but we are not in competition for your funding.
We support NASA initiatives encouraging open science while also preserving your intellectual property. Hence we will not release anything publicly without concurrence from the PI. If we collaborate with you on your project the results and are yours to do with as you wish.
We are a fully staffed team with eleven Innovation Lab Team members. When we are not supporting specific projects we are exploring new technologies and applying new techniques using existing use cases so that we can be ready to help advance projects when applicable.
We follow the open source model by using tools such as: Python, Jupyter, Pangeo, Intake, Dask/Xarray for parallelization and sharing developed code back into the open source git repo. We only develop new tools when necessary and use the Object Oriented framework for ease of reusability.
Code Delivery Method
Containers house packages of software and dependencies that allow the developed code to be run in any environment. Containers are also largely transferrable across platforms. For these reasons, singularity containers are used as a seamless way to facilitate the delivery of ILab code.