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@@ -8,14 +8,14 @@ and usage cases, rather than on the implementation details.
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### Jon the Academic Data Scientist
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-Jon is a academic researcher and data scientist. He has been using the Jupyter Notebook daily
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+Jon is an academic researcher and data scientist. He has been using the Jupyter Notebook daily
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for many years and is an advanced user, teacher and book author. He uses the Notebook
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exclusively on his local system and stores his notebooks on GitHub, in including blog posts
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and full length books.
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Jon regularly works with students, postdocs and other faculty at his own and other universities
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on a wide range of projects. These projects involve the collaborative creation of notebooks,
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-markdown files, documentation (Sphinx) and soruce code files (Python, C, C++). His collaborators
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+markdown files, documentation (Sphinx) and source code files (Python, C, C++). His collaborators
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also run the notebook their local systems.
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Jon and his collaborators need the ability to do ad-hoc collaboration on particular documents. They
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@@ -27,9 +27,9 @@ one or more files or a diretory of files with a group of individuals.
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During the RTC sessions, the participants are focused on the following aspects of their
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work:
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-* Collaborative editing of content
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-* Side channel live discussions (Bluejeans, appear.in, phonecalls)
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-* Discussion and exploration of results
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+* Collaborative editing of content.
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+* Side channel live discussions (Bluejeans, appear.in, phonecalls).
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+* Discussion and exploration of results.
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All individuals in the collaboration already have access to the files (Git/GitHub).
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Because of this, during the RTC they need to be able to collaborative edit the same exact
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@@ -46,28 +46,21 @@ accessed by thousands of scientific users.
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The collaboration has a software stack based on Python and C++ and is embracing modern,
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software engieering practices (version control with Git/GitHub, Travis, Slack, etc.). They version
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-control everything and run an extensive test suite on each commit and have a custom server based
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-on Bokeh and a SQL Database that allows them to monitor metrics related to their software stack.
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-Once the telescope goes live, they will also run regular software based tests on the telescope.
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-
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-The collaboration is exploring the possibility of using JupyterHub to provide a unified user-experience
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-for their users to access data and their analysis software. Initially, that would be used by the
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-software groups themselves, later during commissioning and testing of the experiment and finally by
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-scientists.
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+control everything and run an extensive test suite on each commit. The collaboration is exploring the possibility of using JupyterHub to provide a unified user-experience for their users to access data
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+and their analysis software.
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The collaboration would run JupyterLab with JuptyerHub, and build custom JupyterLab extensions that
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-have custom front-end UIs that talk to their various backend service, such as data stores, their
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-Bokeh/SQL based service, etc. They want to provide RTC capabilities for all of their services to enable
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-the users and scientists to work with the backend services in a collaborative manner. None of these
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-service have filesystem representation. Most of their RTC session will take place on shared
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-single-user notebook servers managed by JupyterHub. This style of collaboration will also extend
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-to Jupyter Notebook, Sphinx based documentation, Python/C++ source code files. In their JupyterHub
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-deployment these files are managed on a massive scale shared file system that is deployed on their
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-compute infrastructure. Again, all files are version controlled at the end of the day.
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-
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-## Arya the Data Science students
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-
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-Emma is a Junion Computer Science Major taking an introductory course in Data Science with Python.
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+have custom front-end UIs that talk to their various backend services. They want to provide RTC
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+capabilities for all of their services to enable the users and scientists to work with notebooks,
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+text files and their custom backend services in a collaborative manner. Most of their RTC session will
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+take place on shared single-user notebook servers managed by JupyterHub. This style of collaboration
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+will also extend to Jupyter Notebook, Sphinx based documentation, Python/C++ source code files.
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+In their JupyterHub deployment these files are managed on a massive scale shared file system that is
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+deployed on their compute infrastructure. Again, all files are version controlled at the end of the day.
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+
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+## Arya the Data Science student
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+
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+Emma is a Junior Computer Science Major taking an introductory course in Data Science with Python.
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Her professor uses the Jupyter Notebook for all course materials and homework. The notebook is
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deployed on a single server using JupyterHub and nbgrader is used for all course material.
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This is the first time Emma has used the Jupyter Notebook and she is enjoying the experience.
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Brian E. Granger