pangeo-data · rabernat · Jun 7, 2018 · Jun 7, 2018 · Jun 7, 2018 · Jun 7, 2018
diff --git a/docs/_static/pangeo-style.css b/docs/_static/pangeo-style.css
@@ -62,11 +62,17 @@ a:hover, a:focus {
 }
 
 .navbar-inverse .navbar-nav>li>a:hover, .navbar-inverse .navbar-nav>li>a:focus {
-    background-color: #e50051;
+    background-color: #00a3b0;
 }
 
 .navbar-inverse .navbar-nav>.open>a, .navbar-inverse .navbar-nav>.open>a:hover, .navbar-inverse .navbar-nav>.open>a:focus  {
-    background-color: #e50051;
+    background-color: #00a3b0;
+}
+
+.dropdown-menu>li>a:hover, .dropdown-menu>li>a:focus {
+    text-decoration: none;
+    /* color: #ffffff; */
+    background-color: #00a3b0;
 }
 
 .navbar-brand {

diff --git a/docs/about.rst b/docs/about.rst
@@ -3,24 +3,31 @@
 About Pangeo
 ============
 
+Pangeo is first and foremmost a :ref:`community of people <collaborators>`
+working collaboratively to develop software and infrastructure to enable
+Big Data geoscience research.
+
+Some of the products produced by this commmunity include interconnected
+:ref:`software pacakge <packages>` and :ref:`deployments <deployments>` of
+this software in cloud and high-performance-computing environments. Such
+a deployment is sometimes referred to as a *Pangeo Environment*.
+
 Motivation
 ----------
 
-There are several building crises facing the Atmosphere / Ocean / Land /
-Climate (AOC) science community:
+There are several building crises facing the geoscience community:
 
--  Big Data: datasets are growing too rapidly and legacy software tools
+-  *Big Data*: datasets are growing too rapidly and legacy software tools
    for scientific analysis can't handle them. This is a major obstacle
    to scientific progress.
--  Technology Gap: a growing gap between the technological
+-  *Technology Gap*: a growing gap between the technological
    sophistication of industry solutions (high) and scientific software
    (low).
--  Reproducibility: a fragmentation of software tools and environments
-   renders most AOC research effectively unreproducible and prone to
+-  *Reproducibility*: a fragmentation of software tools and environments
+   renders most geoscience research effectively unreproducible and prone to
    failure.
 
-We believe these challenges can all be addressed through a unified
-effort.
+Pangeo aims to address these challenges through a unified, collaborative effort.
 
 Mission Statement
 -----------------
@@ -30,56 +37,28 @@ open-source analysis tools for ocean, atmosphere and climate science can
 be developed, distributed, and sustained. These tools must be scalable
 in order to meet the current and future challenges of big data, and
 these solutions should leverage the existing expertise outside of the
-AOC community.
-
-Vision
-------
-
-We envision a collection of related but independent open-source packages
-that meet specific scientific needs within the AOC fields. These
-packages will follow modern best practices for software development,
-including:
-
--  hosting on GitHub,
--  testing,
--  coverage,
--  continuous integration,
--  comprehensive documentation, and
--  a welcoming and inclusive development culture.
-
-As much as possible, we will build on top of existing solutions and
-leverage expertise from the broader technology world, including
-industry.
-
-In practice, the "python data" software stack (see above) currently
-provides the most stable and powerful foundation layer for our desired
-tools. In particular the xarray and dask projects provide a mechanism to
-easily build scalability into scientific analysis. Our vision of future
-AOC software involves the adoption of these common software layers, and
-a clear communication between developers to define project scope and
-dependency that eliminates redundancy and fragmentation.
+geoscience community.
 
-Get Involved
-------------
+Goals
+-----
 
-The scientific culture in the AOC community must be tied to, and evolve
-from, the community's software culture. Hence, we depend upon
-contributions from the entire community, both scientific and industrial.
+To accomplish this mission, we have identified three specific goals.
 
-We encourage everyone to get involved by:
+#. Foster collaboration around the open source scientific python ecosystem for
+   ocean / atmosphere / land / climate science.
+#. Support the development with domain-specific geoscience packages.
+#. Improve scalability of these tools to to handle petabyte-scale datasets on
+   HPC and cloud platforms.
 
--  contributing to the goals and vision of the organization,
--  contributing to the design documents of the proposed software,
--  contributing to the software, via issues and pull requests, and/or
--  using the software for your scientific analysis and letting us know
-   about your experiences (e.g., contributing to examples)
-
-For now, community discussion is happening on our `pangeo google
-group <https://groups.google.com/forum/#!forum/pangeo>`__. This is an
-open group, and we invite anyone interested to join.
+Get Involved
+------------
 
+The pangeo project is completely open to involvement from anyone with interest.
+There are many ways to get involved:
 
-Pangeo receives support from the NSF_ via the EarthCube_ program.
+- *Science users*: read the :ref:`quickstart`, browse the :ref:`use-cases`,
+  read about the :ref:`packages`, or visit a :ref:`deployment <deployments>`.
+- *Developers / system administrators*: learn about the
+  :ref:`Technical Architecture` or read the :ref:`setup-guides`.
 
-.. _NSF: https://pangeo-data.github.io/
-.. _EarthCube: https://earthcube.org/
+For more information, consult the :ref:`FAQ`.
diff --git a/docs/data.rst b/docs/data.rst
@@ -100,7 +100,11 @@ datasets.
 These datasets are directly accessible from the Google Cloud Pangeo deployment:
 `pangeo.pydata.org <http://pangeo.pydata.org>`_.
 
-**HOW DO WE LIST THE DATASETS? CAN WE DIRECTLY PARSE THE INTAKE CATALOG?**
++--------+--------------+
+| Name   | Description  |
++========+==============+
+| Under  | Construction |
++--------+--------------+
 
 
 .. _cloud-data-guide:

diff --git a/docs/faq.rst b/docs/faq.rst
@@ -78,3 +78,26 @@ Frequently Asked Questions
    has the modularity and collaborative structure required to achieve our goals.
 
 #. *Why don't you use Julia or R?*
+
+   We would like Pangeo to evolve into a multi-language platform, including
+   support for Julia, R, and other programming languages used for data science.
+   Because Pangeo uses Jupyter to provide interactive commputing, this is
+   already possible today; Jupyter can be configured to run Kernels in many
+   different languages (see
+   `Jupyter docs on Kernels <http://jupyter.readthedocs.io/en/latest/projects/kernels.html>`_).
+   These kernels can be configured to run on any of the
+   Pangeo :ref:`Deployments`. However, the higher-level features of the Pangeo
+   platform, in particular, parallel execution with Dask, are limited to
+   Python at the moment. If you would like to work on enabling multi-language
+   support, please engage with us via the `Pangeo GitHub issue tracker`_.
+
+#. *Can I use Pangeo for X?*
+
+   Yes! Our goal is to point you towards the building blocks to create your
+   own Pangeo, whatever that means for you. If you want to create up a custom
+   Pangeo environment, start by consulting the :ref:`setup-guides`. If you
+   want help or want to discuss customization options, reach out via the
+   `Pangeo GitHub issue tracker`_.
+
+
+.. _Pangeo GitHub issue tracker: https://github.com/pangeo-data/pangeo/issues
diff --git a/docs/packages.rst b/docs/packages.rst
@@ -1,5 +1,3 @@
-.. _packages:
-
 Packages
 ========
 
@@ -42,6 +40,27 @@ as well as powerful tools for computation and visualization.
 .. _Common Data Model: http://www.unidata.ucar.edu/software/thredds/current/netcdf-java/CDM
 .. _netCDF: http://www.unidata.ucar.edu/software/netcdf
 
+
+Iris
+~~~~
+
+.. image:: _static/Iris_logo_banner.png
+
+- Website: https://scitools.org.uk/iris/docs/latest/
+- GitHub: https://github.com/SciTools/iris
+
+Iris seeks to provide a powerful, easy to use, and community-driven Python
+library for analysing and visualising meteorological and oceanographic data sets.
+
+With Iris you can:
+
+- Use a single API to work on your data, irrespective of its original format.
+- Read and write (CF-)netCDF, GRIB, and PP files.
+- Easily produce graphs and maps via integration with matplotlib and cartopy.
+
+Iris is an alternative to Xarray. Iris is developed primarily by the
+`UK Met Office Informatics Lab <http://www.informaticslab.co.uk/>`_.
+
 Dask
 ~~~~
 
@@ -77,11 +96,11 @@ live.
 Pangeo Affiliated Packages
 --------------------------
 
-xgcm
-~~~~
-
-xesmf
-~~~~~
+There are many other python packages that can work with the core packages
+to provide additional functionality.
+We plan to eventually catalog these packages here on the Pangeo website.
+For now, please refer to the
+`Xarray list of related projects <http://xarray.pydata.org/en/latest/faq.html#what-other-projects-leverage-xarray>`_.
 
 
 Guidelines for New Packages
@@ -128,12 +147,9 @@ additional recommendations.
    inevitable as developers try implementing different solutions to the
    same general problems.)
 4. *Consume and Produce Xarray Objects:* Xarray data structures
-   facilitate mutual interoperability between packages. (For more about
-   Xarray , see below.)
+   facilitate mutual interoperability between packages.
 5. *Operate Lazily:* whenever possible, packages should avoid explicitly
-   triggering computation on
-   `Dask <http://dask.pydata.org/en/latest/array.html>`__ objects. (For
-   more about Dask, see below)
+   triggering computation on Dask objects. 
 
 Why Xarray and Dask?
 ~~~~~~~~~~~~~~~~~~~~

diff --git a/docs/setup_guides/cloud.rst b/docs/setup_guides/cloud.rst
@@ -23,6 +23,8 @@ We hope to soon expand it to include AWS and Azure.
 Step One: Install the Necessary Software
 ----------------------------------------
 
+.. _google-cloud-sdk:
+
 Google Cloud SDK
 ~~~~~~~~~~~~~~~~