Rewrite index page

Add installation instructions and an improved overview of the library.

docs/source/index.rst

@@ -38,36 +38,61 @@ The Performance, Portability, and Productivity Analysis Library (P3 Analysis
 Library) enables a simpler workflow for the collection and interpretation of P3
 data.
 
+- Compute :doc:`metrics <p3.metrics>` like "performance portability" and
+  "code divergence" to quantify the trade-offs between performance, portability
+  and productivity made by applications targeting multiple platforms.
+
+- :doc:`Plot <p3.plot>` cascades and navigation charts to visualize and gain
+  deeper insight into the "performance portability" and "code divergence"
+  scores achieved by different applications.
+
+
+Installation
+############
+
+The latest release of the P3 Analysis Library is version 0.1.0-alpha. To
+download and install this release, run the following::
+
+    $ git clone --branch v0.1.0-alpha https://github.com/intel/p3-analysis-library.git
+    $ cd p3-analysis-library
+    $ pip install .
+
+We strongly recommend installing the P3 Analysis Library within a `virtual
+environment`_.
+
+.. _`virtual environment`: https://docs.python.org/3/library/venv.html
+
+
 Getting Started
 ###############
 
-- `Introduction to P3 Analysis`_
-- `Collecting P3 Data`_
+As a library, the P3 Analysis Library does not provide user-facing scripts for
+preset analyses. Rather, the library provides routines for manipulating and
+visualizing data in support of common P3 analysis tasks.
 
-.. _Introduction to P3 Analysis: introduction.html
-.. _Collecting P3 Data: data.html
+Using the P3 Analysis Library effectively requires:
 
-Examples
-########
+1. **A basic understanding of P3 analysis and related terminology.**
 
-Simple examples of using the library are available on the `examples`_ page.
-Complete end-to-end examples, using real data, are available on the `case
-studies`_ page.
+   A brief refresher can be found `here <analysis.html>`__, and a high-level
+   overview can be found in papers like
+   "`Navigating Performance, Portability and Productivity`_".
 
-.. _examples: examples/index.html
-.. _case studies: case-studies/index.html
+   .. _here: analysis.html
+   .. _Navigating Performance, Portability and Productivity: https://doi.org/10.1109/MCSE.2021.3097276
 
-Documentation
-#############
+2. **P3 data stored in one of the expected formats.**
 
-- `Package Reference`_
+   The library does not interact with the filesystem, and expects data to be
+   prepared and stored in `Pandas`_ DataFrames with specific column names.
 
-.. _Package Reference: p3.html
+   A guide for collecting and structuring P3 data can be found `here <data.html>`__.
 
-Contribute
-##########
+   .. _Pandas: https://pandas.pydata.org/
 
-Contributions to the P3 Analysis Library are welcome in the form of issues and
-pull requests. Please see the `GitHub repository`_ for more information.
+Simple examples of using the library are available on the `examples`_ page.
+Complete end-to-end examples, using real data, are available on the `case
+studies`_ page.
 
-.. _GitHub repository: https://github.com/intel/p3-analysis-library/blob/main/CONTRIBUTING.md
+.. _examples: examples/index.html
+.. _case studies: case-studies/index.html