Add format-selection decision framework page and case studies

.gitignore

@@ -15,3 +15,5 @@ __pycache__/
 .ipynb_checkpoints
 
 /.luarc.json
+
+**/*.quarto_ipynb

CITATION.cff

@@ -17,6 +17,8 @@ authors:
   family-names: "Barron"
 - given-names: "Zachary"
   family-names: "Deziel"
+- given-names: "Emmanuel"
+  family-names: "Mathot"
 - given-names: "Max"
   family-names: "Jones"
 - given-names: "Brianna"

_quarto.yml

@@ -31,6 +31,15 @@ website:
         text: Welcome
       - href: overview.qmd
         text: Overview Slides
+      # NOTE for @abarciauskas-bgse: proposed nav placement only.
+      # Placed before "Formats" so a reader can pick a format family before
+      # diving into a format page. Final position depends on the Track-3 site
+      # redesign - please confirm or move (and rename the path if needed).
+      - section: Choosing a Format
+        href: decision-framework/index.qmd
+        contents:
+          - decision-framework/index.qmd
+          - decision-framework/case-studies.qmd
       - section: Formats
         contents:
         - section: Cloud Optimized GeoTIFFs (COG)
@@ -89,7 +98,7 @@ format:
   html:
     include-in-header: plausible.html
     theme:
-      light: [cosmo, theme.scss] # from https://github.com/sta210-s22/website/blob/main/_quarto.yml
+      light: cosmo # from https://github.com/sta210-s22/website/blob/main/_quarto.yml
       dark: [cosmo, theme-dark.scss]
     code-copy: true
     code-overflow: wrap

_thankyous.qmd

@@ -10,4 +10,6 @@ This guide has been made possible through the support of:
 [![](./images/thankyous-devseed-logo.png){fig-alt="Development Seed Logo" fig-align="left" width=40%}](https://developmentseed.org)
 
 [![](./images/thankyous-cng-logo.png){fig-alt="Cloud-Native Geospatial Forum" fig-align="left" width=40%}](https://cloudnativegeo.org)
-:::
+:::
+
+The [Format Selection Decision Framework](./decision-framework/index.qmd) and its case studies were contributed from a study for the [Centre National d'Études Spatiales (CNES)](https://cnes.fr/), and use public [Copernicus](https://www.copernicus.eu/) and [NASA](https://www.earthdata.nasa.gov/) mission data.

glossary.qmd

@@ -9,6 +9,12 @@ format:
 
 This glossary aims to describe all the jargon of geospatial in the cloud! Are we missing something? [Create an issue](https://github.com/cloudnativegeo/cloud-optimized-geospatial-formats-guide/issues/new?title=Glossary+suggestion:&labels=glossary) to suggest an improvement.
 
+#### Access pattern
+
+What subsets of the data get requested: a time series at a single point, a spatial window at a single date, or a full scan of everything.
+
+The access pattern drives the [chunk](#chunk) shape and the order of the dimensions, which is a separate question from [chunk size](#chunk-size). A cube chunked long in time answers a time series at one point cheaply and a full map expensively; chunked wide in latitude and longitude it does the opposite. Only rewriting the data lets you change it, so a virtualized dataset inherits whatever access pattern its source was written for.
+
 #### Amazon S3 (S3)
 
 The [object storage](#object-storage-cloud-storage) service offered by Amazon. Part of [Amazon Web Services](#amazon-web-services-aws).
@@ -328,6 +334,12 @@ For further reading: [A dive into spatial search algorithms](https://blog.mapbox
 
 A file format for image and raster data that supports [lossless compression](#lossless-compression).
 
+#### Tiered storage
+
+A storage service that keeps data on different classes of hardware at different prices and speeds. A common arrangement is a "warm" tier on disk for data that is read often, and a "cold" tier on tape or archival storage for data that is read rarely.
+
+Some providers set a minimum mean [object](#object-storage-cloud-storage) size for each tier, because indexing very many small objects is expensive. A layout whose objects fall below that floor can be refused or moved to a slower tier, so [chunk size](#chunk-size) and grouping choices have to be made against the policy of the storage you are actually using.
+
 #### Vector data
 
 A type of geospatial data to represent points, lines, and polygons.

index.qmd

@@ -64,15 +64,17 @@ Notes:
 ## Table of Contents
 
 1. [Overview of Formats (slideshow)](./overview.qmd)
-2. Formats
+2. [Format Selection Decision Framework](./decision-framework/index.qmd)
+   a. [Case Studies](./decision-framework/case-studies.qmd)
+3. Formats
    a. [Cloud-Optimized GeoTIFFs](./cloud-optimized-geotiffs/intro.qmd)
    b. [Zarr](./zarr/intro.qmd)
    c. [Cloud-Optimized NetCDF4/HDF5](./cloud-optimized-netcdf4-hdf5/index.qmd)
    d. [Cloud-Optimized Point Clouds (COPC)](./copc/index.qmd)
    e. [GeoParquet](./geoparquet/index.qmd)
    f. [FlatGeobuf](./flatgeobuf/intro.qmd)
    g. [PMTiles](./pmtiles/intro.qmd)
-3. [Cookbooks](./cookbooks/index.qmd)
+4. [Cookbooks](./cookbooks/index.qmd)
 
 
 ## Running Examples
@@ -85,6 +87,7 @@ Most of the data formats covered in this guide have a Jupyter Notebook example t
 * [Alex Mandel](https://developmentseed.org/team/alex-mandel)
 * [Kyle Barron](https://github.com/kylebarron)
 * [Zac Deziel](https://developmentseed.org/team/zac-deziel)
+* [Emmanuel Mathot](https://developmentseed.org/team/emmanuel-mathot)
 * [Overview Slide](./overview.qmd) credits: Vincent Sarago, Chris Holmes, Patrick Quinn, Matt Hanson, Ryan Abernathey
 
 ## Questions to Ask When Generating Cloud-Optimized Geospatial Data in Any Format