ipcc-countries
==============

Database of countries member of the Intergovernmental Panel on Climate Change

## Folder Hierarchy

* sources - data sources, grouped by origin
  * example.tld - each source is identified by corresponding domain name
    * step1, step2,... - one folder for each step to acquire the data,
                         extract it from the source document and transform
                         the data into CSV
    * source document (e.g. PDF, HTML or XML)
    * data.csv - data extracted from the source, in a close structure and format
    * meta.txt - metadata which describes the origin of the document,
                 with annotations in 'key: value' format (one per line),
                 optionally ending with an empty line and a multi-line
                 'description:' field.

* database - SQLite database with data aggregated, refined and cross-checked
  * step1, step2,... - one folder for each step to aggregate the data
                       from data sources, to refine it and cross-check it,
                       and to export each database table as a CSV file,
                       and the database schema as a picture
  * \*.csv - database tables in CSV format
  * database-schema.png - diagram of database relations

* visualizations - data visualizations, grouped by question
  * who, what, where... - one folder for each question asked
    * step1, step2,... - one folder for each step to query the database and
                         export results in the format used in the data
                         visualization (e.g. CSV or JSON)
    * data visualization (e.g. HTML or Open Document Spreadsheet)
      which answers the question visually

ipcc-countries
==============

Database of countries member of the Intergovernmental Panel on Climate Change

## Folder Hierarchy

* sources - data sources, grouped by origin
  * example.tld - each source is identified by corresponding domain name
    * step1, step2,... - one folder for each step to acquire the data,
                         extract it from the source document and transform
                         the data into CSV
    * source document (e.g. PDF, HTML or XML)
    * data.csv - data extracted from the source, in a close structure and format
    * meta.txt - metadata which describes the origin of the document,
                 with annotations in 'key: value' format (one per line),
                 optionally ending with an empty line and a multi-line
                 'description:' field.

* database - database with data aggregated, refined and cross-checked
  * step1, step2,... - one folder for each step to aggregate the data
                       from data sources, to refine it and cross-check it,
                       and to export each database table as a CSV file,
                       and the database schema as a picture
  * \*.csv - database tables in CSV format
  * database-schema.png - diagram of database relations

* visualizations - data visualizations, grouped by question
  * who, what, where... - one folder for each question asked
    * step1, step2,... - one folder for each step to query the database and
                         export results in the format used in the data
                         visualization (e.g. CSV or JSON)
    * data visualization (e.g. HTML or Open Document Spreadsheet)
      which answers the question visually

Remove specific mention of SQLite (the database format is more generic)
Remove specific mention of SQLite (the database format is more generic)

I decided to store the database in CSV in its ready state,
and in SQL dumped by sqlite in intermediate steps; this SQL
is not specific to SQLite according to its documentation,
and can be used AS IS in PostgreSQL as well.
