🗺️ Mapping of the ICT Sustainability Tools Landscape

This repository aim at providing to the global IT Sustainability community a vendor-neutral, fact-based, non-judgmental and exhaustive repository of the tools and services available to assess the environmental footprint of IT components.

It defines a data model that can be used to build an inventory of the tools.

Caution

Today, any data contained in this repository is not validated nor reviewed. It is likely that the data contains completely false assumptions. It is here as sample data for the sole purpose of development and testing of the model. It should NOT be used for anything else.

Warning

The data model is still very drafty and is expected to evolve.

• 🗺️ Mapping of the ICT Sustainability Tools Landscape
  • Repository content
  • Implementation
    • Architecture decisions records / ADRs
    • General design
      • Usage flow
      • Components
    • Data format
    • draft dataset
    • Example Datami widgets

Repository content

• doc/ : documentation
  • architecture decision records: doc/adr/
• ictst
  • ictst/data
    • Main data file (CSV): ictst/data/tools.csv
    • Data validation model: ictst/data/tools.resources.yaml: Used in command line or via github actions.
  • ictst/model
    • data model used to configure the widget: ictst/model/tools.frictionless-table-schema.json
  • ictst/widget:
    • widget html: ictst/widget/tools-widget.html
    • additional fields configuration for the widget ictst/widget/tools.fields-custom-properties.json
• .github/workflows : github action to automate the data validation
• old-examples/: other examples of using Datami

Implementation

Architecture decisions records / ADRs

• All ADRs

General design

We use a Datami widget to display data and allow edition of a file stored in Github. Even if end user is not familiar with Git.

1. data is stored in GIT to benefit from historisation, review and approval workflows (and potential automatic validation of format)
2. data update can be proposed by end users in 2 ways:
   1. A web frontend that allow to view the data and propose edition => This is the preferred solution using Datami widget
   2. Pull requests directly against the data file (git) => Less preferred (mainly for maintainers of people familiar with Git)

Usage flow

Components

Warning

The data validation and the data edition (widget) are configured using different set of files or data models. These data model use different syntax but have to be kept in sync manually !

Data format

• We store data as a csv file.
• add specific descriptors as table-format to describe and validate constraints on the fields.
• implement frictionless-ci or other automatic validation regarding format as a github action frictionless-ci | Frictionless Repository

Note

Our preferred format would have been to have a structured (json) file, described by a json schema. However json edition is not well supported by Datami yet. (JSON data is displayed as json tree which is not very user friendly for non technical users). So for the time being we fall back to using a less structured CSV dataset.

draft dataset

See draft dataset

Example Datami widgets

• A CSV file displayed without any customization old-examples/csv/csv-widget-basic.html
• A CSV file displayed with some additional constraints on fields old-examples/csv/csv-widget-with-constraints.html.
• Other examples with more complex validation rules:GitHub - demeringo/datami-tests: Testing datami widget to edit and validate csv files