Overview
Flower is a Python package with a single purpose: to make human-friendly documentation from machine-friendly metadata. It takes metadata contained in a Data Package’s datapackage.json file and converts them into an output that is designed for humans and can be shared as a website or plain text files.
Why use Flower?
The overall aim of the Seedcase Project is to build tools that make data more FAIR, better documented, and more discoverable. To support this goal, Flower improves the display of metadata, which helps with discoverability and ease of sharing. This is an important part in making data FAIR, considering that one of the biggest barriers to (re-)using data, particularly research data, is the lack of well-documented metadata. For example, having information on how any given variable was collected, what the units are, and why the data was collected in the first place makes it much easier to effectively use data in a reliable and accurate way.
Flower is especially useful considering that there are few tools available that allow you to take metadata that describe a dataset or set of related datasets and make them into a format that is easy to share and easy to read (for humans). Even within the Frictionless Data ecosystem, which is the organisation responsible for initially starting and developing the Data Package specification, there are no tools for doing this. The closest match is a graphical user interface called Open Data Editor that can display the metadata, however it isn’t very flexible, isn’t easy to customise, and is mainly designed around editing metadata.
Learning more
This website contains documentation on Flower’s design, how to use it, and details about the interface.
- How-to guide: The guide section provides a step-by-step introduction to Flower, including installing, using the command-line interface, setting configurations, and creating customised styles.
- Reference: The reference section contains detailed information about Flower’s API, specifically the documentation of individual Python classes and functions.
- Design: The design section describes the architecture and interface of Flower, the requirements, use-cases, and C4 model diagrams.
Contributors
The following people have contributed to this project by submitting pull requests 🎉