Introduction

Local Offline Assessor for FAIR (LOAF) is a Python library for checking metadata: the information that describes a dataset, such as its title, creator and licence. The checks address FAIR principles: Findable, Accessible, Interoperable and Reusable.

An assessor defines what to check and, where applicable, how to assign points.

Supported assessors

Versions are those supported by this library. A metric groups checks; the metric count includes partial support. F-UJI supports all checks in 13 metrics and some checks in one more. Champion's two conditional checks can decide only some cases offline; search indexing is unsupported. These counts describe capability, not how many checks will reach a decision for every input.

How it works

1. Choose an assessor and version.
2. Supply the dataset's metadata.
3. The assessor interprets the metadata and applies its own checks.
4. Read the results, messages and any scores the assessor provides.

What offline means

The library checks the information you supply. It does not download datasets, open their links or contact external services. Checks that need information unavailable offline are marked indeterminate and receive no score.

You can use it to check metadata before publishing it or in an application without network access.

Start here

Use the quickstart to run an assessment. The Python API explains the arguments; Results explains the response. The F-UJI and FAIR Champion pages explain their requirements and offline limits.

Developed for EOSC Data Commons.