FAIR Metadata: A Community-driven Vocabulary Application

11/06/2021
by   Christopher B. Rauch, et al.
0

FAIR metadata is critical to supporting FAIR data overall. Transparency, community engagement, and flexibility are key aspects of FAIR that apply to metadata. This paper presents YAMZ (Yet Another Metadata Zoo), a community-driven vocabulary application that supports FAIR. The history ofYAMZ and its original features are reviewed, followed by a presentation of recent innovations and a discussion of how YAMZ supports FAIR principles. The conclusion identifies next steps and key outputs.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

12/03/2020

Ten Simple Rules for making a vocabulary FAIR

We present ten simple rules that support converting a legacy vocabulary ...
06/01/2021

AMV : Algorithm Metadata Vocabulary

Metadata vocabularies are used in various domains of study. It provides ...
09/13/2021

Project Pipeline: Preservation, Persistence, and Performance

Preservation pipelines demonstrate extended value when digitized content...
10/09/2018

How FAIR can you get? Image Retrieval as a Use Case to calculate FAIR Metrics

A large number of services for research data management strive to adhere...
08/14/2021

Packaging research artefacts with RO-Crate

An increasing number of researchers support reproducibility by including...
10/24/2018

A Map Equation with Metadata: Varying the Role of Attributes in Community Detection

As the No Free Lunch theorem formally states [1], algorithms for detecti...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.