FAIR Metadata: A Community-Driven Vocabulary Application

被引：2

作者：

Rauch, Christopher B. ^{[1
]}

Kelly, Mat ^{[1
]}

Kunze, John A. ^{[2
]}

Greenberg, Jane ^{[1
]}

机构：

[1] Drexel Univ, Philadelphia, PA 19104 USA

[2] Univ Calif Oakland, Calif Digital Lib, Oakland, CA 94612 USA

来源：

METADATA AND SEMANTIC RESEARCH, MTSR 2021 | 2022年 / 1537卷

关键词：

Metadata; Standardization; FAIR; Metadata quality; Community driven;

D O I：

10.1007/978-3-030-98876-0_16

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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 of YAMZ 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.

引用

页码：187 / 198

页数：12

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