FAIR Digital Objects and Natural Science Collection Data

Author:

Islam SharifORCID

Abstract

The Distributed System of Scientific Collections (DiSSCo) is a new Research Infrastructure that is working towards the unification of all European natural science collections under common curation, access policies, and practices (Addink et al. 2019). The physical specimens in the collections and the vast amount of data derived from and linked to these specimens are important building blocks for this unification process. Primarily coming from large scale digitization projects (Blagoderov et al. 2012) along with new types of data collection, curation, and sharing methods (e.g. Kays et al. 2020), these specimens hold data that are critical for different scientific endeavours (Cook et al. 2020, Hedrick et al. 2020). Therefore it is important that the data infrastructure and the relevant services can provide a long-term sustainable and reliable access to these data. To that end, DiSSCo is working towards transforming a fragmented landscape of the natural science collections into an integrated data infrastructure that can ensure that these data can be easily Findable, more Accessible, Interoperable and Reusable – in other words, comply with the FAIR Guiding Principles (Wilkinson et al. 2016). A key decision for the design of this FAIR data infrastructure was to adopt FAIR Digital Objects (Wittenburg and Strawn 2019) that will enable the creation of Digital Specimen—a machine-actionable digital twin of the physical specimen (Lannom et al. 2020). This FAIR Digital Object by design, ensures FAIRness of the data (De Smedt et al. 2020) and thus will allow DiSSCo to provide services that are essential for natural science collection-based research. This talk summarises the motivation behind this adoption by showing how design decisions and best practices were influenced by the FAIR data principles, global discussions around FAIR Digital Objects and outputs from the Research Data Alliance (RDA) interest and working groups.

Publisher

Pensoft Publishers

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3