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DataCite and FAIR Workflows

Author(s)
Keywords

research data managem...

FAIR data principles

collaboration network...

best practice

DataCite

open science

Issue Date
May 12, 2022
Publisher
euroCRIS
Source
Procedia Computer Science 211: 83-92 (2022)
Type
Conference Proceeding
Abstract
The world of research and academic publishing is complex and challenging. There is a need for collective efforts to enhance the discoverability and usage of research out-puts. DataCite is the project organization that leads the “Implementing FAIR Workflows” project, funded by the Templeton World Charity Foundation. Prompted to address the complexities of scholarly information, DataCite, along with the project partners, aims to develop an exemplar FAIR and Open Research workflow based on the reality of the research lifecycle. The aim is to implement such a workflow through the integration of existing and well-accepted global open infrastructure, particularly the different identifier systems, thus enabling research evaluation and accelerated output reuse. ChronosHub is one of the project partners and acts as an intermediary to facilitate the information flow between the different stakeholders in the research ecosystem. This session will invite a discussion of how all of us in the research ecosystem can contribute with collaborative actions to build bridges and remove enormous amounts of administrative work with data collection, structuring, and quality assurance.
Description
Extended abstract to be presented at the CRIS2022 conference in Dubrovnik.-- Event programme available at https://cris2022.srce.hr/#section-program
13 slides.-- Presentation delivered within the session "Open Science implementation [I]"
URI
https://dspacecris.eurocris.org/handle/11366/1970
DOI
https://doi.org/10.1016/j.procs.2022.10.179
File(s)
Thumbnail Image
Name

Reher-Chen-Jagerhorn_CRIS2022_presentation.pdf

Description
PDF presentation
Size

4.97 MB

Format

Adobe PDF

Checksum (MD5)

dd76c6ca4283cfa2f6f62a2fe1856966

Thumbnail Image
Name

Reher-Chen-Jagerhorn_CRIS2022_DataCite-and-FAIR-Workflows.pdf

Description
Extended abstract (PDF)
Size

171.75 KB

Format

Adobe PDF

Checksum (MD5)

1ac887acacbd6bfce9f3ffde6a26404a

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