DataCite Best Practice Guide

This document is a guideline to use the DataCite Metadata Schema [external link], version 4.3. It is meant for researchers, IT and library support staff in the context of the following institutions: Ludwig-Maximilians-Universität München Leibniz Supercomputing Centre If you wish to publish your research data in one of these institutions, this guide helps to make your submission compliant to best practices in the context of research data management. This guide is also designed to be reused by other institutions as well.

Related Organizations

Ludwig-Maximilians-Universität München
Germany
Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities, Germany
Germany
London Metropolitan University
United Kingdom

Keywords

Digital Humanities, Metadata, Research Data Management, DataCite, Interoperability, Research Data, Standardization

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average