We are committed to improving openness, transparency, and reproducibility of research.
We believe research data citation through standard reference lists offers an easy way to access data for reproducible research.
To support best practice in data citation, AME has endorsed the FORCE11 Data Citation Principles (https://www.force11.org/datacitationprinciples). According to the FORCE11 Data Citation Principles, data can be cited in the same way as article, book, and web citations and authors are required to include data citations as part of their reference list.
Data citation is applicable for data held within institutional, subject-focused, or more general data repositories. When citing or making claims based on data, authors should refer to the data at the relevant place in the main text of the manuscript and include a formal citation in the reference list. We recommend the format proposed in the Joint Declaration of Data Citation Principles.
Below is an example of an in-text data citation:
[dataset] Authors; Year; Dataset title; Data repository or archive; Version (if any); Persistent identifier (e.g. DOI)
(please add [dataset] immediately before the reference so it can be properly identified as a data reference)
Research resource identifiers (RRID)
AME journals are pleased to be a part of the Research Resource Identification Initiative, a project aimed at clearly identifying key research resources, aka materials, used in the course of scientific experiments. These include antibodies, cell lines, model organisms, and software tools. To help authors quickly find the correct identifiers for their materials there is a single web site (http://scicrunch.org/resources) where all resource types can be found and a 'cite this' button next to each resource that contains proper citation text that should be included in the methods section of the manuscript. Several examples of properly formatted methods sections with RRIDs can be found below:
Updated on July 30, 2020