Welcome to the Dataverse Curation Guide

What is this guide?

This guide provides step-by-step instructions for curating new datasets deposited in Dataverse. Data curation deals with the active management of research data as it is created, maintained, used, archived, shared, and reused. The guide is framed around the acronym CURATION to provide an easy reminder for curators, especially those starting out, of the main steps in the curation process. This framework is adapted from the Data Curation Network’s CURATED steps for use in a bilingual context and is intended to outline and provide guidance on curation best practices in Dataverse. Data curation is not always a linear process; the type of data you are working with, your institutional policies or practices, your comfort level with curation, and the amount of time the researcher is able to dedicate to the process may require you to skip steps or complete the steps in a different order. You may also need to circle back and complete some of the steps a second time. The level of curation your institution is able to offer, given competing priorities and number of staff dedicated to the curation service, may also determine how many curation steps you can complete.

Our Guide acknowledges there is no “one size fits all” model to data curation. The level and quality of curation is dependent on local resourcing, capacity, policies, priorities, and institutional strategic direction. As a result, the Guide has been developed with flexibility in mind. It can be used by new or experienced curators within academic institutions of all sizes, and it can be adapted by institutions to meet the needs of local policies and procedures.

How to use it?

• Read the instruction pages to learn how to apply this guide based on your institution’s service level and capacity.
• Head to the guide to apply the CURATION workflow to curating data sets in Dataverse.

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