Open Science & Research Data Management

A data management plan (DMP) is a written document that describes the data you expect to acquire or generate during the course of a research project, how you will manage, describe, analyze, and store those data, and what mechanisms you will use at the end of your project to share and preserve your data.

• More about data management plans

Open Access (OA) refers to free, unrestricted online access to research outputs such as journal articles and books. OA content is open to all, with no access fees.

There are many types of OA, but the two main routes to making research outputs openly accessible are “Gold Open Access” and “Green Open Access”. Gold OA involves publishing articles or books via the OA route on a publisher’s platform. Green OA involves archiving a version of the manuscript in an OA repository, like SDU Pure.

Content published via the Gold OA route is accessible immediately on publication at the publisher’s website, but may come with a hefty fee. Manuscripts published via the Green OA route may, in many cases, be made accessible only once a self-archiving embargo period has elapsed. The terms for onward sharing and re-use of OA content will depend on the license under which it has been made available.

In cases where closed access cannot be avoided, please consider writing an OA popular science article, a blog post or engage in OA communication activities regarding your work.

To learn more, visit the FAQ section of our page on data best practices here, visit SpringerNatures page here that this text has been partly adapted from or visit the Open Access webpage. You can also learn more about publishing OA, such as “How to find a suitable OA journal or repository for your publications” by visiting the OpenAIRE web-guide.

What is open access? Nick Shockey and Jonathan Eisen of PhD comics take us through the world of Open Access publishing and explain just what it's all about. Watch the video here.

FAIR research data is data that has been prepared in accordance with the FAIR Guiding Principles published in 2016. These principles contain data management best practices that aim at making data FAIR: Findable, Accessible, Interoperable, and Reusable.

To learn more, visit the FAQ section of our page on data best practices here.

To learn more about FAIR research data, watch this 20 minute video e-Learning module that aims to help researchers understand:

1. The key elements that help make research data discoverable, accessible, interoperable and reusable
2. How these key elements are used in different research disciplines and different research workflows
3. The differences between FAIR data and open data

The website www.howtofair.dk will take you on a deep dive into the subject matter of FAIR research data. Over the course of about two hours, it will show you that FAIR is not a time-consuming administrative mantra, but a set of principles that makes your research efficient, transparent and sustainable. Working in line with the FAIR principles to make your data more FAIR will improve your research data management and safeguard your research data for the future.

The SDU Data Management Forum is a local implementation of the National Forum for Research Data Management. We work on and develop SDU’s services on data management, Open Science, GDPR, and other legal questions.

• More About the SDU Data Management Forum