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Data management guide

Guide to data management plans

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.

You may have already considered some or all of these issues with regard to your research project, but writing them down helps you formalize the process, identify weaknesses in your plan, and provide you with a record of what you intend(ed) to do. Data management is best addressed in the early stages of a research project, but it is never too late to develop a data management plan.

In the 9 steps below, you can read about essentials parts of a data management plan and find suggested online resources. 

Data management guide

SDU requires at data management plan for research projects as a part of the Open Science Policy. 
In addition, many funders require you to provide a data management plan (DMP). These plans are also a great way for you to anticipate your data management needs and establish a shared understanding of the resources available to you. 

Suggested links: 
SDU Open Science Policy
eLearning course research data management
The Danish Code of Conduct for Research Integrity

There a various number of online resources available on data management plans. We have listed some suggestions below. 

Suggested links: 
DMPonline – for creating data management plans
Data Management for Researchers (e-book, chapter 8.2)

The source of the data will affect your choices throughout your data management plan – are they observational, experimental, simulation or deprived/complied? 

Suggested links:
Types of data (DMPtool)
Data flow tool kit
Research Data Management Toolkit 
Manage your data (DeiC knowledge portal)

Personal data is any piece of information about an identifiable person, such as name, e-mail, personal identification number, address, health information, race, or sexual orientation, etc. However de-identified data can be included by GDPR and Danish data protection legislation if the information can be combined with other available data to identify individuals. Therefore, it is vital that data are properly anonymized before sharing. It is recommended to seek advice from an expert in anonymization techniques. 
Handling personal data securely in research is very important and SDU require that you notify SDU RIO of your project. 

Suggested links:
Personal data requirements at SDU
Notify RIO of your project
Get ethics approval from SDU Research Ethics Committee
The Danish Data Protection Agency (Personal data)
GDPR guidelines at SDU
Confidentiality concerns (Dataone Best Practices)
Decide where you will store your data and files during the active phase of your project and consider your backup options (personal computer hard drives, external hard drives, local servers or cloud storage). 

Suggested links: 
SDU IT-guide (SharePoint)
UCloud
Some file formats are better than others to manage, share, and preserve your data. The file format you choose for your data is a primary factor in accessibility in the future.

Suggested links: 
File formats (DMP tool)
Data Management for Researchers (e-book)
A data repository is often ideal for a long-term solution of preserving your data. You are required to preserve your data for a minimum of five years (Code of conduct for Research Integrity). Remember to check the data requirements for your chosen repository and to assign responsibility for long-time preservation to a department. 

Suggested links: 
Find a repository here
Rigsarkivet
Open Access (European Research Council)
The Danish Code of Conduct for Research Integrity
Meta-data should contain what you or someone else would need of information to find, evaluate and use the data in the future. Meta-data is often created as a README file but can often also be added when uploading the data to a repository.  

Suggested link: 
Data Management for researchers (e-book, chapter 4.4)
 
Even if the publisher of your paper does not mandate data sharing, it’s in line with the FAIR principles to upload data and/or metadata to a trusted repository. 

Suggested links: 
Find a repository here
General purpose repository Zenodo
GitHub for code
OpenAIRE guides  
OpenAIRE for Researchers 
Fair sharing (guideline and database)
Additional reading (FAIR data)








Data management guide

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Last Updated 23.06.2021