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Data management plan

You'll need to consider: 

• how you'll make your data available
• when you'll make your data available
• who you'll share the data with
• the conditions in which you'll share the data
• which data repository you'll use. 

If you plan to place restrictions on the accessibility of the data, such as an exclusive access period, clearly set out the reasons why these restrictions are necessary.

When you've completed this section, you should consider what to include in the Responsibilities and Resources component of the DMP.

Data repositories

As set out in the RDM Policy, research data selected for deposit must be made as open as possible and only as restricted as necessary. You should minimise the period of time for which you hold exclusive use of research data.

At the end of your project, you must deposit your selected research data into an appropriate repository as soon as possible. There are a range of options available to º£½ÇÂÒÂ× researchers. These include: 

• disciplinary repositories
• the University’s data storage service, .

Registries such as and can be used to search and identify the most appropriate repository for your research data. Your chosen repository should align with the FAIR Data Principles and meet the requirements set out in the . Search via re3data and select CoreTrustSeal from ‘Certificates’ to ensure your chosen repository meets these requirements.

USIR and data repositories

If you choose to deposit data in a repository other than the University’s Figshare service, you must create a metadata record in the (USIR). The creation of metadata records for Figshare data is handled by the Library team.

How to create a USIR metadata record

Follow the instructions to ensure your dataset is accurately recorded in USIR and linked to your academic profile.

• Visit . From the Outputs menu select ‘Add New Output’
• Choose the option to ‘Add Outputs Manually’
• Complete the 'Type', 'Title' and 'Abstract' metadata fields. In most cases, ‘Type’ should be set to either ‘Dataset’ or ‘Digital Artefact’.
• Set the 'Publication Status' field to ‘Published’
• Enter the same date in the 'Publication Date', 'Online Publication Date', and 'Data Collection Date' fields
• Add the DOI of your dataset in the format '10.17866/rd.salford.12345678.v1'
• In the 'Output Authors' section, add all authors involved in the creation of the dataset. Any authors from the University should be selected from the ‘Linked Person’ dropdown.
• Leave the 'Output Contributors' section blank
• In the 'Output Funders' section, add funding information for the dataset. If the work is unfunded, please select ‘#3 º£½ÇÂÒÂ×’.

Once you've completed the submission form, click ‘Send to Library’. The record will be checked by the Library before being made discoverable.

Please contact the research support team if you're struggling to create a metadata record for your dataset in USIR.

Licenses

You need to enable the maximum possible reuse of your research data. To do this, you should choose the most permissive licence possible. For example, a does not retain any rights to the data. Alternatively, a licence, requires others to attribute you when using the data. For software and source code, you should choose an .

Costs

Selected research data should typically be retained for a period of at least ten years from publication. This is in line with any legal, contractual, regulatory or ethical requirements, so it's important to be aware of the potential costs. Anticipating these costs is especially important where you plan to preserve large volumes of data from your project. Most data repositories are free of charge, but uploads are limited to between 50-100 GB. Anything beyond this size is likely to incur a cost.

Where you plan to share hundreds of gigabytes or even terabytes of data, you should first consider whether it is necessary to retain all the data. If it is necessary to share a high volume of data, then you should factor this expense into your funding application. Most research funders with an open data policy will consider this to be acceptable cost.

Sharing code

To ensure reproducibility, you should also consider sharing any code created during your research project. Sharing code allows other researchers to understand exactly how data was processed and analysed. This is essential for verifying results and reproducing studies.

For source code stored in a versioning control system, such as , you should create a ‘public registration’ for your project in order to obtain a DOI. You can do so by depositing the code into a data repository. This ensures there is an archived version of the code which can verify the related research findings. If you plan to publish, include a link to both the versioning control system (URL) and the archived code in the repository (DOI and citation) in your publication’s data access statement.

FAIR Data Principles

Sharing your data in a repository is the best way to meet the . These are a framework for making your data:

• Findable
• Accessible 
• Interoperable
• Reusable. 

These principles should be put into practice throughout the lifecycle of a research project, but they are particularly relevant when it comes to data sharing.

Below you can find some suggested actions to make your data FAIR.

Findable

• Describe your dataset with rich metadata
• Ensure your data is indexed in a searchable data repository
• Create a unique and persistent identifier, i.e. a Digital Object Identifier (DOI)

Accessible

• Provide a clear route to access your data e.g. via a repository
• Be clear about conditions of access where data is restricted
• Create a metadata record in your chosen repository, where it is not possible to share the dataset

Interoperable

• Check for disciplinary standards that apply to your data
• Ensure the data repository you choose allows you to include links or references to other related data
• Use open, non-proprietary file formats to ensure your data can be reused by others, integrated with other datasets, and accessible in the long term

Reusable

• Add as much metadata and documentation as possible when depositing your dataset in a repository e.g. README file
• Apply an open license to your data, preferably CC0 or CC-BY 4.0
• Ensure your data and metadata must adhere to domain-relevant community standards