An ounce of prevention is worth a pound of cure! - Benjamin Franklin 

Preparing for publication

Preparing early will save you and your users time. Ideally, your research data publishing begins before you even start your research project, and you have a data management plan to help you. Since you will ultimately be sharing your work, your research data will need to be organized and structured to make the most sense to users who may not have ever been a part of your initial project.

Consider how you expect people actually to access your dataset files.  Provide instructions on how to access and use the datasets as intended.  See: Preparing data for publication by file type.

Organize your files, so they make sense to end-users. If you have many files from the tens to the thousands but have only been working in a flat folder structure, separate them into different folders, making them easier to navigate. 

Publish only what is needed. Not all of your data may need to be shared. Consider only those relative files to reproduce the results of your work or were necessary components that allowed you to come to your conclusions.  See: Other data publishing considerations

Manage user expectations for downloading. Dataverse is not an active research notebook system. Users may need to download and analyze the datasets on a local system. Some of the most extensive datasets in our repository could take upwards of 60 hours to download under normal circumstances. 

If you are submitting very large or numerous files, provide instructions for a download manager or consider other backup options to ensure users may access your research datasets promptly.  Multiple issues, such as local internet speed, firewalls, and limitations on end-user laptops and desktop computers, will affect users.

Some of the most extensive datasets in our repository could take upwards of 60 hours to download under normal circumstances.

You don’t need to create a dataset for every file and don’t confuse datasets and files. Datasets contain the metadata, the descriptive and administrative information about your project, and the files from the project. Files can be organized into a folder structure or tagged by keywords within a dataset. Do users need to understand the relationship of the file hierarchy, or do they need to filter them by keywords? Thinking about structure can make work easier for you and your users. 

The ASU Library indexes Dataverse at the dataset level into our library search interfaces. Provide as much information as necessary and limit the number of datasets requiring repeated information that could congest and confuse search results.  

You don’t have to go this alone. ASU Library experts provide consultations and can help get you started before you spend the time uploading files, only to realize you need to rethink their structure and sharing method. 

FAIR Data Sharing and the CARE Principles

Before publishing, make your research data FAIR: Findable, Accessible, Interoperable, and Reusable. Benefits of the FAIR Principles include:

• Promoting Research Impact – making your data available for discovery increases the likelihood of others finding your work, as well as increasing its relevancy

• Upholding Funding Requirements – depositing your data in a disciplinary repository or ASU’s Research Data Repository facilitates granting agency and institutional data sharing and curation.

• Supporting Preservation – depositing your research data begins a preservation process that ensures your data is maintained over the long-term

• Fostering Data Utilization – applying comprehensive metadata to your research data provides essential context for yourself and others to utilize in the future

• Encouraging New Discoveries – making your data available helps others build on your findings and make scientific discoveries with potential benefit to society in unimaginable ways

• Endorsing Open Access – sharing your data in this way, you support the open access movement, which in turn helps the scientific community and society as a whole

The people and purpose-oriented CARE Principles for Indigenous Data Governance complement FAIR and reflect the crucial role of research data in advancing Indigenous innovation and self-determination. Our curatorial team is informed by the CARE Principles and will work with you where appropriate.

The Essentials: What You Need To Know

“Everything Should be made as simple as possible, but no simpler.” – Albert Einstein

The essential Considerations that need to be Answered

There are a lot of questions that must be addressed throughout the planning process. Understandably, at times it can feel overwhelming. However, as the old saying goes, it is possible to eat an elephant. You just have to do it one bite at a time. So, approach each question independently. Break things down until they are manageable for your purposes. You do not have to do this alone. ASU’s Office of Research Data Management research data managers is here to help plan and execute your active research data needs.

You can review our library tutorials and read our guide that features an introduction to the DMPTool which can be used to help build your proposal and request feedback. See: Other data publishing considerations

Components of Responsible Data Management and Curation

The following elements, if planned out appropriately, will set you up for success when it comes time to submit your data to ASU’s Research Data Repository. Don’t find yourself scrambling at the last minute. If you utilize these recommendations, meeting ASU’s submission requirements will be a much smoother process.

Big picture data curation and management planning

Focusing on research data curation