Data sharing during the project
If other team members need to access the data, they can do so through your chosen storage solution if it allows for it (e.g. if you use UiO OneDrive, you can share selected folders with your team members. You can do the same in TSD or Educloud, but you need to contact IT to set up the folders with granulated access). This will vary from solution to solution and may sometimes involve contacting IT support. For more information on each of these solution’s visit UiO’s storage and collaboration.
In some cases, you may need to send or transfer files rather than granting access to a storage solution. In that case, you can consider using FileSender which can transfer files up to 1000GB in size.
Remember that the classification of your data will determine what solutions you can use for both storage and sharing. For more information about classification and storage, visit our data classification and storage page.
Research projects with external collaborators
Projects with external collaborators that will be processing personal data are required to enter into legal agreements which govern the processing, transfer and sharing of personal data. More information about how to manage personal data can be found on UiO’s Privacy for Researchers website.
UiO has developed standard templates for some of these agreements (in Norwegian with English templates).
Data sharing after the project is finished
Once your project is finished, you can preserve your data by putting it in a data archive (i.e. a data repository), publishing it alongside your article, or writing a separate data paper. Generally, all data that support a research project or scholarly work should be archived in accordance with UiO's policy and guidelines and the FAIR principles.
UiO's Data archiving pages give an overview of the different options available for archiving your data.
Which data should I archive?
- Is your data valuable for the field and has a potential for reuse? For example, is it unique and novel? Many different types of new datasets can be valuable to other researchers.
- If you conduct research with human subjects: is your data anonymous (i.e., without any identifiable information about your research subjects) or can they be anonymized, so that you can share it according to data protection regulations, unless you have received explicit permission from your subjects for sharing their identifiable information?
- Is it practical to archive your data based on its size and scale and the potential cost of storing it long-term? These practical issues are less important the higher dataset's uniqueness, novelty and general value for the field.
Note that all points above also apply to metadata. For example, if your dataset cannot be shared for some reason (e.g. has general and sensitive personal data that can’t be anonymized), you can archive metadata about your project (such as descriptions of the dataset or datapoints, descriptions of the variables, etc.). You could also provide instructions for how a researcher could apply for access to the dataset.
Finally, a general rule of thumb should be that all articles should be published with supporting data. This is also becoming the standard in many journals. Just make sure that you choose an appropriate license.
How do I prepare my data for archiving?
Most data require some tidying before you can archive and share them. Remember that other researchers, not involved in your project, will need to understand what is in the dataset(s) when they access your data. Make sure that your data is well organized and documented. In addition:
- Choose accessible, patent-free and open file formats (you can find examples of preferred file formats for archiving here)
- Reduce complexity and size by grouping similar files in zip bundles (to make the upload and download easier)
- Consider size limitations (does your chosen archive have restrictions on file size?)
You can see an example of what an archive may require from you in the DataverseNO deposit guide.
What are the benefits of data sharing and publishing?
There are many different reasons for why it is beneficial to share and archive data, apart from complying with publishers’ and funders’ requirements. Sharing data:
- Makes research more robust and reliable by helping prevent data manipulation and fraud
- Increases the citation rates of the project outputs
- Helps avoid data duplication, that is different research groups collecting the same data
- Increases scientific transparency (by making research more open) and reproducibility (by allowing other researchers to reuse your data and reproduce your results).
- Gives more visibility to your own research
- Opens up for new uses of your data and facilitates collaborations with other researchers around the world
This means that archiving and sharing data contributes to both making science more open and improving your own research quality and visibility.
Need advice?
Contact us at: research-data@uio.no