It is important that you document your research data and methods throughout the research project. According to Uniarts Helsinki research data policy research data is open by default, so researchers need to consider this aspect as well.
Some journals and publishers require that the research data is open. It’s important to recognize and separate that part of the data that’s been used from the rest of the dataset, and to archive it separately (freezing the data). Create adequate metadata and publish it (see e.g. Etsin) to improve the findability and visibility. To ensure the reuse of the data, it’s recommended to select a data repository that issues a permanent identifier (URN, DOI); see e.g. sections below about Fairdata services and "Other data archives and registeries".
(Source: TUT research data guide, CC BY)
There are degrees to how open or public the data is. The creator or collector of the data can usually determine how openly the data is available to other users. You can e.g. choose a suitable Creative Commons license. Open science coordination has recommended to use CC BY licenses when the content of the data allows this.
According to Uniarts Helsinki’s research data policy, the metadata should always mention the owner of the data and any legal restrictions to reuse. Open publishing should always consider copyrights issues. Data with personal or sensitive data must be taken into account in RDM plans.
Fairdata services include services that support the findability, preservation, and management of research data. The services “enable verifiable and reproducible science and secure p, reservation of digital research outputs”. The services include IDA research data storage, Etsin research data finder, Qvain research dataset metadata tool, and Fairdata PAS for long-term preservation of valuable data. More information from the links above and this guide.
Using these services has many benefits: first, the data are secured for re-use and they have a permanent identifiers e.g. for citations. Secondly they are easy to use to share your data and find new data. Thirdly, it’s easy to meet the funders’ requirements.
Image: Fairdata.fi, CSC
Research data storage service IDA “enables storing and sharing research data. Data stored in IDA (ida.fairdata.fi) can be described as a dataset, published, and opened for others to download utilizing the other Fairdata services”. Read more from the IDA user guide.
(Click “CC” for English subtitles in the video above)
The service is not suitable for storing sensitive personal data. If you are going to manage sensitive data, please contact the library.
Metadata makes the research data visible: metadata makes it easy to find and get an overview of the data.
Qvain, a tool for describing research data, aims to make the description of research data as easy as possible for the researcher: the data is entered by filling in a form that clearly indicates, among other things, the mandatory fields. You can save and edit your data as long as you like, and then publish it at any time.
The description of the data can be linked to files in the IDA service, but it is also possible to link to data outside Fairdata or to publish only the description of the datadata. The published data will appear in the Etsin service regardless of the description method.
(Source: https://www.fairdata.fi/en/qvain/)
Etsin enables you to find research datasets from all fields of science. Etsin contains information about the datasets and metadata in the national Fairdata services, the Language Bank of Finland, the Finnish Social Science Data archive and the Finnish Environmental Institute, and new sources will be included.
The published metadata on the dataset is open to everyone. The data owner decides how the underlying research data can be accessed and by whom. Etsin works independently of actual data storage location and contains no research datasets. Datasets can be described and published through the Qvain service.
Read more about the subject from the Open science coordination in Finland -website, Finnish Social Science Data Archive’s Data Management Guidelines, and Fairdata services.