Reusing and benefiting from existing datasets is a fundamental motive of data opening and sharing. Research data are valuable resources that often require a lot of time and money to create. It is thence worthwhile to consider reusing existing datasets that previous studies have generated and publicly archived. Yet reusing data is not only about saving time and resources. It also improves data repeatability and verifiability, and thus the reliability of scientific outputs.
At the same time, optimal use and reuse of archived data become possible only when the accessibility and reusability of research data have been ensured. Properly managed and openly published research data with appropriate licenses enable and facilitate shared use. FAIR data principles in the section below give guidance on how to make your data truly open and reusable. See also Sharing data below about how to open and publish your data.
Services for searching datasets include:
Some new initiatives that aim to collect and mediate open data include:
When reusing data, good practices for the attribution of authorship and data citation must be followed. See the citing instructions Citing archival data by the Finnish Social Science Data Archive. See also how to reuse research data by OpenAIRE.
The openness of research data increases the visibility and impact of your research, speeds up the adoption of your research findings and the creation of innovations, and facilitates disciplinary and interdisciplinary collaboration, all both within the scientific community and in the wider social circle. Open data improves the transparency and reliability of science, empowering and democratizing science.
Research data and related published research results produced at Hanken ought to be open and available for shared use. The discoverability and citability of research data ought to be ensured.
When opening your data, consider the following questions:
1. What part of the data will be opened and published?
2. Where will the data be opened?
Data storage services provided by CSC: IDA - Research Data Storage Service, part of the Fairdata services. Read the instructions on how to Apply for IDA storage space.
The Finnish Social Science Data Archive (FSD) and their catalogue Aila. You can contact them directly on their service address asiakaspalvelu.fsd@uta.fi for further assistance.
Zenodo by the OpenAIRE project and CERN.
3. When will the data be available? Do you need to set any embargo period?
4. Will some part of the data be destroyed? More information, see Data disposal by the Finnish Social Science Data Archive (FSD).
5. Which license will you use to open and share your data? Agreements on data ownership and other intellectual property rights must be concluded before commencing any actual research activities.
More information, see Five steps to decide what data to keep by the Digital Curation Centre (DCC).
Long-term preservation means that data is preserved for more than 25 years. When creating your data, you need to consider how long it will be preserved. Also remember to check discipline-specific, funder-related, and publishers' data preservation time length requirements. A data archiving plan is part of research quality and transparency. If your data has long-term value, consider:
More information, see Five steps to decide what data to keep by the Digital Curation Centre (DCC).
The FAIR data principles, formulated by Force11, are guiding principles on how to make data truly open. FAIR is an acronym for "findable, accessible, inter-operable, and re-useable":
To be Findable:
To be Accessible:
To be Interoperable:
To be Reusable:
The FAIR data principles can be formularized as “Findable+Accessible+Interoperatable=Reusable.” Making data reusable, and reusing and benefiting from existing datasets, are the fundamental motives of open data.
FAIR is not equal to open or free. Data can be closed and paid for yet perfectly FAIR, while data that are open and free are often not FAIR, and thus regarded cost-inefficient and re-useless.
Most of the FAIR data principles concerns metadata. It is crucial to describe and document your research data to make them truly open and reusable. See Data documentation and metadata in the following section.
More information, see:
The Fairdata services are offered by the Ministry of Education and Culture and produced by CSC – IT Center for Science Ltd for data management, data storage, metadata creation, dataset dissemination and distribution as well as digital preservation of research data. The services include:
Read How to make the research dataset FAIR? and learn more about the Fairdata services.
Documentation (describing the data, human readable) and metadata (data about data, the who, what, when, where, why, how of your data, computer readable) both provide information about the data. When making data FAIR, metadata plays a crucial role. Systematically described research data is the key to making your data understandable, findable and reusable. Data quality improves with clear and detailed documentation and metadata.
Use Fairdata Qvain, a metadata tool, to describe and publish your datasets. Qvain is part of the Fairdata services to support your research data to go FAIR.
Remember that you shall register both your publications and datasets in Haris - Hanken's research database. The information you have registered in Haris about your datasets will be transferred to Etsin and available at the Ministry's research database portal/tutkimustietovarannon tiedejatutkimus.fi-portaali.
More information, see: