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Research Data Management: Open and Reuse

Open your data

As said in Tampere higher education community's Open Science and Research policy, research data related to research results is by default open and meant for cooperative use. However, confidentiality should not be compromised, and hence, sharing and opening your data should follow the principle: as open as possible, as closed as necessary. When closing a project, evaluate which materials should be preserved and for how long and which materials should be disposed of permanently. There are several benefits to open your data

How to open your data?

There are different ways to open your data. Your preference may depend on the customs in your discipline or on the expectations of your funder. Some publishers also has requirements for the length of time for preservation regarding data related to a publication.

It's also recommended that source code be shared and distributed where it is most appropriate, as determined by funding and other factors. Read more about opening your codes and softwares.

When publishing your data:
  • Plan beforehand! Having a data management plan helps you.
  • Document your data well and create adequate metadata. Remember to publish the metadata as well!
  • Check that there are no ethical or legal issues that prevent you from publishing your data
  • Check that the terms of reuse of your data are clear (licenses)
  • CC0 waiver is the most efficient way of facilitating reuse of your data, but Creative Commons 4.0 can also be recommended for open data. See the guide on How to select a Creative Commons License
Does your research include processing sensitive or confidential data?

Data with personal information can only be published anonymised, when it is no longer subject to data protection legislation. Pseudonymised data is still personal data and cannot be opened without explicit consent for that purpose.

In some cases, personal information can be shared, if the original processing purpose allows it. However, if the original consent form does not refer to the further use of the data, opening the dataset may require requesting new consent from the data subjects. If you plan to share data which includes personal information, please contact dpo@tuni.fi.

Please remember that you should still be able to open the metadata of the data holding personal information, although the actual data cannot be.

Archiving and long term preservation

The aim of long-term preservation is to keep data usable and comprehensible for tens or even hundreds of years. If your data has a long term value, consider following:

  • What part of the data is archived?
  • Where will it be archived?
  • How long will the data be preserved?
  • Are there some costs related to archiving? Who takes care of them?
  • Will some part of the data be destroyed?

The Ministry of Education and Culture is developing a service for the long-term preservation of valuable research data (Digital Preservation Service for Research Data, Fairdata-PAS). Tampere University has determined the process for identifying research data that will retain its value for a longer period and transferring it to the service. If you think your data will be suitable for Fairdata-PAS, contact researchdata@tuni.fi.

 Tips for best practices 
  • When you start your project and begin to collect your data, consider also how long the data should be preserved.
  • Submit your data selected for long-term preservation to a certified data repository or data archive such as Finnish Social Science Data Archive,  Language Bank of Finland or Mendeley Data provided by Elsevier
  • It is recommended to use a disciplinary-specific repository for long-term data preservation. You may also use general data repositories such as ZenodoEUDAT or IDA.
  • Remember to check publisher, funder, disciplinary or national recommendations for data repositories, data archives or data banks, and their preservation time requirements.
Does your research include processing sensitive or confidential data?

Traditionally, it has been recommended to destroy all sensitive data after the research project has ended, as storing it is risky and requires special arrangements. However, depending on research permits, datasets containing sensitive personal data may also be stored in the Fairdata-PAS service. What is important, is that research participants must be informed about preservation of data and the basis of the duration of preservation.

Archiving datasets that contain sensitive personal data requires a storage permit from the National Archives of Finland. The data must be minimised before storage. The further processing of such data requires a research permit.

  • Remember also to plan the safe disposal of the data.
  • Please remember that the anonymisation and disposal or archiving of data must be carried out by the expiry of the relevant research permit.
  • Genuine anonymisation requires that both direct and indirect identification are made impossible, in addition to which the identification key must be destroyed.

Citing data

Data citation gives credits to a data creator and facilitates tracking the usage and impact of the data. The researcher's position as the creator or collector of research data can be acknowledged by accordingly citing research data. Data citation practices are guided by copyright laws, data archive guidelines and the general rules of the scientific community.

Data storage services have their own general guidelines on how to cite data. Additionally, individual datasets may have citation guides. If there are no specific citation guidelines, data should be cited just like any other publication. Crosscite is a tool that helps you format your data citation.

Read more:

CC License

Data repositories

When choosing a repository:
  • Check the recommendations of the publishers, learned societies, and funders of your own field of science. Where have you or your colleagues in the same field published data?
  • The repository publishes machine-readable metadata and uses a known metadata standard. This helps search engines and other databases find the data.
  • Trustworthy repositories are assessed with a certification such as Core Trust Seal and ISO 16363 standard, which indicate that they have transparent and properly documented policies and procedures.
  • Some repositories allows you to set restrictions (such as embargos, technological access restrictions, data use agreements and licenses) on how your data can be reused. However, these may have unwanted consequences and eventually, they may prevent others using your data.
  • Also, some repositories may have specific requirements concerning deposited data. To make sure your data meet all requirements, please contact repositories already in the early stage of your research project.
  • The repository assigns persistent identifiers (PID), such as DOI or URN, to your data. A persistent identifier is a long-lasting reference to a digital resource and makes your data easier to cite.
List of data repositories

The list consists of well known data repositories. Many of the services accept any kind of data types and files, but some of them are specialised in specific data. If you don't have any established repository in your field, use of these services is highly recommended.

  • Aila Data Service – Reseach data deposited in the Finnish Social Science Data Archive (FSD), with extensive metadata both in Finnish and in English
  • Zenodo – easy to use and suitable for any kind of data files smaller than 50gb. Fuelled by CERN and OpenAIRE.
  • IDA –  Offers a free quota for Finnish Universities for storing data during the active phase of the research in an immutable state, sharing data within the project group, and publishing the data as a dataset. Part of the Finnish Fairdata Services.
  • EUDAT – EU Horizon 2020 funded service for storing, opening, sharing and browsing data.
  • Figshare – Multidisciplinary data archive.
  • The Language Bank Fin-Clarin –  A comprehensive text and speech corpora. Basic use is free for academic researchers and students.
  • Array Express EMBL-EBL – Functional genomics data from microarray and sequencing platforms.
  • Dryad – Data archive focused on natural sciences and medicine. Contains research data linked to scientific publications.
  • GitHub – Service for opening and sharing code.
  • Worldwide Protein Data Bank PDB - 3D structure data and metadata of proteins, nucleid acids, and complex assemblies.
Other data services
  • Re3data.org – Registry of Research Data Repositories gathers information on different data archives from different subjects that offer long-term data storage.
  • Etsin – Research data finder, which contains descriptive information (metadata). Part of the Fairdata Services.
  • Qvain – Research Dataset Metadata Tool. Part of the Fairdata Services.
  • Paituli spatial data service – Includes datasets from following data providers: Finnish Meteorological Institute, National Land Survey, Traffic Agency, Agency for rural affairs, Statistics Finland and Finnish Environment Institute (SYKE). Part of Avaa research data portal.
  • Scientific Data – Research data journal's list of recommended data repositories.
  • See also Finnish Biobanks.

Photo by Pixabay

Data disposal

Deleting and emptying the recycle bin containing the deleted files is not an irreversible way to destroy unnecessary data. Deleted data can be recovered even after reformatting the hard disk. Use special file deletion software in order to overwrite the data or demagnetise the hard disk. Storage devices can also be mechanically crushed into an unreadable state.

  • Finnish Social Science Data Archive's (FSD) guidance on data disposal.

Photo by rawpixel.com from Pexels

Funders' requirements about Open Data

Photo by pxhere. CC0 Public domain.

Contact us

Is there something you did not found in this guide? Or is some important information missing? You can always contact us for further information, and we will help you with the research data management.