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Research data management
Here you will find information about how to plan and execute the management of your research data, including how to write a data management plan, store, and share your data.
We are very interested in understanding what you think about the information we provide. Please send questions and comments to datahantering@sh.se.
Planning your data management
This section provides information about what you must do before you start gathering and processing data in a research project.
The process of managing research data continues throughout a research project’s lifecycle. It includes the collection, documentation, processing, storage, sharing, archiving and deletion of data. If your project handles research data, that data must be managed in accordance with the university’s guidelines.
The university’s template for data management plans is designed to make it easy to follow the guidelines and to avoid any data management risks. Under the guidelines, all research projects that manage research data must therefore write a data management plan.
Plan your data management using the following five steps. You can contact the university’s Data Management Support at any time, by emailing your questions to: datahantering@sh.se.
1) Decide whether you manage research data
Do you manage research data? Research data is empirical information that is collected or compiled in a research context. In addition to measurement data generated by research in the natural sciences, research data can include survey responses, recorded interviews, systematic compilations from archives or other textual sources, or observations captured on image or video. Systematic information about physical objects, such as works of art or archaeological collections, is also considered research data.
However, research data does not include such reference lists and bibliographies as appear in all academic publications, nor personal notes, thoughts, and argument sketches made in the writing of an article, as these do not document specific observations. Physical samples are also not in themselves considered data, although measurements and tests conducted on the samples generate data.
If you are unsure whether your project manages research data, you can contact the university’s Data Management Support at datahantering@sh.se.
2) Make sure your project has a registration number
If you manage research data, your project needs a registration number. This is used to link your data to the project. If your project is externally funded, it will already have a registration number that matches the one for your funding application. If your project does not have a registration number, request one from the central records manager using the procedure described on the employee web at Requesting a registration number.
3) Order storage space for archive copies of your data
All projects must have a folder in Dataspar, a storage space where the project’s research data is kept for archival purposes. These can be ordered via the employee web, at My page → ICT cases → Order storage space on Dataspar. Dataspar is secure and may also be used for other project purposes, but can only be accessed by participants with an SH-Account. Read more about which data must be preserved in the section on Retaining research data for archival purposes further down this page.
4) Write a data management plan
Once you have a registration number and have ordered storage space on Dataspar, you are ready to write a data management plan. If your funder doesn’t require that you use of a specific template for the data management plan, use the university’s. Read more about this in the Data management plan section. Use the information on this page to help you write your plan. If you need more help, you can contact the university’s Data Management Support at datahantering@sh.se. You can also refer to the section on What support does the university offer?, below, for more information about where to find help.
5) Send the plan to the central records manager
Once you have written your plan and added the project’s registration number to it, send it to registrator@sh.se with a copy to datahantering@sh.se.
The data management plan is a document that systematically describes the various aspects of data management throughout the project’s lifecycle. Writing a data management plan ensures that you do not expose yourself to any risks in your data management, and that your data management is in accordance with university guidelines and external requirements.
Therefore, according to university guidelines, each research project that collects or generates new research data must write a data management plan. Most external funders also require that a data management plan is drawn up at the start of the project. The plan can be updated once the project has started. Thus, it may include provisional information at the beginning of a project, that can be specified in more detail at a later stage.
Every updated version of the data management plan must be sent to registrator@sh.se, preferably with a copy to datahantering@sh.se.
Template, data management plan
If your funder doesn't require that you use of a specific template for your data management plan, use the university’s template (link below). Use the information here on the employee web to help you complete the plan. If you need additional help, you can contact the university’s Data Management Support via datahantering@sh.se or any of the support functions in the next section, What help does the university provide?
NB! Use Adobe Acrobat Reader to complete the template, not your browser.
When planning your research data management and writing your data management plan, start by using the information here on the employee web and the support provided in the data management plan template. If you have further questions, contact the support functions listed below.
General questions
If you have general enquiries about data management for a research project, or do not know where to direct your question, contact Data Management Support via datahantering@sh.se.
Legal questions
If you have legal questions about data management, such as about processing personal data, please contact the data protection officer at dataskydd@sh.se.
Questions about archiving
Questions about archiving research data can be addressed to the archivist at arkivarie@sh.se.
Software and technical issues
Software is ordered via the employee web → My page → Computer and software cases → Order software. Questions about software purchases can be sent to licenser@sh.se.
If you experience technical issues with the university’s computers or IT systems, register a case with IT support on the employee web, under My page.
Ethical and secure data management
This section provides information about assessing your research data’s level of confidentiality and need for protection and, given this assessment, what you must and may not do with your data.
All research data used in research projects at Södertörn University must be managed in a legally correct manner and in accordance with good research practice. Research misconduct is a serious deviation from good research practice, specifically taking the form of fabrication, falsification or plagiarism. You can read about research misconduct and good research practice on the employee web.
When it comes to research data management, good research practice includes:
- Managing the subjects in your research with respect and care and in accordance with legal and ethical regulations.
- Designing, conducting and documenting data management in a careful and well-considered way.
- You and the university ensuring that research data is managed and appropriately retained for a reasonable time.
- You and the university ensuring that data is available as openly as possible and as restricted as necessary and, where applicable, in accordance with the principles of FAIR data management (read more in the section on Open publication of research data further down this page).
All staff at Södertörn University have joint responsibility for ensuring compliance with good research practice. If you suspect any deviations from good research practise, you should contact the university’s Council for Research Ethics.
Will you process personal data as part of your research project?
Personal data is information that can be linked to a living person. Information about deceased persons is not considered personal data.
Personal data includes:
- name
- address
- personal ID number
- email address
- ID card number/passport number
- telephone number
- IP address
- car registration number
Video and audio recordings, such as recorded interviews, are also considered personal data, because individuals can often be identified from faces or voices.
Some personal data are considered privacy-sensitive and should be given extra protection. These include:
- information about salaries
- evaluative information (such as results from personality tests)
- information about social relationships
- personal ID number
If your project processes personal data, specific requirements must be fulfilled for the processing to be lawful. Try not to collect personal data if it is not necessary for your research and you can avoid including it in the project’s data.
If you are going to process personal data, you must read Personal data in research at the employee web.
Sensitive personal data requires an approved ethical review before processing.
This concerns data of the following types:
- ethnicity
- political opinions
- religious or philosophical beliefs
- membership in a trade union
- health and medical history
- a person’s sex life or sexual orientation
- genetic information
- biometric information that is used to unambiguously identify a person
- criminal convictions, proceedings and offences
As with all personal data, avoid collecting sensitive personal data if this information is not necessary for your research.
Data on criminal offences are not sensitive personal data under the GDPR, but still require an approved ethical review before processing,
If you are going to process sensitive personal data in your project, read more about Ethical review at the employee web.
Your data may require additional protection because it contains information such as trade secrets or about security-sensitive activities. If you have any questions about this, you can contact the data protection officer: dataskydd@sh.se.
NB! If your data falls under the Säkerhetsskyddslagen (2018:585) External link, opens in new window., you must contact the director of Campus and ICT Services.
Information classification describes how sensitive or worthy of protection a particular data set is. For research data, the information classification primarily indicates how data should be stored and shared. The classification is also used during the confidentiality assessment that needs to be conducted if there is a disclosure request for your research data, as an official document.
Three security aspects
The university’s model for information classification has three security aspects:
- Confidentiality
Data may not be accessed by unauthorised persons. - Integrity
Data must be accurate and reliable, i.e. not altered or destroyed. - Availability
Data is accessible and usable by authorised persons when needed.
Each of the three safety aspects is given a classification from 0 to 3. This classification is based on an assessment of the severity of the consequences if a security aspect fails.
How the university’s research data is classified
Södertörn University’s research data are given the following standard classifications:
- All research data are class 2 in the integrity and availability categories.
- No research data has class 0 for confidentiality.
As a researcher, you thus only need to assess whether your data is class 1, 2 or 3 as regards confidentiality.
When you classify your data, you can divide it into data sets. One data set may consist of one or more files. Each data set is then given a confidentiality classification.
Guide to confidentiality classification
Class 3
Personal data that includes information of the following type:
- ethnicity
- political opinions
- religious or philosophical beliefs
- union membership
- a person’s health or sex life
- genetic or biometric data
- information relating to criminal offences, for example that someone has committed a crime or is suspected of a crime
Also: code keys for pseudonymised personal data that contains information of the types listed above, and information that is confidential for other reasons, such as national or trade secrets.
Class 2
Information containing privacy-sensitive personal data:
- information about salaries
- evaluative information (such as results from personality tests)
- information about social relationships
- personal ID number
Also: code keys for pseudonymised privacy-sensitive personal data.
Class 1
All other research data.
How you may store and share the data set during and after the project is now determined by the confidentiality classification you have given it. (See the section on Approved storage spaces, below.)
Read more in the section on examples of information security and classification on the employee web (in Swedish).
Storing and sharing your data during the project
This section tells you where you can store your research data during the project, based on the data set’s confidentiality and need for protection, and who needs access to it during the project.
The table below shows the storage spaces for research data that are provided by the university. You can see there which types of project participants (internal or external to SH) may be given access to the space. You can also see what confidentiality classes the space is approved for. Storage of class 3 data may require manual encryption with a personal key, see the box Data encryption, below.
Dataspar | SH Teams | SH OneDrive | SH email | |
|---|---|---|---|---|
Accessible by | Only project participants | Internal and external | Internal and external project participants | |
Approved for confidentiality class | ||||
1 | Yes | Yes | Yes | Yes |
2 | Yes | Yes | Yes | Personal encryption |
3 | Yes | Personal encryption | Personal encryption | Personal encryption |
Dataspar
Dataspar is an internal network drive on a local server that is specifically for research data and can only be accessed by people with an SH account. The storage space is approved for all confidentiality classes and does not require manual encryption. You can order a project folder on Dataspar via the employee web, at My page → ICT cases → Order storage space on Dataspar.
SH Teams
This is Södertörn University’s procured Microsoft Teams, and the recommended solution for sharing research data with external project participants. A research project can create a team to which internal and external project participants can be invited. You create a new Team for your project on the employee web, under Tools → Teams. Class 3 data must be manually encrypted if stored in Teams (see box on encryption, below).
SH OneDrive
This is Södertörn University's procured Microsoft OneDrive, to which all university computers automatically connect. Individual files and folders can be shared with external parties. OneDrive is less structured than Teams. Shared content is deleted if the owner is no longer employed by the university. Class 3 data must be manually encrypted if shared from OneDrive (see box below).
SH email
Research data with confidentiality class 2 or 3 must be manually encrypted if shared in an email (see box on encryption, below).
Other storage spaces and cloud services
Box, DropBox, Google Drive, private OneDrives and other external cloud services are not approved for the storage of research data, as no official backups are made.
The university has a responsibility to ensure that research data is not destroyed or lost, so they must be stored where backups are made regularly. Therefore, research data may be stored on external storage devices such as USB sticks, external hard drives, local laptop hard drives, measuring instruments and recording equipment only while strictly necessary (e.g. during data collection in the field). These data must be transferred to one of the approved storage spaces listed in the table above as soon as possible.
When measuring instruments and recording equipment are used to collect data with confidentiality class 2 or 3, you must ensure that the data is not automatically uploaded to a cloud service such as Samsung Cloud or iCloud (Apple). Make sure you switch off this feature in the app before starting to collect data.
Research data with confidentiality class 2 or 3 may need to be encrypted. (See the sections on Information classification of research data, Ethical and secure data management, and approved storage spaces, above.) Instructions for different types of encryption follow below.
Encrypted email in Outlook
Emails can be encrypted using Outlook’s encryption feature. This can be found under Options → Encrypt when you create a new email. You can select “Encrypt,“ or “Do not forward” if you want your message to be both encrypted and impossible to forward, copy and print. Encryption works for all recipients but does not protect attached files. Files must be encrypted manually, see the instructions below.
Encrypt files manually with your own key
You can encrypt data files and other material manually, using encryption software. Instructions for three different programs are provided here.
7-zip (Windows) and Keka (Mac)
These programs allow you to encrypt multiple files into one encrypted folder that can be shared. 7-zip and Keka can open files encrypted with either program. The programs can be ordered from the university, place an order on the employee web → My page → Computer and software cases → Order software.
Everyone permitted to access the files needs the encryption password, so this must be shared unencrypted. It strongly recommended that you share the password at a face-to-face meeting and do not send it electronically. If it must be sent electronically, you should use a different communication channel from the one through which the data is shared.
7-Zip encryption guide External link.
Keka user’s guide External link.
Kleopatra (Windows)
Kleopatra allows you to encrypt files and folders without the need to share a secret encryption password. This means it is more secure than 7-zip and Keka for sharing information, and Kleopatra’s standard encryption is also stronger. The initial installation procedure is a bit more involved than for 7-zip and Keka, but using it thereafter is straightforward.
Kleopatra comes with the software package Gpg4win. Gpg4win can be ordered from the university, place an order on the employee web → My page → Computer and software cases → Order software.
Kleopatra user’s guide External link.
Kleopatra is available for Windows. Mac has an equivalent called GPG Suite. Any application that encrypts using the PGP standard can encrypt and read material encrypted with Kleopatra.
Retaining research data for archival purposes
This section contains information on how and where research data must be retained as part of the university's archive, and what data must be retained.
Research data generated in projects at Södertörn University are normally official documents and included in the university archive. They can therefore be requested by the public in accordance with the principle of public access to official documents. It is also vital that research can be reviewed, such as in the event of suspected research fraud. The retention of research data is therefore also an important element of good research practice.
According to university regulations, research data must be retained for ten years. After that period, the project leader for the project in which the data was generated, or the head of school or equivalent if the project leader is no longer at the university, should decide whether the data set can be deleted (weeded) or whether it should be permanently preserved. The university archivist can assist during this deletion review.
Södertörns högskolas Informationshanteringsplan (in Swedish) is the governing document.
Only data files of the following types must be retained. Please note that the same data set can fulfil several of these conditions, and that satisfying one of the conditions is sufficient for it to have to be retained.
Raw data files
This includes, for example, unprocessed survey responses, audio and video recordings and images, and files created by measuring instruments.
Data files that have served as the basis for a scholarly publication
Data necessary for conclusions in a published, peer-reviewed article or book must be retained. Research results that have only been presented at a conference or published somewhere as a draft without peer review are not included.
Data files that are regarded as finalised
All data files that have been finalised—i.e. no additions or other changes will be made—must be retained. Data material that is unfinished and currently being processed does not need to be retained, unless it fulfils one of the other conditions.
NB! Data requested from archives or registers of Swedish government agencies, which have not been processed to the point that significantly new data objects have been created, do not need to be archived at Södertörn University. However, for smaller data sets, it can be convenient to keep copies of these data together with the project’s other data.
When planning your data management, you order a folder on Dataspar, the university’s internal storage space for research data. (See the section Planning your data management at the top of this page.) A subfolder called “Data Archive” is automatically created in this folder. This is the folder into which you copy the data files that meet the conditions for retention in the section above.
The folder also contains a file named “Data documentation - [reg no].docx”. This is a template in which you enter certain information about your data. This information is needed in case someone other than you has to perform a confidentiality review of the data due to a request for disclosure. It is also used when it is time to decide whether these data should be deleted or permanently preserved in the university archives (deletion review). The template includes instructions for filling it in.
This procedure for preserving research data replaces the previous convention according to which the researcher was responsible for a research project’s data being preserved for ten years. This means that once it has been placed in the data archive folder on Dataspar, researchers no longer need to store their project’s data elsewhere.
If you have research data from a previous project on a local hard drive or external storage device, you should move it to the approved storage space for long-term retention.
Instructions:
- Make sure that the project the data set belongs to has a registration number. If the project does not have a registration number, request one from the chief records officer according to the procedure described in Requesting a registration number on the employee web External link..
- Order a folder on the Dataspar storage space on the employee web under My page → ICT cases → Order storage space on Dataspar.
- Move your old data to the data archive folder in the new storage space by following the instructions in the sections above.
Open publication of research data
This section has information about what making research data openly available means, and how to do so according to the principles of open science.
Making research data openly available entails documenting them and publishing them openly, so others can find them and use them in a new context.
Harmless data can usually be made directly downloadable, while other data is only disclosed to someone if specific conditions are met. Read more about this in the section What data can be made available? below.
There are good reasons to make research data openly available. One important reason is research transparency and the potential to examine research results. Another objective with making data available is to get as much good as possible out of the investment made during data collection, by researchers, research subjects and funders, by making it possible to reuse data. For these reasons, it is the goal of the Swedish government that by 2026 all research data generated with public funding is made as openly available as ethical and legal considerations allow. Read more in the government bill, Proposition 2024/25:60, Forskning och innovation för framtid, nyfikenhet och nytta External link. (in Swedish).
Three things that available data should or must have:
A permanent link
A minimum requirement for a data set to be considered openly available is that it has a permanent link, called a persistent identifier (PID). This link can be used to refer to the data set, for example in a publication, and by following the link the data set can be directly downloaded or requested. There are different standards for persistent identifiers; the one most used for research data is called a DOI (Digital Object Identifier) External link..
Descriptive metadata and documentation
This is information about the data set, and includes things like the research field, data format, and time, place and method of collection. Some information is machine-readable and used by a search engine to find data sets and filter search results. Other documentation is necessary to ensure that the data set can be used in a rigorous manner, for example in a new research context.
Standard formats
Using open and well-documented standard formats for the data files allows them to be read by new users without specialised software, now and in the future.
The FAIR principles are an evolution of the requirements for making research data available. FAIR stands for Findable, Accessible, Interoperable and Reusable. FAIR is a vital element of the work on open science. You can read more about FAIR at The Swedish Research Council External link..
Available research data are stored in a repository, also called a catalogue. Data published in the repository can be found using a web search engine. Some data sets, once found, can be freely downloaded, others require you to send a request for disclosure if access requires that certain conditions are met.
The organisation that runs the repository assigns a DOI to each uploaded data set. The repository can also place requirements on data uploads to ensure some degree of compliance with the FAIR principles. Research data repositories may thus be of varying quality, depending on how well their data conform to the FAIR principles.
There are many different research data repositories, of varied quality and focusing on different research fields. If a research project at Södertörn University does not have specific reasons for choosing another repository, we recommend the Swedish National Data Service's (SND) research data catalogue External link.. SND’s repository maintains a high standard, meaning that research data stored there can be found base on good metadata and are well documented.
Data published at SND are searchable using Researchdata.se External link., the Swedish dataportal External link., the European dataportal External link., Google Dataset Search External link. and other international search engines.
Read more about how to publish your research data with SND. External link.
Researchdata.se also has information about making research data openly available. External link.
The university’s Data Management Support can help you with the publication. Contact them via datahantering@sh.se.
Some research data can be made available without restrictions, so a user can download the data set directly. This could be data that does not contain any personal data, trade secrets or national secrets, and is not protected by copyright.
Other research data can be made available with limited access. This means that a description of the data set (its metadata) can be found by following a DOI or getting a hit in a search engine, but the data set cannot be downloaded; instead, it must be requested. In the event of such a request, a confidentiality review is performed. If the client does not fulfil the conditions for accessing the data set, the data is not released.
Making available just the metadata for a dataset that for some reason cannot be shared freely, and not the actual data, is also a way of following the FAIR principles and is therefore encouraged.
You can read more about which types of data cannot be made available without restrictions at Researchdata.se External link..
There are several ways of finding openly available data sets.
Find data via a persistent identifier
A DOI is a persistent identifier, i.e. a permanent link to the openly available data set (or just its metadata) that can be used to reference the data set, for example in a publication. A DOI can look like this: https://doi.org/10.7937/NC7Z-4F76 External link.. The link can be followed in an ordinary web browser.
Finding data via a search engine
You can also search for research data for which you do not have a DOI in a search engine on the web. Many of these search engines will search several repositories, such as the SND research data catalogue. These include:
Researchdata.se
Researchdata.se External link. searches several Swedish research data repositories.
Sveriges dataportal
Sveriges dataportal External link. searches Swedish research data and openly available data from government agencies.
Data.Europa.Eu
Data.Europa.Eu External link. is the European data portal and searches through available European research data and other available European data from public authorities and others.
Google Dataset Search
Google Dataset Search External link. is a search engine for data sets and searches research data repositories internationally.
Re3data.org
Re3data.org External link. is a catalogue of research data repositories. You can search for repositories, for example by subject, or browse among registered repositories External link..
If you are going to use openly available data
What follows are some things to consider if you use openly available research data in your own work.
As with other published research, good research practice requires that you cite openly available data sets you have used in your work. Usually, the citation should take the same form as a bibliographic citation and include the data sets’ DOI.
A data set may have specific terms of use, specified in a licence. Ensure your use does not violate these terms.
If you request a data set that has been published with restricted access, you will usually specify what you are going to use the data set for, and you may not use it for anything other than what you specified.
You can read more about what you need to do when reusing open available research data at Researchdata.se External link..
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