Student's guide to responsible and open science: Data management and data protection

Responsible data management is an essential part of writing a thesis and also an important work-life skill. Here are some essential things you need to consider when managing your materials.

Data management refers to the collecting, processing, describing, storing and preserving of the data used in the thesis.

• In the data management plan, these processes are described and written down even before the actual collection of the data.
• It is also updated and completed as work progresses and plans are refined or changed.

The purpose of the data management plan is to:

• Anticipate potential data protection risks and ensure that the data remains safe and usable throughout the project.
• Improve the reliability and reproducibility of the results of the study or exercise
• Promote the further use of the collected research data.

When writing your data management plan, you can use the form template (linkki), which you can also find in the guidelines on this page. Guidance can also be found on the DMPTuuli service for writing data management plans.

Briefly describe your research data: what kind of data do you collect or produce, or what existing data do you use?

•     How much storage space do you need for your data?
•     Make sure that the data you collect is of sufficient quality for your study. For example, first collect a small test sample before collecting the actual data: conduct a pilot interview, test a questionnaire

If you are using previously collected data, familiarise yourself with it carefully and assess whether it can help you answer your research questions.

The collection and processing of data should be described with enough precision that someone other than yourself can understand what the data is about. The data should be described in such detail that, if for some reason you were to stop working on your thesis for a year or two, you would still be reasonably confident that you could continue where you left off.

Describe the collection and processing of data

• What do the data files contain?
• When was the data collected?
• Where was the data collecte?
• Why was the data collected?
• How was the data processed or edited?
• In tabular data, column and row headings, data coding (including information on missing data), units of measurement, etc.
• Open the abbreviations you use.

File naming and folder structure

• Pay attention to the names and order of files and folders.
• Smart file names are short, informative and consistent. For example, the standard way of labelling dates is YYYYMMDD.
• Use version numbering for file names and keep the original file separate from the editing files.
• Even one interview can easily result in three files: the original audio file, the transcribed text file and the interview notes.
• Do not use any identifying information related to the persons in the file names!

Please note:

• Any copyright or terms of use associated with material you receive from elsewhere.
• Not all material available online may be available for use in your own work. Please check the terms of use of the service you are using to see if you are allowed to use the material for research purposes.
• Watch the video on intellectual property and data protection of research data (Youtube, 5:02):

Images, texts, other outputs:

These are also most probably protected by copyright.

• In particular, if you upload images or texts to your own computer, you should ensure that you have the right to do so.
• Sometimes the terms of permission for images and texts are specified in the licenses.
• For example, if you are using social media posts as your material, check the terms of use of the service to ensure that you can download the posts to your computer if necessary.
• See Aalto University's ImagOA guide on the use of images
• Read the advice of the Copyright Lawyer on how students can use images in their thesis.

• If your supervisor gives you access to the material, you should agree who can use it and what will be done with it after the thesis is completed or if it is not completed, to avoid any confusion.
• Similarly, if you are working on your thesis in collaboration with a company, for example. Will the material remain available to the company, can you use it later, or does the material have to be destroyed?

Further use: anticipate the further use or opening of the data even before data collection!

To open the data for further use by others, you need the permission of the respondents. 

• The opening of the data is done in archives, such as the Tampere University's Finnish Social Science Data Archive (FSD). They accept thesis material for archiving on a discretionary basis. The material should be large enough for comparative research, methodological teaching or new research. Read more about the materials accepted by the FSD.
• For example, contact the FSD and ask about the possibilities of opening. The right to use the university's storage solutions expires on completion if you don't want to destroy the material, please recover it.

Personal data, informants' rights:

• Informing subjects about further use is essential.
• The information of the subjects should be kept clear. The data containing personal data is usually destroyed after the thesis is completed and approved.
• Inform the subjects if you intend to use the data after your thesis, for example for postgraduate studies or if you intend to publish your thesis. It may be necessary to keep the material used in the publication for verification purposes.
• You should also take into account the possible interests of the institution or company that commissioned your thesis in the material.

Preservation:

• The EU-funded Zenodo service is suitable for the preservation of many types of material. If necessary, you can limit the visibility of the material so that only you have access to it, but you can also open it via Zenodo.

Equipment used for data processing

• Questionnaire systems O365 Forms and LimeSurvey (intra)
• Interviews - Dictators (intra)
• Zoom and Teams (intra) are compliant with the Data Protection Act and the EU General Data Protection Regulation (GDPR) according to the intranet guidelines when logged in with tuni IDs. The recording is saved on the interviewer's computer.
• Laptops (intra).
• External hard drives: protect external hard drives with at least a password.
• Use university storage solutions (intra) such as OneDrive for Business, Tuni Groups and Personal Network Drive.
• Commercial cloud services for consumer use are not always suitable for handling confidential data, such as personal data.

Research always includes: legal, rights and ethical issues.

Show that you are aware of the laws and regulations that apply to research and data handling!

Remember:

• Assess whether you are processing personal data. The General Data Protection Regulation (GDPR) defines personal data as any information relating to an identified or identifiable natural person.
• Data protection is the protection of personal data. The processing of personal data must always be based on law.
• Sensitivity of data, sensitivity of data, e.g. children
• Other confidential data, commercial data, business data, trade secrets, military data, sensitive species data?
• Research authorization or prior ethical review?
• Assess the risks associated with the processing of personal data and how you manage them.

See also Data protection and personal data

Links on the use of social media for research  

• Do you use social data in your research? Marko Ahteensuu discusses the legal and ethical issues surrounding the use of social media data.
• Published on the Social Science Space platform on the collection of social media data for research use.
• Who gets to decide what data a researcher has access to? Certainly not a large American corporation. A reflection on the use of social media data in research, published on the Rajapinta website.
• Skilfully ethical online research. Article by Salla-Maaria Laaksonen on the website Vastuullinentiede.fi.

Using Facebook data on The Conversation channel.

• Facebook's data lockdown is a disaster for academic researchers
• Facebook data harvesting: what you need to know
• Facebook data: why ethical reviews matter in academic research