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dcc:pdpsol:datadesctruction [2026/02/09 12:13] – added menu order giuliodcc:pdpsol:datadesctruction [2026/02/24 09:24] (current) – [Final clean-up (after archiving)] marlon
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 ====== Data Destruction ====== ====== Data Destruction ======
 ===== Introduction ===== ===== Introduction =====
 Although it is possible to prevent the collection of data, it is also important to think about the data that you might need for your research at first, but that become redundant later on. By planning for timely de-identification and destruction of your data, you can better protect your participants. You can use the examples below can help you prepare for the timely destruction of data. Although it is possible to prevent the collection of data, it is also important to think about the data that you might need for your research at first, but that become redundant later on. By planning for timely de-identification and destruction of your data, you can better protect your participants. You can use the examples below can help you prepare for the timely destruction of data.
  
-===== Informed Consent forms ===== +==== Secure and destroy personal identifiable notes ==== 
-Consent forms can reveal personal information. It is therefore important to handle consent registration with care. Minimize the amount of personal data on your consent form. Follow the practical guidelines on the DCC website about informed consent to guide you in the process.+During your research, you may unexpectedly need to record personal information about a participant. For example, a participant may report a change in their contact details or provide additional personal comments. Whenever possible, record this information directly in a digital format on the secure storage solution you use for your research documentation. If this is not possible, temporarily record the information on paper and digitize it as soon as possible. Do not retain personal information longer than necessary, especially on paper. Once the information has been digitized, immediately destroy the original paper notes using UG confidential paper containers or a shredder.
  
-==== Online consent ==== +====Securely remove your data from devices and platforms ==== 
-If you are conducting questionnaire research via an online platform (e.g., Qualtrics), you can ask consent via a question in the platform itself. Make sure to follow the faculty and university guidelines with regard to the design of your consent form. Participants’ progression to the next page can be considered as consent. +While collecting data, it is often necessary to use storage solutions that are no longer necessary after you have collected the data and are going to analyse the data. Transfer your data from these devices and platforms to a secure storage location as soon as possible. First make sure that you check the integrity of the data. As soon as this is confirmed, remove the data from the device or platform.
- +
-When asking for consent, ensure you collect only the personal data that is necessary: +
-  * If your objective is to collect anonymous or de-identified data, do not ask for names or other contact details for consent registration purposes. +
-  * If your objective is to collect identifiable or sensitive personal data, use a pseudonymization ID to prevent direct identification. At the relevant time in the project, remove the link between the consent and the participant’s identity reported in your keyfile. For example, when you've started to analyze the data and the participants can no longer request their data to be removed (right to withdraw consent), as stated in the consent form, or after you connected these data to other data (e.g. interview data). +
- +
-==== Paper consent ==== +
-If you are conducting interviews or experiments, it is common practice to ask for consent on paper. Make sure to follow the faculty and university guidelines with regard to the design of your consent form.  +
- +
-When asking for consent, ensure you collect only the personal data that is necessary:  +
-  * If your objective is to collect anonymous data, do not ask for names, and signatures and do not use pseudonymization IDs in consent forms. +
-  * If your objective is to collect (pseudonymized) personal data, do not ask for names, signatures on the consent form. Instead, use a pseudonymization ID in consent forms to prevent direct identification. Ensure this pseudonymization ID corresponds with name and/or contact details in a keyfile. At the relevant time in the project, remove the link between the consent form and the research data and the participant’s identity reported on the keyfile. For example, when you've started to analyze the data and the participants can no longer request their data to be removed (right to withdraw consent), as stated in the consent form. After the link between the pseudonymization ID and the identity of the participant have been removed, the consent forms can be considered anonymous.  +
- +
-After you finish your research:  +
-  - scan paper consent forms +
-  - archive anonymous digitized consent forms with your research data +
-  - destroy the original paper forms (use UG paper containers for confidential materials or a shredder).  +
- +
-==== Audio consent ==== +
-If you are conducting interviews, it is sometimes necessary to ask consent during the interview itself. Make sure to follow the faculty and university guidelines with regard to the design of your consent procedure.  +
- +
-  * Be aware that audio or video recordings of informed consent cannot be fully anonymized without altering their content;  +
-  * Make sure the verbal consent recorded via audio or video is saved separately from your research data (e.g., experiment, interview, observation etc.);  +
-  * Archive the consent files in a separate location (separate folder with different access rights) from your research data;  +
-  * use an extra layer of protection, such as [[https://www.rug.nl/digital-competence-centre/it-solutions/privacy-and-security/data-encryption|encryption]].+
  
 +====Final clean-up (after archiving) ====
 +Before you do your final clean-up, it is important to check whether all necessary data are included in your data package, publication package or archive according to your [[https://www.rug.nl/digital-competence-centre/research-data/policies|faculty research data policy]].
  
 +After you have confirmed that your data is archived correctly, you can critically review the data you have stored during your research: 
 +  * Check whether you have removed all copies of your data from secondary locations (e.g. the data collection platform, laptop, SurfDrive, Unishare, etc.)
 +  * If you are no longer planning to use the data for future projects, consider also deleting it from your main working directory after archiving. Make sure to follow the agreements made with participants. 
 +  * If you are still working with the data, consider tidying your working directory: 1) Delete any temporary working files (e.g. data that can easily be regenerated by archived scripts). 2) Remove duplicate or obsolete versions (e.g. final_v1.csv, final_v2.csv, etc.).
  
 [[dcc:pdpsol:start | → Go back to the Privacy & Data protection home page]] [[dcc:pdpsol:start | → Go back to the Privacy & Data protection home page]]