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dcc:pdpsol:datadesctruction [2026/04/10 09:53] – albadcc:pdpsol:datadesctruction [2026/06/15 11:14] (current) – alba
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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 to 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 to help you prepare for the timely destruction of data.
  
 ==== Secure and destroy personal identifiable notes ==== ==== Secure and destroy personal identifiable notes ====
-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.+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. Please do not shred paper by hand into a few pieces, and do not throw paper containing confidential data in an open paper bin. 
 + 
 +**Figure 1: Confidential paper container** 
 +---- 
 +{{:dcc:pdpsol:data_destruction:confidential_bin.png?direct&800|}}
  
 ====Securely remove your data from devices and platforms ==== ====Securely remove your data from devices and platforms ====
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 After you have confirmed that your data is archived correctly, you can critically review the data you have stored during your research:  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.)   * 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.  +  * Delete the data from your working directory after archiving if you are no longer planning to use the data for future projects. 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.).+  * If you are still working with the data, clean your working directory by: 1) Deleting any temporary working files (e.g. data that can easily be regenerated by archived scripts). 2) Removing duplicate or obsolete versions (e.g. final_v1.csv, final_v2.csv, etc.).
  
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 [[dcc:pdpsol:start | → Go back to the Privacy & Data protection home page]] [[dcc:pdpsol:start | → Go back to the Privacy & Data protection home page]]