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dcc:pdpsol:pseudonymization [2026/02/19 15:12] – add figure marlondcc:pdpsol:pseudonymization [2026/02/24 12:38] (current) – [Introduction] marlon
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 ====== Pseudonymization ====== ====== Pseudonymization ======
 ===== Introduction ===== ===== Introduction =====
-//“Pseudonymization is a de-identification procedure during which personally identifiable information is replaced by a unique alias or code (pseudonym). In some situations, the researcher maintains the link between the unique code and the data subject in a keyfile, while in other projects this connection is not necessary.”// +Pseudonymization is a de-identification procedure during which personally identifiable information is replaced by a unique alias or code (pseudonym). In some situations, the researcher maintains the link between the unique code and the data subject in a keyfile, while in other projects this connection is not necessary. 
  
 The manner in which pseudonymization is done varies between projects based on the research setup. It is good practice to describe the process of pseudonymization specific to your research either in your data management plan or a separate Pseudonymization Protocol. You can use the examples below to guide you in this process. The manner in which pseudonymization is done varies between projects based on the research setup. It is good practice to describe the process of pseudonymization specific to your research either in your data management plan or a separate Pseudonymization Protocol. You can use the examples below to guide you in this process.
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 ==== Creating a keyfile ==== ==== Creating a keyfile ====
-First, create a pseudonymization keyfile (e.g., in Excel or another UG approved tool available in the University Workplace) that assigns each data subject a unique pseudonymization ID. For the creation of the pseudonymization IDs, you can follow the same steps as described in //Pseudonymization without a keyfile//. Direct identifiers such as names, email addresses, or phone numbers should be stored only in this keyfile and removed from the research dataset. In the research dataset, remove all direct identifiers or replace them with the pseudonymization IDs.  +First, create a pseudonymization keyfile (e.g., in Excel or another UG approved tool available in the University Workplace) that assigns each data subject a unique pseudonymization ID. For the creation of the pseudonymization IDs, you can follow the same steps as described in //Pseudonymization without a keyfile//. Direct identifiers such as names, email addresses, or phone numbers should be stored only in this keyfile (Figure 2) and removed from the research dataset. In the research dataset, remove all direct identifiers or replace them with the pseudonymization IDs.  
  
-Figure 2: Pseudonymization key+**Figure 2: Pseudonymization with keyfile**
 ---- ----
-{{:dcc:pdpsol:pseudonymization:pseudk.png?direct&400|}}+{{:dcc:pdpsol:pseudonymization:pseudk.png?direct&400 |}}{{:dcc:pdpsol:pseudonymization:pseudnk.png?direct&400|}} 
 ==== Managing the keyfile ==== ==== Managing the keyfile ====
 You must store the keyfile securely in your [[https://www.rug.nl/digital-competence-centre/it-solutions/store-and-archive/university-workplace-storage|X-Drive or Y-Drive]], separate from the research data. Strictly limit access to the keyfile, for example, by using password-protected, encrypted, or stored on a secure server. This ensures that, even if the research dataset is shared or accessed by unauthorized parties, re-identification is only possible if the keyfile is also compromised. Keep track of who is authorized to access the keyfile, and if necessary (e.g. longitudinal research), ensure that there are two people who have access to the key in case one becomes unavailable.  You must store the keyfile securely in your [[https://www.rug.nl/digital-competence-centre/it-solutions/store-and-archive/university-workplace-storage|X-Drive or Y-Drive]], separate from the research data. Strictly limit access to the keyfile, for example, by using password-protected, encrypted, or stored on a secure server. This ensures that, even if the research dataset is shared or accessed by unauthorized parties, re-identification is only possible if the keyfile is also compromised. Keep track of who is authorized to access the keyfile, and if necessary (e.g. longitudinal research), ensure that there are two people who have access to the key in case one becomes unavailable. 
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 This approach reduces the risk of re-identification and protects sensitive information throughout the data transfer process. For guidance on implementing this protocol, contact your [[https://www.rug.nl/digital-competence-centre/contact/|faculty data steward or the DCC]]. This approach reduces the risk of re-identification and protects sensitive information throughout the data transfer process. For guidance on implementing this protocol, contact your [[https://www.rug.nl/digital-competence-centre/contact/|faculty data steward or the DCC]].
 +
 +**Figure 3: Pseudonymization with double coding**
 +
 +----
 +{{:dcc:pdpsol:pseudonymization:pseudnk.png?direct&350|}}{{:dcc:pdpsol:pseudonymization:pseuddc.png?direct&350 |}}{{:dcc:pdpsol:pseudonymization:pseuddc2.png?direct&350 |}}
  
 [[dcc:pdpsol:start | → Go back to the Privacy & Data protection home page]] [[dcc:pdpsol:start | → Go back to the Privacy & Data protection home page]]