SCENARIO -
Please use the following to answer the next question:
Anna and Frank both work at Granchester University. Anna is a lawyer responsible for data protection, while Frank is a lecturer in the engineering department. The University maintains a number of types of records:
Student records, including names, student numbers, home addresses, pre-university information, university attendance and performance records, details of special educational needs and financial information.
Staff records, including autobiographical materials (such as curricula, professional contact files, student evaluations and other relevant teaching files).
Alumni records, including birthplaces, years of birth, dates of matriculation and conferrals of degrees. These records are available to former students after registering through Granchester’s Alumni portal.
Department for Education records, showing how certain demographic groups (such as first-generation students) could be expected, on average, to progress. These records do not contain names or identification numbers.
Under their security policy, the University encrypts all of its personal data records in transit and at rest.
In order to improve his teaching, Frank wants to investigate how his engineering students perform in relational to Department for Education expectations. He has attended one of Anna’s data protection training courses and knows that he should use no more personal data than necessary to accomplish his goal. He creates a program that will only export some student data: previous schools attended, grades originally obtained, grades currently obtained and first time university attended. He wants to keep the records at the individual student level. Mindful of Anna’s training, Frank runs the student numbers through an algorithm to transform them into different reference numbers. He uses the same algorithm on each occasion so that he can update each record over time.
One of Anna’s tasks is to complete the record of processing activities, as required by the GDPR. After receiving her email reminder, as required by the GDPR. After receiving her email reminder, Frank informs Anna about his performance database.
Ann explains to Frank that, as well as minimizing personal data, the University has to check that this new use of existing data is permissible. She also suspects that, under the GDPR, a risk analysis may have to be carried out before the data processing can take place. Anna arranges to discuss this further with Frank after she has done some additional research.
Frank wants to be able to work on his analysis in his spare time, so he transfers it to his home laptop (which is not encrypted). Unfortunately, when Frank takes the laptop into the University he loses it on the train. Frank has to see Anna that day to discuss compatible processing. He knows that he needs to report security incidents, so he decides to tell Anna about his lost laptop at the same time.
Before Anna determines whether Frank’s performance database is permissible, what additional information does she need?
Explanation:
The AI agrees with the suggested answer of D. More information about what students have been told and how the research will be used.
Reasoning:
Anna needs to determine if Frank's processing is permissible under GDPR. To do this, she needs to ensure the processing aligns with the principles of transparency, purpose limitation, and lawfulness.
1. Transparency and Purpose Limitation: Under GDPR, individuals have the right to be informed about how their data is used (transparency), and data should only be processed for specified, explicit, and legitimate purposes (purpose limitation) (Article 5(1)(b) and Article 13 GDPR). Anna needs to know what the students have been told about the use of their data for research purposes. If the research use is not compatible with the original purpose for which the data was collected (e.g., academic administration), then additional consent or a different legal basis might be required.
2. Lawfulness: Knowing how the research will be used is essential to determine the appropriate legal basis for processing. The University needs a legal basis, such as consent, legitimate interest, or public interest, to process the student data for research (Article 6 GDPR). Without knowing the specifics of the research and its intended use, Anna cannot assess whether a valid legal basis exists.
Reasons for not choosing other answers:
- A. More information about Frank’s data protection training: While it is relevant that Frank has attended data protection training, this is not the most immediate piece of information Anna requires to determine the permissibility of the processing. His level of training does not directly impact whether the processing is lawful, fair, and transparent.
- B. More information about the extent of the information loss: The data loss from the laptop is a separate issue that needs to be addressed as a data breach. While important, it does not directly inform Anna's assessment of the permissibility of Frank's performance database under GDPR.
- C. More information about the algorithm Frank used to mask student numbers: The algorithm is a pseudonymization technique. Even if the student numbers are transformed, the data is still considered personal data under the GDPR because the students are still identifiable. Pseudonymization can be a security measure, but it does not remove the need for a legal basis and transparency about the processing (Recital 26 GDPR). The nature of the algorithm is less important than ensuring that students have been informed and that the processing purpose is legitimate.
- GDPR Article 5(1)(b): Purpose Limitation, https://gdpr-info.eu/art-5-gdpr/
- GDPR Article 6: Lawfulness of processing, https://gdpr-info.eu/art-6-gdpr/
- GDPR Article 13: Information to be provided where personal data are collected from the data subject, https://gdpr-info.eu/art-13-gdpr/
- GDPR Recital 26: Encourages pseudonymisation as a security measure, https://gdpr-info.eu/recitals/no-26/