Άρθρο 5 GDPR. Αρχές που διέπουν την επεξεργασία δεδομένων προσωπικού χαρακτήρα
Article 5 GDPR. Principles relating to processing of personal data
Αρχές που διέπουν την επεξεργασία δεδομένων προσωπικού χαρακτήρα
Principles relating to processing of personal data
1. Τα δεδομένα προσωπικού χαρακτήρα:
1. Personal data shall be:
α) υποβάλλονται σε σύννομη και θεμιτή επεξεργασία με διαφανή τρόπο σε σχέση με το υποκείμενο των δεδομένων («νομιμότητα, αντικειμενικότητα και διαφάνεια»),
(a) processed lawfully, fairly and in a transparent manner in relation to the data subject (‘lawfulness, fairness and transparency’);
β) συλλέγονται για καθορισμένους, ρητούς και νόμιμους σκοπούς και δεν υποβάλλονται σε περαιτέρω επεξεργασία κατά τρόπο ασύμβατο προς τους σκοπούς αυτούς· η περαιτέρω επεξεργασία για σκοπούς αρχειοθέτησης προς το δημόσιο συμφέρον ή σκοπούς επιστημονικής ή ιστορικής έρευνας ή στατιστικούς σκοπούς δεν θεωρείται ασύμβατη με τους αρχικούς σκοπούς σύμφωνα με το άρθρο 89 παράγραφος 1 («περιορισμός του σκοπού»),
(b) collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes; further processing for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes shall, in accordance with Article 89(1), not be considered to be incompatible with the initial purposes (‘purpose limitation’);
γ) είναι κατάλληλα, συναφή και περιορίζονται στο αναγκαίο για τους σκοπούς για τους οποίους υποβάλλονται σε επεξεργασία («ελαχιστοποίηση των δεδομένων»),
(c) adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed (‘data minimisation’);
δ) είναι ακριβή και, όταν είναι αναγκαίο, επικαιροποιούνται· πρέπει να λαμβάνονται όλα τα εύλογα μέτρα για την άμεση διαγραφή ή διόρθωση δεδομένων προσωπικού χαρακτήρα τα οποία είναι ανακριβή, σε σχέση με τους σκοπούς της επεξεργασίας («ακρίβεια»),
(d) accurate and, where necessary, kept up to date; every reasonable step must be taken to ensure that personal data that are inaccurate, having regard to the purposes for which they are processed, are erased or rectified without delay (‘accuracy’);
ε) διατηρούνται υπό μορφή που επιτρέπει την ταυτοποίηση των υποκειμένων των δεδομένων μόνο για το διάστημα που απαιτείται για τους σκοπούς της επεξεργασίας των δεδομένων προσωπικού χαρακτήρα· τα δεδομένα προσωπικού χαρακτήρα μπορούν να αποθηκεύονται για μεγαλύτερα διαστήματα, εφόσον τα δεδομένα προσωπικού χαρακτήρα θα υποβάλλονται σε επεξεργασία μόνο για σκοπούς αρχειοθέτησης προς το δημόσιο συμφέρον, για σκοπούς επιστημονικής ή ιστορικής έρευνας ή για στατιστικούς σκοπούς, σύμφωνα με το άρθρο 89 παράγραφος 1 και εφόσον εφαρμόζονται τα κατάλληλα τεχνικά και οργανωτικά μέτρα που απαιτεί ο παρών κανονισμός για τη διασφάλιση των δικαιωμάτων και ελευθεριών του υποκειμένου των δεδομένων («περιορισμός της περιόδου αποθήκευσης»),
(e) kept in a form which permits identification of data subjects for no longer than is necessary for the purposes for which the personal data are processed; personal data may be stored for longer periods insofar as the personal data will be processed solely for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) subject to implementation of the appropriate technical and organisational measures required by this Regulation in order to safeguard the rights and freedoms of the data subject (‘storage limitation’);
στ) υποβάλλονται σε επεξεργασία κατά τρόπο που εγγυάται την ενδεδειγμένη ασφάλεια των δεδομένων προσωπικού χαρακτήρα, μεταξύ άλλων την προστασία τους από μη εξουσιοδοτημένη ή παράνομη επεξεργασία και τυχαία απώλεια, καταστροφή ή φθορά, με τη χρησιμοποίηση κατάλληλων τεχνικών ή οργανωτικών μέτρων («ακεραιότητα και εμπιστευτικότητα»).
(f) processed in a manner that ensures appropriate security of the personal data, including protection against unauthorised or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organisational measures (‘integrity and confidentiality’).
2. Ο υπεύθυνος επεξεργασίας φέρει την ευθύνη και είναι σε θέση να αποδείξει τη συμμόρφωση με την παράγραφο 1 («λογοδοσία»).
2. The controller shall be responsible for, and be able to demonstrate compliance with, paragraph 1 (‘accountability’).
8. Technical and organizational measures and necessary safeguards can be understood in a broad sense as any method or means that a controller may employ in the processing. Being appropriate means that the measures and necessary safeguards should be suited to achieve the intended purpose, i.e. they must implement the data protection principles effectively. The requirement to appropriateness is thus closely related to the requirement of effectiveness.
 “Effectiveness” is addressed below in subchapter 2.1.2
9. A technical or organisational measure and safeguard can be anything from the use of advanced technical solutions to the basic training of personnel. Examples that may be suitable, depending on the context and risks associated with the processing in question, includes pseudonymization of personal data ; storing personal data available in a structured, commonly machine readable format; enabling data subjects to intervene in the processing; providing information about the storage of personal data; having malware detection systems; training employees about basic “cyber hygiene”; establishing privacy and information security management systems, obligating processors contractually to implement specific data minimisation practices, etc.
 Defined in Article 4(5) GDPR
13. Effectiveness is at the heart of the concept of data protection by design. The requirement to implement the principles in an effective manner means that controllers must implement the necessary measures and safeguards to protect these principles, in order to secure the rights of data subjects. Each implemented measure should produce the intended results for the processing foreseen by the controller. This observation has two consequences.
14. First, it means that Article 25 does not require the implementation of any specific technical and organizational measures, rather that the chosen measures and safeguards should be specific to the implementation of data protection principles into the particular processing in question. In doing so, the measures and safeguards should be designed to be robust and the controller should be able to implement further measures in order to scale to any increase in risk. Whether or not measures are effective will therefore depend on the context of the processing in question and an assessment of certain elements that should be taken into account when determining the means of processing. The aforementioned elements will be addressed below in subchapter 2.1.3.
 “Fundamental principles applicable to the controllers (i.e. legitimacy, data minimisation, purpose limitation, transparency, data integrity, data accuracy) should remain the same, whatever the processing and the risks for the data subjects. However, due regard to the nature and scope of such processing have always been an integral part of the application of those principles, so that they are inherently scalable.” Article 29 Working Party. “Statement on the role of a risk-based approach in data protection legal frameworks”. WP 218, 30 May 2014, p. 3. ec.europa.eu/justice/article-29/documentation/opinion-recommendation/files/2014/wp218_en.pdf
15. Second, controllers should be able to demonstrate that the principles have been maintained.
16. The implemented measures and safeguards should achieve the desired effect in terms of data protection, and the controller should have documentation of the implemented technical and organizational measures. To do so, the controller may determine appropriate key performance indicators (KPI) to demonstrate the effectiveness. A KPI is a measurable value chosen by the controller that demonstrates how effectively the controller achieves their data protection objective. KPIs may be quantitative, such as the percentage of false positives or false negatives, reduction of complaints, reduction of response time when data subjects exercise their rights; or qualitative, such as evaluations of performance, use of grading scales, or expert assessments. Alternatively to KPIs, controllers may be able to demonstrate the effective implementation of the principles by providing the rationale behind their assessment of the effectiveness of the chosen measures and safeguards.
 See Recitals 74 and 78.
220.127.116.11 “state of the art”
18. The concept of “state of the art” is present in various EU acquis, e.g. environmental protection and product safety. In the GDPR, reference to the “state of the art”  is made not only in Article 32, for security measures, but also in Article 25, thus extending this benchmark to all technical and organisational measures embedded in the processing.
 See German Federal Constitutional Court’s “Kalkar” decision in 1978: https://germanlawarchive.iuscomp.org/?p=67 may provide the foundation for a methodology for an objective definition of the concept. On that basis, the “state of the art” technology level would be identified between the “existing scientific knowledge and research” technology level and the more established “generally accepted rules of technology”. The “state of the art” can hence be identified as the technology level of a service or technology or product that exists in the market and is most effective in achieving the objectives identified.
19. In the context of Article 25, the reference to “state of the art” imposes an obligation on controllers, when determining the appropriate technical and organisational measures, to take account of the current progress in technology that is available in the market. The requirement is for controllers to have knowledge of, and stay up to date on technological advances; how technology can present data protection risks or opportunities to the processing operation; and how to implement and update the measures and safeguards that secure effective implementation of the principles and rights of data subjects taking into account the evolving technological landscape.
20. The “state of the art” is a dynamic concept that cannot be statically defined at a fixed point in time, but should be assessed continuously in the context of technological progress. In the face of technological advancements, a controller could find that a measure that once provided an adequate level of protection no longer does. Neglecting to keep up to date with technological changes could therefore result in a lack of compliance with Article 25.
21. The “state of the art” criterion does not only apply to technological measures, but also to organisational ones. Lack of appropriate organisational measures can lower or even completely undermine the effectiveness of a chosen technology. Examples of organisational measures can be adoption of internal policies; up-to date training on technology, security and data protection; and IT security governance and management policies.
22. Existing and recognized frameworks, standards, certifications, codes of conduct, etc. in different fields may play a role in indicating the current “state of the art” within the given field of use. Where such standards exist and provide a high level of protection for the data subject in compliance with – or go beyond – legal requirements, controllers should take them into account in the design and implementation of data protection measures.
18.104.22.168 “cost of implementation”
23. The controller may take the cost of implementation into account when choosing and applying appropriate technical and organisational measures and necessary safeguards that effectively implement the principles in order to protect the rights of data subjects. The cost refers to resources in general, including time and human resources.
22.214.171.124 “nature, scope, context and purpose of processing”
28. In short, the concept of nature can be understood as the inherent characteristics of the processing. The scope refers to the size and range of the processing. The context relates to the circumstances of the processing, which may influence the expectations of the data subject, while the purpose pertains to the aims of the processing.
 Examples are special categories personal data, automatic decision-making, skewed power relations, unpredictable processing, difficulties for the data subject to exercise the rights, etc.
126.96.36.199 “risks of varying likelihood and severity for rights and freedoms of natural persons posed by the processing”
32. The risk based approach does not exclude the use of baselines, best practices and standards. These might provide a useful toolbox for controllers to tackle similar risks in similar situations (nature, scope, context and purpose of processing). Nevertheless, the obligation in Article 25 (as well as Articles 24, 32 and 35(7)(c)) to take into account “risks of varying likelihood and severity for rights and freedoms of natural persons posed by the processing” remains. Therefore, controllers, although supported by such tools, must always carry out a data protection risk assessment on a case by case basis for the processing activity at hand and verify the effectiveness of the appropriate measures and safeguards proposed. A DPIA, or an update to an existing DPIA, may then additionally be required.
188.8.131.52 At the time of the determination of the means for processing
34. The “means for processing” range from the general to the detailed design elements of the processing, including the architecture, procedures, protocols, layout and appearance.
35. The “time of determination of the means for processing” refers to the period of time when the controller is deciding how the processing will be conducted and the manner in which the processing will occur and the mechanisms which will be used to conduct such processing. It’s in the process of making such decisions that the controller must assess the appropriate measures and safeguards to effectively implement the principles and rights of data subjects into the processing, and take into account elements such as the state of the art, cost of implementation, nature, scope, context and purpose, and risks. This includes the time of procuring and implementing data processing software, hardware, and services.