Data protection impact assessment | IT-Medienrecht

Discover how a Data protection impact assessment (DPIA) protects fundamental rights. Learn about GDPR Article 35 requirements and how to manage risks…

Data Protection Impact Assessment (DPIA): Overview and Requirements

A Data Protection Impact Assessment (DPIA) is a process designed to identify, assess, and manage risks posed to individuals' fundamental rights by an organization's use of a particular technology or system. It is governed by Article 35 of the General Data Protection Regulation (GDPR) and, in most cases, replaces prior checking by the supervisory authority.

Requirements for a Data Protection Impact Assessment

A Data Protection Impact Assessment must be carried out when the nature, scope, circumstances, and purposes of the processing are likely to pose a high risk to the rights and freedoms of natural persons. This is particularly relevant in cases involving:

Furthermore, a Data Protection Impact Assessment is mandatory if the processing operation appears on the positive list issued by the competent supervisory authority, as per Article 35(4) of the GDPR.

Content of a Data Protection Impact Assessment

At a minimum, a Data Protection Impact Assessment must include the following elements:

Understanding "Processing Operation"

The term "processing operation" lacks a specific legal definition within the GDPR. However, German supervisory authorities interpret processing operations as "the sum of data, systems (hardware and software), and processes." This broad interpretation ensures a comprehensive approach to identifying and managing data protection risks.

Fazit

Conducting a Data Protection Impact Assessment is crucial for organizations dealing with high-risk data processing activities. It not only ensures compliance with GDPR Article 35 but also helps to proactively identify and mitigate potential threats to individuals' fundamental rights and freedoms. By meticulously documenting processing activities and their associated risks, organizations can demonstrate accountability and build trust with their data subjects.