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Table 1 Summary of first validation by aspect

From: Making context the central concept in privacy engineering

Aspects raised in the interviews

Initial position

Implications of first validation

Understanding of context

Dynamic entity defined by knowledge focus, not a container described by a set of characteristics (e.g. individual privacy preference statements)

Dynamic definition fruitful basis for the design

Need to extend CI theory

Context part of the theory underdeveloped

Development gap recognised

Knowledge aspects of context

Focus should be on the three types of knowledge (external, contextual and procedural)

Different aspects are understood applied to privacy use cases

Context triggers

Event-driven approach to handling privacy in context

Concept useful starting point for privacy engineering

Data sharing policy

Concept encapsulating preference handling on behalf of the user

Considered useful as an overall idea; however, many questions about structure and management not dealt with in the first development cycle

Contextual graph formalism

Graph presented as an abstract example (template)

Should be introduced in a pedagogical example related to privacy (see updated Fig. 7); the graph should be explained in relation to other graph types if it should be used in applications

Provisional definition of data privacy

Guiding definition for use in design was provided

The definition was improved (see the Understanding data privacy’ section) for clarity and scope

Organisational design

Focus on role of data sharing policies

Questions to the envisioned business process motivated extending the Organisational design—defining data sharing policies’ section, explaining more in depth the role of ML and the personal data sharing policies’ relationship to institutional privacy policies

Technical design

An application scenario was presented

The role of high-level technical architecture and scenarios is highlighted; design at this level could potentially drive future design cycles

Use of smart contracts

These artefacts are part of cutting edge technologies, and in our proposal given, the role of executing data sharing decisions

According to interviews blockchain and smart contracts should be explored

Use of ML

ML is positioned as a key instrument in delegating the execution of policies to the IT system, allowing users to focus on their main activities

Interviews showed support for making ML an important part of the design