# DPIA in Context: Applying DPIA to Assess Privacy Risks of Cyber Physical Systems
## 8 Conclusions  
In this paper, we presented the DPIA Data Wheel: an empirically evaluated DPIA framework. The DPIA Data Wheel exemplifies how PbD can be achieved through designing CI into the DPIA process. The framework was devised to provide a useful tool that decision makers can use to ensure contextual considerations are included as part of their privacy risk assessment process. The DPIA Data Wheel framework was designed with charities in mind. However, it can equally be applied and used in any organisation who are required to conduct privacy risk assessments and/or DPIAs. This DPIA Data Wheel provides an exemplar, GDPR compliant DPIA process that incorporated two prototype spreadsheets (a Data Register and the life of the form, devised to capture details of the data flow within the organisation) from the GDPR implementation case study (see [5]). These prototypes have been included in the DPIA Data Wheel to facilitate organisations being able to collate appropriate evidence for demonstrating compliance with GDPR. For context, the DPIA framework questions integrated most of the questions from CLIFOD, including all the contextual questions, into the framework. Finally, the DPIA framework also incorporated a privacy risk assessment, and recording of suitable mitigation strategies to address any privacy risks identified, designed to aid practitioners in determining what privacy risks might be associated with data processing associated with the implementation of a new system, project or process or other data processing activity associated with CPS (see Section 3). The DPIA framework presented in this paper provides decision makers with an exemplar for conducting a combined DPIA and PIA assessment in practice based on CI. Moreover, this DPIA framework not only helps decision makers conduct consistent and repeatable privacy risk assessments, it also guides them towards making informed decisions about privacy risks and provide them with demonstrable evidence of GDPR compliant processes and practices. This, we contend, is particularly useful in scenarios where boundaries between different processes or systems are blurred, such as CPS. Some of the outcomes from the evaluations in Section 5 should not be entirely surprising. Historically, risk assessment is invariably concerned with what the consequences and likelihood of the risk occurring would be for the business and how this might negatively affect the organisation, rather than how they might affect the individual. Thus, decisions makers might be pre-conditioned into thinking about risks in terms of organisational risks. Therefore, asking them to now look at risk from the perspective of the individual without first providing more direction and guidance is unlikely to result in the desired DPIA assessments Data Protection Regulation Authorities might hope for. Our work demonstrates that the wider the consultation on the DPIA risks identified, the more in-depth and complete the resulting privacy risk register is likely to be. Moreover, in terms of context, what our evaluation illustrates is that, the more stakeholders are consulted, the more context is likely to be included in the assessment. This shows the importance of allowing each stakeholder group to add their different perspectives, thereby broadening the context being considered. Stakeholder consultation is also an opportunity for reciprocal learning, making participants more likely to implement and use the lessons learnt which, in turn, reduces the likelihood of the risks identified occurring. While the breadth of the evaluation, and therefore the consultation, was inclusive and comprehensive, more emphasis needs to be placed on the procedure for conducting the DPIA and how to contextualise and relate the risks to the individual rather than the organisation to ensure wide stakeholder engagement. To address this, consideration needs to be given to whether and how the questions can be adapted to encourage a change in perspective, or illustrative examples can be incorporated into the framework questions.