4.2 Balancing priorities; responsible data management
Now that you have taken a closer look at the context in which your data processing takes place, read through the following slides, take a small quiz and then continue to the next exercise.
Slide 1: Responsible Data Management
Responsible data management is the duty to account for unintended consequences of working with data by:
- prioritising people’s rights to consent, privacy, security and ownership when using data,
- implementing values and practices of transparency and openness.
When looking at this definition it becomes clear that there is an inherent tension between a government and a cities obligation to protect the privacy and data of their citizens, with the need to open data as a source of increased accountability as well as the development of innovative solutions. The organizational culture, context and legal environment become crucial in trying to find the right balance.
Slide 2: Transparency, open data vs data protection
The tension between transparency vs data protection lies amongst others in:
- Data processing and publishing data can pose risks to individuals, groups, your institution and society at large.
- There have been incidences where privacy and data protection have been used as an argument against opening up data that has great public value.
- The emphasis on data protection or privacy is historically defined. Countries have different approaches, while in European legislation the right to data protection is historically more enshrined, in the US and LATAM the right to information has been more reflected in law. Nevertheless, boths rights theoretically are perceived as equally relevant and non-hierarchical.
Slide 3: Transparency as a tool to fight misuse
Transparency can also be complementary to data protection, as it can prevent misuse of the privacy and data protection argument to keep certain governmental or city data closed.
Privacy and data protection can be a valid reason for cities and municipalities to decide not to open specific data. However, it requires transparency about the decisions to keep data out of the public domain, and clear arguments why the data is not opened up.
Slide 4: Open data vs Privacy in City of Seattle
In 2016, in the light of developing their new Open Data Strategy the City of Seattle rigorously evaluated their current open data practices with the support of researchers from Washington. The goal was to understand how to stimulate the opening up of more and more relevant data sets. However, the researchers revealed an additional problem to them : Several of the data sets released presented a potential privacy risk, and researchers were able to link back information about individuals crossing the data sets with other data openly available (i.e. social media data). As a result, the city decided to change their policy based on these findings. Instead of following an “open by default” they are now following an “open by preference policy”. That means, before opening up any data set they are divided into risks group and depending of the data subject to a more rigorous risk assessment. They also hired the American organisation “Future of Privacy Forum” who then conducted a more extensive privacy audit and who developed an open-data-risk-assessment tool for the city employees. The objective continues to be the same as in 2016: To open up as much data as possible in order to promote transparency, accountability, and innovation. However, now this happens in a more systematic and controlled manner.
Here you can find the document “Open Data Risk Assessment” developed by the Future of Privacy Forum
Slide 5: Data management assessment tools
- Risk assessment: is a classification of the different risks as a possible result of data processing, their impact and likelihood versus the effort you are willing to take protect yourself against these risks.
- Privacy Impact assessment: is a process which assists teams, departments and organisations who are implementing a project that processes data to identify and minimise privacy risks.
Slide 6: Implementing data protection instruments
There is a range of areas in which measures can be taken to increase the protection of the data and privacy of individuals. From hardening the infrastructure, to creating data integrity policy to making it a priority of management. This course is designed for urban practitioners, therefore the next 4 sessions will cover a number of more human centric data protection instruments:
- De-identifying data
- Consent and proactive communication
- Access controls and data management
Slide 7: Other data protection instruments
There are two important data protection elements that will not be covered in this course but are good to take into account.
Ensuring proper implementation through a security audit: like any system or project it is important to evaluate data processing at set times. Not only to evaluate if the privacy risks have changed, or if the project is still aligned with the cities or municipalities values and objectives. A security audit test the systems for possible vulnerabilities and error rates. This audit can be done internally or by external experts.
An audit trail: are logs of how the data processing works, who accesses the data for which actions. It is important to implement an audit trail from the start so that if something goes wrong, you can ‘follow the breadcrumbs’ to try and figure out where and why something went wrong.