How Open Data can work in the social sector
In the course of the digitalisation of social institutions, a tension is emerging between two issues that are gaining increasing attention: the publication of data and individual data protection. Making data accessible brings various benefits, but also risks. These trade-offs will be discussed at the two-day Hack4SocialGood which aims to support social organisations with concerns about digitalisation.
Open and freely usable government data has the potential to improve services, foster innovation, transform institutions and improve society overall by providing access to data for researchers, data journalists and public stakeholders. As part of the federal administration’s “Open Government Data” strategy, more and more data from the cantons, municipalities, cities and federal enterprises is being made publicly available. Open data is also important in basic research. For example, the Swiss National Science Foundation promotes the principle of making research data open and accessible to science and society, provided that the provision of open data does not violate any legal or ethical principles.
Although the benefits of open data seem obvious, in practice it is the case that health and social care organisations in particular rarely make their data openly available. This has to do, first of all, with the fact that data in these sectors is particularly sensitive and worthy of protection. Other risks also affect other public services: If control over data is relinquished, misleading or false analyses can be produced from it. In the worst case, incorrectly prepared open data can lead to the identification of individuals.
Ways to protect the individual
However, the reluctance to use open data is also related to a lack of knowledge about existing security measures to protect individuals. Data that are inextricably linked to natural persons may not simply be made openly available. However, they can form the basis for an anonymised or statistical data set.
In principle, personal data must be completely anonymised and made unrecognisable when published so that no conclusions can be drawn about individuals. Personal data such as names, addresses or AHV numbers must be removed, as well as data that allows a person to be re-identified. These data are not of general interest and publication could constitute a violation of personal rights. Data can be further protected by “masking” or making other key characteristics unrecognisable. For example, publishing the year of birth instead of the date of birth provides more anonymity.
Another category of anonymisation is to publish data grouped or aggregated, i.e. summarised and generalised according to certain characteristics. For example, residents are grouped by municipality of residence, birth data is divided into larger time intervals or the qualification level is listed instead of the occupation. Another possibility are synthetic data sets. Here, completely new data is created that is no longer based on real people but has the same correlations as the original data set.
As the original data becomes more obscured, the protection for the individual increases and re-identification becomes more difficult. However, at the same time, the possibilities and accuracy of further data processing decrease rapidly. A balance must therefore be struck between public, general interest and individual protection. Which approach makes sense and is appropriate must be examined and weighed up in each specific case.
A contribution to inclusive digitisation
At Hack4SocialGood, interested parties from the social and technology sector meet to support social institutions in data and software projects and in this way promote fair and equitable innovations in the social sector. This event will support social institutions in making their data accessible in a secure way for a limited period of time. Participants will learn about new technologies for data access and data protection compliance. They will also learn about the value of open data in building a community that can be instrumental in achieving social sector goals. This can be a small step towards open and secure data use with more sharing and participation.
The Hack4SocialGood brings together people from the tech and social sectors to help social organisations find solutions to digitalisation concerns over a two-day event. Everyone can get involved in the event, regardless of their background.
- Keynote: “Augmented Intelligence in the Digital Society of the Future”, Mascha Kurpicz-Briki (Bern University of Applied Sciences)
- Panel discussion: “Social Organizations and the Challenge of Digitalization”
- Teamwork on Challenges (with regular refreshment breaks)
- 31. March, 1.30 p.m. – 1 April 6 p.m. at the Berner Generationenhaus, Bahnhofplatz 2, Bern
- Supervised children’s programme: 1 April, 9.00-15.30 hrs
Literature and further links
- Swiss Federal Statistical Office: “Open Government Data” Strategy 2019-2023
- Gkoulalas-Divanis A, Mac Aonghusa P (2014) Privacy protection in open information management platforms. IBM Journal of Research and Development 58:2:1-2:11.
- Green B, Cunningham G, Ekblaw A, et al (2017) Open Data Privacy. Social Science Research Network, Rochester, NY
- Janssen M, Charalabidis Y, Zuiderwijk A (2012) Benefits, adoption barriers and myths of Open Data and Open Government. Information Systems Management 29:258-268.
- Kostkova P, Brewer H, de Lusignan S, et al (2016) Who Owns the Data? Open Data for Healthcare. Frontiers in Public Health 4
- Swiss National Science Foundation: Open Research Data
- Sweeney L (2000) Simple Demographics Often Identify People Uniquely. Carnegie Mellon University
- Young MM (2020) Implementation of Digital-Era Governance: The Case of Open Data in U.S. Cities. Public Administration Review 80:305-315.