These enable people to share their data, anonymously, for specific purposes or social benefit.
Some data commons specialise in particular types of data, such as health, and have a very specific purpose. These commons are not open to the public in the same way, as the data is far more sensitive and members of the commons use the restriction as leverage to give themselves a voice and stake in how it used. For instance, health data commons offer a trade-off to pharmaceutical companies and medical researchers that access to the data is dependent on members being given a say in which research is conducted, and which pharmaceutical research and development is undertaken.
The creation of personal data commons has started to result in some powerful analytical insights. At first, data was limited and the use of it tended to be on small-scale responses and solutions. But after more people participated, and more personal data sets started flowing in, there are now significant insights which can be linked, blended, and analysed, all under underpinned by a system of trusted permissioning and transparency over who has access.
Over time, this resource has become useful to policymakers, social researchers, businesses and other third-party app developers who may also tap into to the data commons for a rich array of linked datasets. They pay an extra fee if they intend to use the information to generate data-driven services that turn a profit.
A minority of mainly older people do not participate in data commons, or store their personal data in one place. They rejected computer technology, either for practical or philosophical reasons, and live without it. By rejecting technology these people are absent from the picture created by data commons and smart citizen sensing labs.
In response, the city government has to factor in that this section of society is not being represented by data. City data analysts have developed statistical techniques to factor in their absence. It also reinforces the need for the city government to continue offline consultation and engagement work, so that there is always a means for people to contribute which doesn’t involve technology.
Looking for work and sufferring from a long-term health condition
Florence has lupus, an autoimmune condition which restricts her ability to work full-time, regular hours. The gig economy meets many of her needs, enabling her to work when she can but take time out when she needs to for health reasons. After a negative experience with a commercial gig work platform - which initially seemed promising because of the higher fees it paid - Florence joined a cooperatively-run gig work platform. Through this platform Florence can quickly find work, and all members have collectively agreed rules which prevent undercutting of payment rates. The platform has a Mutual Benefit Fund, which can provide financial assistance for people unable to work due to health or other reasons. While Florence tries not to call on its help, every now and then it provides a vital lifeline.
Florence is also active in a national data commons for people with lupus. Due to the relative rarity of the condition, a local scheme initially struggled to achieve the scale needed to create a dataset which could be used by researchers, so a national commons was formed. Members of the cooperative work with researchers and pharmaceutical companies to have their experiences and preferences reflected in the type of work that is carried out with their data. A fee is paid by organisations accessing the data, which helps meet the running costs of commons.
Members negotiate that companies must adhere to high standards of data security, and publish any results from the studies that use their data. In turn, Florence contributes as much data as she can in the hope that by considering a wide range of factors, there is more chance that positive interventions might be found.