Group items tagged

Purpose should govern the choice of dataset to focus on Standards should be the primary guide to the design of the datasets User engagement should influence engagement activities ‘on top of’ published data to secure prioritised outcomes New user needs should feed into standard extension and development User engagement should shape the initiatives built on top of data

The call for ‘raw data now‘ was not without purpose: but it was about the purpose of particular groups of actors: not least semantic web reseachers looking for a large corpus of data to test their methods on. This call configured open data towards the needs and preferences of a particular set of (technical) actors, based on the theory that they would then act as intermediaries, creating a range of products and platforms that would serve the purpose of other groups. That theory hasn’t delivered in practice

They describe a process that started with a purpose (“get better bids on contract opportunities”), and then engaged with vendors to discuss and test out datasets that were useful to them.

Aggregated Location Data Analysis of aggregated location data can be used to identify hotspots of transmission and forecast future trends on transmission. This can help governments measure the efficacy of existing measures as well as guide government decision-making going forward, on subjects such as public-health interventions and where to allocate testing and medical resources. This kind of data will be particularly significant for governments as lockdowns are eased; it is essential that governments are able to gather real-time insights on the effectiveness of their interventions.

Medical experts currently believe that the virus is transmissible within 2 metres – meaning a person must come in contact within 2 metres of an infected person to have a chance of contracting it from social interactions. Therefore, effective digital contract tracing requires highly precise data. However, most extant technology was not designed to rapidly geolocate devices at that level of precision, meaning most location data is less precise than 2 metres. The ongoing challenge for technologists is to either adapt extant technology for a purpose for which it was not designed or build new solutions that can deliver the required level of precision.

ost notably, if the data used for generating location and mobility insights is weak (low precision and low accuracy), then the privacy implications may be less stark – but the value of the exercise also decreases. Both individual tracking and generating aggregated mobility insights based on weak location data can result in flawed insights. This can have a range of undesirable costs for both individuals and governments.

This volume explores these questions and introduces the principles and practice of a quietly growing field: systems thinking. With roots in disciplines as varied as biology, cybernetics, and ecology, systems thinking provides a way of looking at how the world works that differs markedly from the traditional reductionistic, analytic view. Why is a systemic perspective an important complement to analytic thinking? One reason is that understanding how systems work – and how we play a role in them – lets us function more effectively and proactively within them. The more we understand systemic behavior, the more we can anticipate that behavior and work with systems (rather than being controlled by them) to shape the quality of our lives.

For example, this information could help officials understand changes in essential trips that can shape recommendations on business hours or inform delivery service offerings.

Ultimately, understanding not only whether people are traveling, but also trends in destinations, can help officials design guidance to protect public health and essential needs of communities.

The Community Mobility Reports are powered by the same world-class anonymization technology that we use in our products every day. For these reports, we use differential privacy, which adds artificial noise to our datasets enabling high quality results without identifying any individual person.