The Internet of Things (IoT) is the network of traditionally unconnected devices that are now equipped with connectivity in order to provide better or additional services. Typically these devices communicate over the internet, are uniquely identifiable, and interoperate with existing internet services. Smart cars, watches, thermostats and meters are examples of IoT devices. Gartner (2013) estimates there will be nearly 26 billion IoT devices by 2020. Big data from smart devices connected to the IoT provides new societal and business opportunities, and has potential to become highly valuable input for evidence-based policy development. In practice however, seizing such opportunities seems to be limited by several factors:
- The lack of an appropriate regulatory framework. Such framework is needed in order to tackle legal, privacy and information security-related issues. It should also define and recommend particular applications in evidence-based policy.
- Hesitation by market parties to share data. Platform owners are the primary collectors of IoT data, but are hesitant to share it with others because the data is privacy- and/or competition sensitive. In addition there is little strategic incentive for market parties to share data for the benefit of other (unrelated) private organisations or government.
- High variety. While the big data discussion is often centred around volume, we suspect the real problem with IoT data will be variety. The landscape of IoT devices is still highly fragmented. There is also a lack of standardization of methodologies and definitions for evidence-based policy based on IoT data.
- Large differences in data quality. Traditional frameworks for quality are rigid and are difficult to use in the context of high-variety IoT data. In addition assessing the quality of IoT data is more difficult than for data collected using more traditional methods.
Bongers et al. (2015) argue that a government can fulfill four different broadly-defined roles with respect to big data. In the context of IoT data specifically, we recommend the following, in order to enable the opportunities for public and private organisations provided by IoT data:
- Governments at the supranational level should set (policy) guidelines and perimeters for using and handling IoT data. This mitigates issues (1) and in part issue (2). Institutions involved in statistics at the supranational level can help by setting methodological standards (issue (3)) and developing frameworks for data quality (4).
- Governments at the national level should facilitate implementation. A particular way to do this is to set up clearing houses for relevant IoT data. This lowers the barrier for platform owners to share data and mitigates issue (2)
- Governments at all levels should set an example by opening up own data sources (‘open data’). In addition, they should invest in using and integrating IoT data in their policy development processes. Governments should be ‘launching customers’ of IoT data.
Working paper by Arthur Vankan and Tommy van der Vorst, 2015.