Teresa Scassa - Blog

The U.S has cleared the way for the use of citizen science by federal government agencies and departments in a new law titled the American Competitiveness and Innovation Act (ACIA) (awaiting presidential signature).

The ACIA as a whole should be of interest to Canadians, as it lays out the principles for how the National Science Foundation (NSF) in the United States should approach its mandate to support scientific research. Earlier bills failed to reach acceptable compromises; some of these would have restricted types of scientific research funded by the NSF to specific sectors. This has echoes of the controversial choices in Canada under the previous government to focus on applied rather than basic scientific research. The American Competitiveness and Innovation Act has moved away from this narrow approach and sets out two main criteria for funding scientific research: intellectual merit and broader public impacts.

The ACIA contains a distinct section titled the Crowdsourcing and Citizen Science Act (CCSA) which paves the way for the use by government agencies and departments of scientific research practices based upon distributed public participation. The CCSA defines citizen science as “a form of open collaboration in which individuals or organizations participate voluntarily in the scientific process in various ways.” (§402(3)(c)(1)) The level of participation can vary, and may include public participation in the development of research questions or in project design, in conducting research, in collecting, analyzing or interpreting data, in developing technologies and applications, in making discoveries and in solving problems. In its preamble, the CCSA acknowledges some of the unique benefits of crowd-sourced research, including cost-effectiveness, providing hands-on learning opportunities, and encouraging greater citizen engagement.

The CCSA specifically empowers the heads of federal science agencies to make use of crowdsourcing and citizen science to conduct research projects that will advance their missions. It enables the use of volunteers in research – something that might otherwise become entangled in red tape. The Act also directs agencies to draft appropriate policies to govern participant consent, and to address “privacy, intellectual property, data ownership, compensation, service, program and other terms of use to the participant in a clear and reasonable manner.” (§402(4))

Significantly, the CCSA also mandates that any data collected through citizen science research enabled under the legislation should be made available to the public as open data in a machine-readable format unless to do so is against the law. It also requires the agency to provide notifications to the public about the expected use of the data, any ownership issues relating to the data, and how the data will be made available to the public. (I note that these issues are addressed in my co-authored guide Managing Intellectual Property Rights in Citizen Science published by the Wilson Center Commons Lab.) The statute also encourages agencies, where possible, to make any technologies, applications or code that are developed as part of the project available to the public. This legislated commitment to open research data and open source technology is an important public policy statement.

One barrier to the use of crowdsourcing and citizen science in the government context is the fear of liability within the risk-averse culture of governments. The CCSA addresses this by proving that participants in citizen science projects enabled under the statute agree to assume all risks of participation, and to waive any claims of liability against the federal government or its agencies.

The CCSA permits federal agencies to partner with community groups, other government agencies, or the private sector for the purposes of carrying out citizen science research. After a two-year grace period, the statute also requires the filing of reports on any citizen science or crowd-sourcing projects carried out under the CCSA, and contains detailed requirements for the content of any such report.

The inclusion in this science and innovation bill of provisions that are specifically designed to facilitate and encourage the use of citizen science by governments is a significant development. It is one that should be of interest to a federal government in Canada that is attempting to carve out space for itself as open, pro-science and keen to engage citizens. Citizen science has significant potential in many fields of scientific research; it also brings with it benefits in terms of education, citizen engagement, and community development.

Municipalities are under growing pressure to become “smart”. In other words, they will reap the benefits of sophisticated data analytics carried out on more and better data collected via sensors embedded throughout the urban environment. As municipalities embrace smart cities technology, a growing number of the new sensors will capture data in real time. Municipalities are also increasingly making their data open to developers and civil society alike. If municipal governments decide to make real-time data available as open data, what should an open real-time data license look like? This is a question Alexandra Diebel and I explore in a new paper just published in the Journal of e-Democracy.

Our paper looks at how ten North American public transit authorities (6 in the U.S. and 4 in Canada) currently make real-time GPS public transit data available as open data. We examine the licenses used by these municipalities both for static transit data (timetables, route data) and for real-time GPS data (for example data about where transit vehicles are along their routes in real-time). Our research reveals differences in how these types of data are licensed, even when both types of data are referred to as “open” data.

There is no complete consensus on the essential characteristics of open data. Nevertheless, most definitions require that to be open, data must be: (1) made available in a reusable format; (2) prepared according to certain standards; and (3) available under an open license with minimal restrictions or conditions imposed on reuse. In our paper, we focus on the third element – open licensing. To date, most of what has been written about open licensing in general and the licensing of open data in particular, has focused on the licensing of static data. Static data sets are typically downloaded through an open data portal in a one-time operation (although static data sets may still be periodically updated). By contrast, real-time data must be accessed on an ongoing basis and often at fairly short intervals such as every few seconds.

The need to access data from a host server at frequent intervals places a greater demand on the resources of the data custodian – in this case often cash-strapped municipalities or public agencies. The frequent access required may also present security challenges, as servers may be vulnerable to distributed denial-of-service attacks. In addition, where municipal governments or their agencies have negotiated with private sector companies for the hardware and software to collect and process real-time data, the contracts with those companies may require certain terms and conditions to find their way into open licenses. Each of these factors may have implications for how real-time data is made available as open data. The greater commercial value of real-time data may also motivate some public agencies to alter how they make such data available to the public.

While our paper focuses on real-time GPS public transit data, similar issues will likely arise in a variety of other contexts where ‘open’ real-time data are at issue. We consider how real-time data is licensed, and we identify additional terms and conditions that are imposed on users of ‘open’ real-time data. While some of these terms and conditions might be explained by the particular exigencies of real-time data (such as requirements to register for the API to access the data), others are more difficult to explain. Our paper concludes with some recommendations for the development of a standard for open real-time data licensing.

This paper is part of ongoing research carried out as part of Geothink, a partnership grant project funded by the Social Sciences and Humanities Research Council of Canada.