Monithon, its name a contraction of the words monitor and marathon, is citizen-based monitoring effort in Italy that seeks to evaluate the success of local projects funded by the EU. Small groups of volunteers, sometimes from the Monithon development team and otherwise comprised of concerned citizens, assess the progress of projects and identify potential problems as they crop up. Finding projects to watch over is made easy due to OpenCoesione, a government-initiated open data portal that provides visualizations for funds allocated and projects supported. The result is ample access to valuable data given to committed volunteers armed with the skills needed to make sense of it.

This entire model demonstrates well what monitorial citizenship entails – groups of individuals paying attention to government-funded works in their areas of interest. When split into its discrete components, however, elements of both participatory and justice-oriented citizenship also shine through. Much of it has to do with OpenCoesione and the willingness of the government to release data to the public. But, as mentioned in Ethan Zuckerman’s post, just having data is never enough. Luckily, “open data days” and other data analysis workshops have sprung up in Italy in order to teach individuals and young students how to interpret the information at their disposal. This data literacy is vital as it sets the foundation for multiple types of civic engagement. From the technical skills taught come the potential of participatory citizenship; students who know how to assemble garbled data into coherent narratives are capable of participating in projects such as Monithon that rely on skilled interpreters of statistics. Such workshops can also introduce students to the critical mindset held by justice-oriented citizens. It takes a stolid mind to work on discerning between good government practices and poor ones without thinking about the structural implications of the results. Thus, while being trained in data analysis might not be a direct exposure to the more abstract, structural analytics associated with justice-oriented citizenship, it certainly offers a glimpse of what problems may lie deep within the data and what flaws may exist in the system.

Questions remain as to how Monithon might be made even better. For one, participatory movements are difficult to expand. The case study on Rynda pointed out that the platform created served more as a way for previously active citizens to interact and allocate resources, rather than encouraging support from usually disinterested segments of the population. Giving workshops for students and getting them involved early on certainly approaches this problem , but it’s possible that participation could be harnessed from a greater number of people, as with Social Cops. What was required from the average contributor for Social Cops, however, was simply an indication of whether or not their trash was collected. While movements can be made highly successful by decreasing the commitment necessary to be involved, it’s a markedly different sort of participating than what developers or data analysts do. Providing data may even be more akin to an act of personally responsible citizenship – donating information as one would food or money. The efficacy of limited scope can also be brought into question. Can many groups of people narrowly focused on specific projects lead to national discussions about things such as systematic disenfranchisement of certain social groups, or other dialogues that require an analysis of structural as well as infrastructural context? Perhaps a new method could be made, similar to Monithon but with a slightly different purpose: for the identification of far more nebulous systemic failures.