PoliVisu’s approach to data-driven policy experimentation is being tested in the field of smart mobility, chosen because transport forms the backbone of all urban economies. The ability to move freely, cost-effectively and easily is one of the most important drivers of economic and societal development. Mobility policies are interdisciplinary with a direct impact on urban development and the environment. For example, urban congestion, an exponentially growing problem in Europe, contributes to over 40% of all CO2 emissions and up to 70% of other pollutants. The cost to society includes an impact on health and damage to the environment. The cost to drivers of wasted time across all 45 662 major European traffic hotspots (identified in 2016) could amount to EUR 207.9 billion by 2025. It is clear that European cities require effective strategies to help overcome these challenges.
Yet, policymaking can be a long and laborious process, which struggles to keep up with the realities of everyday life. For instance, despite policies such as the Kyoto Protocol, which over 10 years ago set out strategies to cut CO2, cities such as Paris are suffering the highest levels of air pollution in over a decade. Today’s policymakers have a need to act urgently, working with city managers to craft, trial and assess short-term measures, including new transport initiatives, to more rapidly achieve their overarching policy goals.
While the private sector understands the analytic possibilities unleashed by the transport data tsunami, e.g. the release of ‘big’ flight data by the airline industry for open innovation to generate more effective sales, much of the public sector has yet to catch up. Decision makers are still rooted in traditional ways of doing things, making policy decisions based upon static models of consultation and closed planning meetings over a timeframe of a year or more. As a result, decision-making is often siloed and slow, with thinking and solutions out of date by the time policy is ready to be implemented.
When it comes to modern transport policy, legislation and regulation will mean the difference between a potentially green utopia and a congested dystopia. Adopting new technology alone is not enough, systemic thinking is needed and the use of big data can help. While the concept of driverless cars is undeniably attractive, what happens if we have ever more cars clogging up our streets, polluting the air, driving around endlessly, free from the need to ever pay for parking? What type of policies will create more green, pedestrian spaces in cities? Should cities be taxing journeys not cars; establishing high levies for single passenger journeys rather than increasing fuel costs? New methodologies and tools are needed to explore, experiment and test innovative approaches to addressing policy challenges. PoliVisu sets out to create these tools and bring them together into a digital toolbox for all cities to use and benefit from.
To take advantage of the increasing opportunities presented by big city data for improving policymaking the PoliVisu – policy visuals toolbox project believes two major objectives must be addressed:
- Data literacy: PoliVisu ensures the opportunities presented by big data in policymaking are open to all public administrations across Europe by:
- developing and testing a collaborative framework for policy design and big data interplay that public administrations can use alongside their current process (evolution, not revolution);
- packaging tools and support material in a toolbox enabling public administrations to undertake policy experimentation;
- offering free training to cities across Europe to use the PoliVisu Toolbox to learn how open and big data can be harnessed for collaborative policymaking;
- creating positive user stories from the results of the PoliVisu Toolbox to showcase the business case for the use of big data for policymaking.
- Advanced technology: PoliVisu will make it easier to analyse data and derive accurate insights for policy development in a real-world context by:
- providing decision makers (policy and operational) with visual, map-based, interactive data analytic tools that will facilitate data-driven decision-making;
- integrating crowd-sourcing applications that utilise existing social media channels to support collaboration and open policymaking;
- ensuring that the PoliVisu tools are scalable, pluggable and interoperable so they can be used with any administrations existing data platforms;
- testing the tools with the use of real big data sources including real-time data publication in resource description framework (RDF) and its further combined use (e.g. road sensor data, parking availability data, traffic cameras data, city bike rental availability, public transport schedules general transit feed specification (GTFS) data).