A global transition is underway. The digital revolution now including practical big data and artificial intelligence, and climate change, confronts policymakers with complex questions about livability, mobility, sustainability and participation. Much of this complexity is caused by the fact that the issues escape traditional domains, such as spatial planning, social security, environmental management and safety. They require an integrated approach. Many of the issues manifest themselves concretely in the physical environment and land on the desk of municipalities, provinces and water boards, but also of construction, infrastructure and geo companies.
Let’s first look at how the policy-making process usually proceeds. A policymaker formulates a policy question. On the basis of this, an information manager or geo-ict professional collects data from multiple sources that may be useful. To give an idea of the scale of available data: the Netherlands has about fifteen thousand public data sources at the local, regional and national level. The topics range from the well-known data about plots, businesses, demographics and the like to data known only to specialists, such as for example the distribution of dung beetles.
Once the relevant data for a policy question has been gathered from all those sources, the dataset is then checked for timeliness and compatibility with own databases and systems. In the next step, a GIS professional analyzes the validated dataset and documents this analysis in maps, tables and/or texts. Based in part on such reports, the policymaker ultimately formulates answers to the posed question and translates them into policy. Gathering relevant data from the multitude of available sources and compiling a validated dataset takes roughly half of all time and energy in this process.
The compartmentalization of the available data in separately managed databases is reflected in specialized departments, but also in separate organizations. Each department or organization is responsible for a specific domain in the physical environment. This combination of digital and organizational compartmentalization complicates an integrated approach; gathering relevant data takes a lot of time and often the available information is not sufficiently used. Moreover, many organizations use outdated technology, which limits the information value of delivered reports. Policy-making remains for an important part time-consuming “GIS work”.
How it can be better: digital twins
Lately, the concept of digital twin has been buzzing around in geo circles. A digital twin is a digital, three-dimensional copy of, for example, a city, region or country, in which all available information is available in a location- and object-oriented manner. With special viewers and dashboards, all this information can be retrieved, analyzed and visualized on demand. With the help of such a smart, digital representation of reality, policymakers can formulate evidence-based answers to relevant policy questions much better than before. The digital twin is not a recent innovation; the technology has existed for ten years and is now mature. By applying smart algorithms to large amounts of historical data, serious forecasts are also possible.
Argaleo is part of a network that also includes, for example, Logistics Community Brabant (LCB) and the Jheronimus Academy of Data Sciences (JADS). Omgevingsserver offers a solid foundation for digital twins in 3D and at all desired aggregation levels in the Netherlands: from individual objects (house, plot, parking space etc.) via street, neighborhood, city, water board, safety district to provincial and national level. In addition, Omgevingsserver contains a comprehensive database with data from, among other things, the system of basic registrations (BAG, Trade Register, large-scale topography and the like) and from other, reliable open government sources, such as the National Register of Childcare, demographic data from the CBS, the Risk Map, the Register of National Monuments, Spatial Plans, Energy Label.nl, the Antenna Register. The reliability of Omgevingsserver is guaranteed by continuous validation and updating of data, while the system is compatible with common viewers and GIS systems. Finally, Omgevingsserver is based on the DAAS concept: web-based, reliable and without additional costs for data management, hardware and software.
Cloud-based data services like Omgevingsserver combine data from multiple Dutch spatial open data sources, continuously update them and gradually expand the data available within them. They thus provide an excellent foundation for digital twins. The laborious task of gathering relevant data yourself from all those scattered available datasets is now a thing of the past.
Two examples of twins
The great potential of these data services for policymakers lies in developing specific digital twins with which certain policy issues can be analyzed in an integrated manner as a basis for evidence-based policy. This smart use of data services such as Omgevingsserver is what we call twinning. Below are two examples.
A first example: what if we use a digital twin to place bus stops in a municipality that takes into account not only geographic distribution but also socioeconomic factors and the average walking time from home to bus stop? In this way, we can place bus stops where people depend on them most. Such a digital twin helps combat mobility poverty.
A second example: What would a digital twin for the theme ‘bicycle accessibility’ look like? In this, we could combine the available data on the road network and building use functions, for example, with smart calculation (algorithms) on bicycle and other vehicle movements, with information about fine dust and the nature of the road surface (nice smooth asphalt or cobblestones?). In this way, twinning provides policymakers with new, evidence-based insights and thus also better policy options.
In short: data services such as Omgevingsserver provide a solid and reliable foundation for analyzing and answering specific policy questions using digital twins. In time, the data services will also increasingly provide real-time information, such as traffic flows, sensor data, infrastructure maintenance activities and so on. Very useful for, for example, organizers of major events where safety officials have continuous insight into the current situation through a real-time digital twin. In short, a solid foundation for policy decisions.
The impact of twinning
Twinning is a powerful tool for integrated and evidence-based policy development for complex societal issues. Additionally, twinning will also have an impact on how the policy-making process is organized. For example, different departments and organizations will collaborate more intensively, perhaps even merge. But roles will also change. Take the role of GIS professionals, for example. They will shift from evaluating data collection and analysis for departments to facilitating integrated policy teams in optimally using digital twins, by providing access to and linking information from their own data sources and helping develop dashboards on specific societal or business themes.
The moral of the story: those who want to get policy control over the transition we are in the middle of will stop guessing and start twinning today.