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From GIS to Digital Twins

There's a global transition going on. The digital revolution including practical big data and artificial intelligence and climate change confronts policymakers with complex issues of liveability, mobility, sustainability and participation. This complexity is to a large extent caused by the fact that the issues evade traditional domains such as spatial planning, social security, environmental management and safety. They require an integral approach. Many of the issues are expressed in concrete terms in the spatial environment and thus end up on the boards of municipalities, provinces and water boards, but also of construction, infrastructure and geo-companies.

Let's first see how that policy-making process usually goes. A policy maker formulates a policy question. Based on this, an information manager or geo-ict-er collects data from multiple sources that may be useful. To give an idea of the extent of available data: The Netherlands has about fifteen thousand public data sources at local, regional and national level. The themes vary from the widely known data on plots of land, businesses, demographics and the like to data known only to specialists, such as the distribution of dung beetles.

Once the relevant data for a policy question has been gathered from all these sources, the dataset is then checked for timeliness and linkability to the company's own databases and systems. In the next step, a GIS employee analyses the validated dataset and records this analysis in maps, tables and/or texts. Partly on the basis of such reports, the policy maker ultimately formulates answers to the question posed and translates these into policy. Gathering relevant data from the multitude of available sources and compiling a validated dataset takes roughly half of all the time and energy in this process.

The compartmentalisation of the available data into separately managed databases is reflected in specialised departments, but also in separate organisations. Each department or organisation is responsible for a specific domain in the spatial environment. This combination of digital and organisational compartmentalisation makes an integral approach difficult; collecting relevant data takes a lot of time and the available information is often underused. In addition, many organisations use outdated technology, which limits the information value of the reports they produce. As a result, policymaking remains to a large extent a time-consuming 'guesswork'.

How to do it better: digital twins

Lately, the term 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 called up, analysed and visualised in a demand-driven manner. 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 quantities of historical data, serious forecasts are also possible.

Argaleo is part of a network in which, for example, Logistics Community Brabant (LCB) and the Jheronimus Academy of Data Sciences (JADS) also participate. Omgevingsserver offers a solid basis for digital twins in 3D and at all desired aggregation levels in the Netherlands: from individual objects (house, plot, parking etc.) via the street, neighbourhood, city, water board, security rayon to the provincial and national level. In addition, Omgevingsserver contains an extensive database with data from the system of key registers (BAG, Trade Register, (large-scale) topography and the like) and from other reliable open government sources, such as the National Register for Childcare, demographic data from Statistics Netherlands, the Risk Map, the National Monuments Register, Spatial Plans, Energielabel.nl and the Antenne Register. The reliability of the Environment Server 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 such as Omgevingsserver combine data from multiple spatial open data sources in the Netherlands, update them continuously and steadily expand the data available within them. This makes them an excellent basis for digital twins. The difficulty of gathering relevant data from all those datasets that are distributed is therefore a thing of the past.

Two examples of twinning

The great potential of these data services therefore lies for policymakers in the development of specific digital twins with which certain policy issues can be analysed integrally as a basis for evidence-based policy. We call this smart use of data services such as Environment server twins. Below are two examples.

A first example: what if we use a digital twin for placing bus stops in a municipality which, in addition to the geographical distribution, also takes socio-economic factors and the average duration from house to bus stop into account? In this way we can plan bus stops where people are most dependent on them. Such a digital twin helps to combat mobility poverty.

A second example: What could a digital twin look like for the theme 'bicycle accessibility'? In it we could combine the available data about the road network and functions of buildings, for example, with smart calculations (algorithms) of movements of bicycles and other means of transport, with information about particulate matter 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 better policy options.

In short: data services such as Omgevingsserver form a solid and reliable basis for analysing and answering specific policy issues using digital twins. In time, the data services will also provide more and more real-time information, such as traffic flows, sensor data, maintenance activities to infrastructure and so on. Very useful, for example, for organisers of large-scale events where those responsible for safety have continuous insight into the current situation via a real-time digital twin. In short, a solid basis for policy decisions.

The impact of twinning

Twinnen is a powerful tool for integrated and evidence-based policy development for complex social issues. In addition, twinning will also have an impact on the organisation of the policy-making process. Different departments and organisations will work together more intensively, perhaps even integrate. But functions will also change. Take the role of GIS staff, for example. This evaluates from data collection and analysis for the benefit of departments to the facilitation of integrated policy teams in making optimal use of digital twins, by unlocking and linking information from their own data sources and helping to develop dashboards on specific social or business economic themes.

Morality of the story: anyone who wants to get a grip on the transition we are in the middle of, stops guessing and starts twinning today.