Recommendation 6: Identify where digital public services can be simplified or transformed using location information and location intelligence, and implement improvement actions that create value for users
| Implementation guidance | Related information |
|---|---|
Why
- As everything happens in a place or space, location information underpins many digital public services. However, this is not always understood or recognised, and location information is not always used in the most effective and efficient ways.
- Administrative burdens can be reduced and better services delivered with optimal use of location information, accessed via digital channels whenever appropriate.
- Location intelligence provides new means to gather insight, driving innovation in digital public services.
- Such action will help realise the value of location information in digital public services.
- Data, in all forms, is becoming a fundamental resource, with digital public services relying on and creating large amounts of data. Location data and interoperability concerns need to be assessed for their full contribution in these contexts and not be seen as a separate effort or after-thought.
- Users of digital public services have increasing expectations on the nature and integration of the online experience, based on their exposure to private sector applications.
How
Key events inventory
- A focus on ‘key events’ which are in some way related to ‘location’ can help in deciding priorities for optimisation of relevant digital public services.
- Look for events that trigger a series of cascading actions and location data exchange across a network of people, businesses and organisations, and things to achieve a singular objective (e.g. moving house).
- Create an inventory of key digital government processes and services that play a role in such events and determine in which location information plays a significant role.
- Document use cases for such events in a common structured manner as this will increase the possibility of re-use and interoperability, with the associated economic advantages and user benefits. Consider using the following classification:
- This approach will support organisational interoperability by setting a common description across Member States, a first step towards reuse of practices and then solutions. Use cases can then be documented according to the different possible scenarios related to the roles of different actors: G2G, G2B, G2C and the intermediary role for government to provide the rule engine for the different producers and consumers of data.
Digital public service optimisation
- Analyse opportunities for improving digital public services and processes in their use or potential use of location information, through internal analysis (e.g. using BPMN), external analysis (e.g. customer insight techniques) or external comparison (e.g. benchmarking, examining best practices in other Member States or other administrations in the same Member State). This can be best achieved by applying the following event-based approach:
- Step 1: Identify key events in your environment in which location data plays a critical role. Key events are ideally real-life cases which are very recognisable and impact multiple stakeholders e.g. precision emergency response to incidents (e.g. terror attack, boat capsizes, oil spill, flooding, search and rescue, etc.) or natural disaster (e.g. tornado, tsunami, etc.) or human-related incidents (e.g. job losses, human and drug trafficking, etc.) or events impacting the local community (e.g. litter, graffiti, maintenance of street furniture, traffic flows, schools and crèche services);
- Step 2: Analyse the bilateral data exchanges amongst the different stakeholders involved in the processes of the key event. (Techniques such as BPMN, Use Case Diagrams and Data Modelling can support this step);
- Step 3: Rethink the processes and data exchanges, considering their role in any broader data ecosystem and exploring different options for multidirectional exchange of data;
- Step 4: Analyse what new (location-) intelligence techniques could add value either using existing data sources or connecting with new data sources. Techniques could be for example: site location optimisation (e.g. police force deployment, automated public lighting), location impact simulation (e.g. oil spill), geographic concentration (e.g. terrorism threats);
- Step 5: Look for new ways of collaboration with all stakeholders who might benefit from the processes and data exchanges being assessed. Stakeholders, in this context, could be those engaged in the data ecosystem, potential partners in a digital collaboration platform (‘digital platform’), contributors to a digital public service or users of a digital public service. Evaluate the impact on their business and operating model, and the benefits to end-users, as input to define the new digital public services. Consider, for example, how various external parties can be integrated in the processes involved in digital public service delivery or how they may benefit from the outputs of the digital public service. This could be integration of external companies in the service delivery model with associated sharing of location data (e.g. supply of energy saving solutions to citizens and businesses signing up to energy saving initiatives), involving citizens or businesses in volunteering activities in a local borough (e.g. to clean up parks), or engaging citizens in problem reporting (e.g. ‘Fix My Street’ type reporting linked to scheduling systems for priority-based problem resolution).
Data ecosystem optimisation
- Some individual digital public services are part of a broader data-driven digital ecosystem (or ‘data ecosystem’ for short), which needs to be considered at the macro level in order to determine the role of government (the public task), the effectiveness of the ecosystem for different participants and users, and actions to improve effectiveness in particular areas. The focus of the Blueprint is on data ecosystems where location data plays an important role.
- Data ecosystems involve different actors exchanging data around a common purpose. Typically, this means different public sector and non-public sector actors (e.g. businesses, NGOs, citizens, academia). Public administrations may be a participant in the data ecosystem (e.g. road transport) or orchestrate the ecosystem (e.g. smart city management, climate action programmes, pandemic management).
- Triggers for examining ecosystem effectiveness include a policy initiative (e.g. climate policy, open government policy), an unforeseen event (e.g. pandemic), a failure in the ecosystem (e.g. traffic accident levels, crime levels), demands from or expectations of participants and users (e.g. parking availability), developments in use of technology (e.g. IoT, digital twins), or government funding actions to stimulate growth (e.g. infrastructure projects), prioritise investment or deliver savings for the taxpayer.
- Good practices for public administrations involved in data ecosystems depend on the nature of the ecosystem and their role. Some examples are described below:
- Coordinating agreements on data models and data exchange standards necessary for the functioning of the ecosystem (e.g. travel information standards, data exchange standards for managing underground works, integration of geospatial and BIM standards in smart cities);
- Making public data available openly determining with ecosystem partners how best to meet their needs. One aim in this is to enable private sector companies to develop products and services for the ecosystem and the broader market (e.g. Transport for London open data and unified API for developers);
- Coordinating or participating in data sharing communities associated with the ecosystem (e.g. Intelligent Transport Systems community, UK Transport Data Initiative);
- Developing platforms for exchanging data between multiple actors as well as delivering services and information (e.g. multi-purpose urban platforms for policy and operational management in cities);
- Integrating dynamic and static location data in smart city applications, using IoT devices and cameras, localised processing, and integration of streamed data;
- Coordinating or participating in ecosystems to support policy goals (e.g. Sonderborg Project Zero, Covenant of Mayors for Climate and Energy). These initiatives may include action plans, projects for different actors in support of collective goals, funding incentives, localised data collection and reporting (e.g. through a city dashboard), scenario analysis of optimal solutions (e.g. best sites for solar energy, traffic congestion measures), and localised multi-dimensional reporting against targets aggregated across different levels of government;
- Using evidence in decision making to ensure effective operation of the ecosystem (e.g. assessing impact of altering speed limits on traffic flow and safety);
- Analysing value chains and impact on different actors in the ecosystem when assessing potential changes or improvements in digital public services and use of location data that are part of the ecosystem;
- Consider opportunities for connecting with new data sources and actors, including developments at a European level with the emerging common European data spaces;
- Prioritised and interconnected projects undertaken in collaboration with different actors in the ecosystem, with associated governance arrangements to manage dependencies and ensure value delivered for multiple stakeholders;
- Funding models relevant to the functioning and sustainability of the ecosystem or core data to support multiple ecosystems (e.g. KLIP underground works in BE, Basic Data Programme in DK).
Digital platforms
- A digital platform is a business-driven framework that allows a community of partners, providers and consumers to share, extend or enhance digital processes and capabilities for the benefit of all stakeholders involved through a common digital technology system.
- A digital platform is a new way of organising, thinking and collaborating around digital government. To adopt such an approach involves a new business model, new funding structures and possibility alterations to legislation.
- Digital platforms may be used for standalone digital public services, digital public services that are part of a broader data ecosystem or a collection of digital public services, which may be provided by a single public administration (e.g. services related to city governance and operations) or multiple administrations (e.g. a national government digital platform).
- Public administrations may have different roles in the digital platforms in the same way as they have in data ecosystems mentioned above. In fact, a digital platform may be used to support the whole ecosystem or form part of the overall ecosystem.
- The most logical starting point for public administrations that seek to explore platform business models is to start with orchestration business models, as these provide a natural role for public administrations to coordinate interaction between distant groups in society. Using a digital platform approach shifts government (and others) to facilitating the integration of business processes between different actors within an ecosystem.
- The approach for public administrations implementing digital platforms may include:
- Establish your own (government-led) digital platforms, engage in platform “co-creation” with other public or private sector stakeholders, or devise appropriate strategies on how to operate with privately owned digital platforms, as provider, consumer or ecosystem partner;
- Evaluate with stakeholders the data exchange and analytical requirements and the appropriate technologies for addressing these requirements (e.g. IoT and location intelligence components, a ‘digital twin’ approach with associated scenario modelling);
- Invest in creating and designing ecosystem partnerships to channel value to digital platforms or to ensure the digital platform delivers value to the broader data ecosystem. Foster ecosystems around government platforms or support the creation of ecosystems around private platforms;
- For public administrations providing data as part of the ‘user-driven SDI’, this may involve designing the platform to target specific needs (use cases) and collaborating with the relevant stakeholders, e.g. around priorities, finance, formats, service levels.
Technology innovation
- Public administrations should consider opportunities linked to technology innovation and approaches to investigate these opportunities, such as establishing a ’technology watch’ or collaboration with universities. An example of technology innovation is the use of location intelligence for predictive policing and public safety to better position resources to improve response time.
- Technology watches should focus on the variety of technologies that influence the evolution of Digital Government, as depicted in the Gartner Hype Cycle for Digital Government. The analysis should cover both the potential for innovation and their benefits but also the time to maturity of the technology, which has an impact on the risk of investing in this technology. An example is presented below, which lists the technology trends that will impact location intelligence, according to Gartner. These trends are classified both in terms of their number of years to mainstream adoption and in terms of benefit.
- New technologies should be considered in the relation to existing and potential needs of public administrations in order to be able to answer the question ‘why should we be interested in particular technologies?’ See below, the home page for a technology awareness tool created by KL (Local Government) Denmark.
Improvement programmes
- Establish improvement programmes in priority areas where public location information can be used more effectively in digital public services and processes, data ecosystems and digital platforms.
- Ensure users, partners and operational staff involved in service delivery are consulted on priorities and design of improvements.
- Determine the most cost-effective business models, from step-changes in the approach (e.g. the introduction of a collaborative ‘digital platform’ supporting new business models to replace previous bi-lateral arrangements) to more incremental improvements (e.g. revising a single part of the process, relationships with a single actor).
- Look for quick wins to demonstrate progress.
- Establish and publicise ‘model implementations’ in repeatable areas to encourage wider take-up of good practice (e.g. smart city architectures, applications and components (e.g. my nearest bus stop, reporting a problem, finding a parking space).
- Look elsewhere nationally and in other MS to identify good practices that can be re-used.
- Introduce methods of continuous assessment involving all stakeholders, to help in planning and delivery of incremental improvements, identify new factors that need to be considered, and ensure interoperability is maintained over time as location-enabled services and solutions evolve.
Challenges
- Better use of location information is only one aspect of public service improvement.
- The significance and benefits of well-managed or applied location information may not be understood or be clear.
- The benefits of investment in other areas may be more cost effective or felt to be more cost effective because they are more clearly understood and defined.
- Individual digital public services may be collectors, providers or users of location information. The same information may be relevant in many other digital public services and wider contexts. This is particularly the case for core location data, e.g. addresses, buildings information, transport information. However, the wider context may not be taken into account in planning individual investments.
- Digital platforms imply new collaboration and funding models and, possibly new legal instruments, together with changes in governance of data (e.g. ownership, sharing), leading to reuse, for example, of non-open data and definitions of new licensing models.
- Innovating with new technologies involves having enough time and resources to test scenarios and carry out evaluations. In this way, risks are mitigated and relevant opportunities identified.
- The value of location intelligence and the techniques that might be applicable may not always be understood or appreciated.
- Lack of available skilled resources may inhibit large scale adoption of new technologies.
- Smart spaces, smart city platforms and digital twins involve collecting, processing and analysing large amounts of data, including combining dynamic, static and modelled data from multiple sources. There are challenges in data integration and ensuring interoperability in these complex data-driven applications.
Best Practices
- # 1: A digital platform for location data in Flanders
- # 4: Rotterdam Digital City
- #14: Air quality monitoring and reporting in Belgium
- #18: Territorial Information System of Navarre: SITNA
- #21: Integrated transport solutions: TRAVELINE
- #22: Standardised road safety data exchange
- #23: INSPIRE-compliant marine environment e-reporting
- #30: Location intelligence for ground works – KLIP platform
- #31: Helsinki 3D
- #32: City of Madrid - Asistencia COVID19
- #33: Urban platform, Guimarães
- #37: Integrated Rescue System
- #40: Rubber Boot Index
- #41: Public private partnership for development and release of hydrological elevation model
- #45: Common Services BUILD
- #46: Citizen Map
- #47: IDE-OTALEX
- #49: Rennes Urban Data Interface (RUDI)
- #51: Hinderpremie
- #52: BDZ RADAR train locator application
- #53: Multimodal mobility - LinkingAlps
- #56: Cadastre of Public Law Restrictions on Landownership (PLR Cadastre)
- #57: Federal Register of Buildings and Dwellings
- #62: KAMP a climate change tool
- #69: Édugéo
- #72: myProjectIreland
- #73: PELL Public lighting platform
- #74: Kurgyvenu.lt
- #75: REGIA
- #76: Boer & Bunder - Data-driven services for growers and agribusiness
- #77: Risicokaart - How to spot risk situations that can lead to disasters and crises
- #86: Praia em Directo
- #87: Smart Built Environment
LIFO Monitoring
The Location Information Framework Observatory (LIFO) monitors the implementation of EULF Blueprint recommendations in European countries. Read about the implementation of Recommendation 6 in the LIFO Country Factsheets or the LIFO European State of Play Report. Explore the results for selected countries at LIFO Interactive Dashboards - Recommendations.
Related Frameworks: European Interoperability Framework (EIF)
| EIF Pillars | Recommendations |
|---|---|
| Underlying Principle 6: User centricity | Recommendation 13: As far as possible under the legislation in force, ask users of European public services once-only and relevant-only information. |
| Underlying Principle 10: Administrative simplification | Recommendation 17: Simplify processes and use digital channels whenever appropriate for the delivery of European public services, to respond promptly and with high quality to users' requests and reduce the administrative burden on public administrations, businesses and citizens. |
| Interoperability Layer 4: Organisational Interoperability | Recommendation 28: Document your business processes using commonly accepted modelling techniques and agree on how these processes should be aligned to deliver a European public service. |
Related Frameworks: UN-GGIM Integrated Geospatial Information Framework (IGIF)
Strategic Pathway 5: Innovation
| Documentation | Elements |
|---|---|
|
Technological Advances Innovation and Creativity Process Improvement Bridging the Geospatial Digital Divide |
| Actions | Tools |
|---|---|
| 2. Identifying Innovation Needs | |
| Monitoring Trends | APP5.3: Geospatial Drivers and Trends |
| Technology Needs Assessment |
APP5.4: ICT Data Inventory APP5.5: PEST and SWOT Analyses |
| 3. Transformation Roadmap | |
| Modern Data Creation Methods |
APP5.7: Modern Data Creation Methods |
| Enabling Infrastructure |
APP5.8: Data Integration Approaches APP5.9: Data Storage Processes |
| 4. Culture of Innovation | |
| Geospatial Digital Transformation Strategy |
Future trends in geospatial information management: the five to ten year vision (third edition) Framework for Effective Land Administration Strategic Framework on Geospatial Information and Services for Disasters COVID-19: Ready to Respond - The role of the Geospatial Community in Responding to COVID-19 |
| 5. Operationalising Innovation | |
| National Innovation System | |
| Innovation Programmes | APP5.10: Pillars of an Innovation Programme |
| Innovation Hubs | |
| Process Improvement | APP5.11: Critical Path Analysis |
| 6. Innovation Ecosystem | |
| Bridging the Digital Divide | APP5.12: Open SDG Data Hubs |
| Integrated System of Systems |
ELISE Resources
Further Reading
- United Nations E-Government Survey
- OECD Digital Government
- Digital Government Benchmark - Study on Digital Government Transformation
- EU Cohesion Policy 2014-20
- EU Cohesion Policy 2021-27
- EU Smart Specialisation Platform
- Declaration on joining forces to boost sustainable digital transformation in cities and communities in the EU
- E-Government: Using technology to improve public services and democratic participation, European Parliamentary Research Service, 2015
- ISA2 Innovative Public Services: Bringing new technologies into the public sector
- Transport Data Initiative
- Transport for London – Open Data and APIs
- Intelligent Transport Systems, European Commission
- Intelligent Transport
- FixMyStreet
- GIS and BIM integration leads to smart communities, ESRI
- Project Zero, Sonderborg
- Covenant of Mayors for Climate and Energy
- European data strategy, 2019
- The technological future of municipalities - a tool for knowledge and dialogue, KL (Local Government) Denmark
- Principles for Spatially Enabled Digital Twins of the Built and Natural Environment in Australia
- Digital twins for the built environment, Atkins
- Digital Urban European Twins (DUET)
- Ordnance Survey Case Studies
- Geospatial Singapore
- Geospatial AI/ML Applications and Policies: A Global Perspective, World Geospatial Industry Council Policy Report, 2021
- SmartCitiesWorld City Profile - BarcelonaHelsinki’s 3D city models and Kalasatama Digital Twins Project, Final Report
- Fin Est Digital Twin Cities – 3D city model demonstration