- Value [1] Modeling
- On policy modelling and simulation, thanks to standardisation and reusability of models and tools, system thinking and modelling
applied to policy impact assessment has become pervasive throughout government activities, and is no longer limited to high-profile
regulation. Model building and simulation is carried out directly by the responsible civil servants, collaborating with different
domain experts and colleagues from other departments. Visual dynamic interfaces allow users to directly manipulate the simulation
parameters and the underlying model.
- Value [2] Simulation
- Value [3] Standardisation
- Value [4] Reusability
- Value [5] Productization
- Policy modelling software becomes productized and engineered, and is delivered as-a-service, through the cloud, bundled with
added-value services and multidisciplinary support including mathematical, physics, economic, social, policy and domain-specific
scientific support.
- Value [6] Engineering
- Value [7] Cloud Services
- Value [8] Added-Value Services
- Value [9] Multidisciplinary Support
- Value [10] Mathematics
- Value [11] Physics
- Value [12] Economics
- Value [13] Scientific Support.
- Value [14] Interoperability Standards
- Cloud-based interoperability standards ensure full reusability and composability of models across platforms and software.
- Value [15] Composability
- Value [16] Dynamics
- System policy models are dynamically built, validated and adjusted taking into account massive dataset of heterogeneous data
with different degrees of validity, including sensor-based structured data and citizens-generated unstructured opinions and
comments. By integrating top-down and bottom-up agent based approaches, the models are able to better explain human behaviour
and to anticipate possible tipping points and domino effects.
- Value [17] Big Data
- Value [18] Heterogeneous Data
- Value [19] Structured Data
- Value [20] Unstructured Data
- Value [21] Opinions
- Value [22] Comments
- Value [23] Top-Down Approaches
- Value [24] Bottom-Up Approaches
- Value [25] Human Behaviour
- Value [26] Tipping Points
- Value [27] Domino Effects
- Value [28] Collaborative Governance
- On collaborative governance, policy-making leverages collective intelligence and collective action. It accounts for the greater
policentricity of our governance system. While traditional tools are designed for the public decision-makers, these research
challenges are more symmetric by nature, in order to engage stakeholders all through the phases of the policy-making cycle.
Thanks to visualisation and design, it is able to reach out to new stakeholders and lower the barriers to entry in the policy
discussions. Policy-making 2.0 is not only designed to be more effective, but also more participatory.
- Value [29] Policy-Making
- Value [30] Collective Intelligence
- Value [31] Collective Action
- Value [32] Policentricity
- Value [33] Stakeholder Engagement
- Value [34] Visualisation
- Value [35] Design
- Value [36] Participation
- Value [37] Effectiveness
|
