Vision

Make the most out of data
Prepare the data and make it usable with the URBANITE data curation components: data quality checks, transform unstructured information into high quality data sets, address privacy issues with anonymization and pseudonymization, guarantee data interoperability.

Make the data management process more efficient
Handle the entire process: fetch data from various heterogenous sources , transform, fuse and map it and store it in dedicated databases ready for its use.

Learn from short- intermediate- and long-term trends to improve urban mobility
e.g. learn from the trends of peak hours in which a street is blocked or from the use of a certain transportation system (bikes, public transport, taxi etc.). Data analysis results will be visualized to show traffic density, traffic flows, points of interest etc.

Anticipate behaviours and delimit unforeseen consequences
Simulate the effect of different traffic situations (through the use of artificial intelligence algorithms), e.g. simulate the effect of opening a pedestrian street at certain times, of locating electric charging stations or bike sharing points in certain areas.

Identify potentially problematic or otherwise important events
These events would have a high price if discovered in the real life. Identify events with cutting edge detection methods and validate mobility policies in a virtual environment with simulation techniques

Create public policies and services “with” people and not just “for” them.
Put people at the centre of urban mobility policy making, making sure policies are based on shared values and principles and address effective needs of the citizens and relevant stakeholders.

Foster cross-departmental collaboration by creating an urban ecosystem
Optimize urban management by involving public administrations, private transport companies and citizens.

Boost and guide an efficient and successful digital transformation
Get guidance on the adoption and implementation of big data, artificial intelligence and algorithms in urban mobility decision making

• Find unmet needs – participants in the co-creation activities can suggest, report or vote needs and social/local issues and bring them to the attention of policy makers.
• Support idea generation - supports Public Administrations in the collection of spontaneous and guided ideas with an always-on and wherever available digital tool.
• Support co-creation workshops - enter documentation and any information useful for the running of the workshop and enter ideas generated during the workshop to continue idea generation and evaluation online.
• Resource sharing - different kinds of resources are available such as policy briefings, multimedia content, methodologies, best practices that can support the successful application of co-creation activities and the use of disruptive technologies.
• Keep track of the whole co-creation process - it provides the full history of ideas, accompanying documentation, evaluations and voting.
• Select the best ideas together with all the stakeholders involved through idea voting and idea management.
• Keep the community updated, improve transparency on the whole co-creation process boost satisfaction, collaboration and engagement.

• Data harvesting i.e. fetching data from various heterogenous sources, transformation and mapping of data and metadata, and storing them in dedicated databases.
• Data curation (preparation) - before the actual publication i.e. data quality checks, data transformation and annotation, data anonymization and pseudonymization.
• Data aggregation and storage i.e. storage of data and its semantic description (metadata), aggregation and deduplication of the data that originates from distinct sources and retrieval of the stored data via a provided API.

• Big Data analysis methods;
• Intuitive and understandable visualizations;
• Traffic simulations of both current situation and hypothetical situations (traffic density, traffic flows, points of interest etc.);
• Presentation of different proposals of action to choose from during the decision–making processes;
• Detection/Prediction of potentially problematic or important events;
• Validation of mobility policies through predictions and simulations.

• Guidance on what to do and what not to do in the use of disruptive technologies for decision–making processes.
• Tailored to the context and the needs of public administrations, co-created with civil servants addressing their specific needs and doubts.
• Details on benefits, risks and potential of the disruptive technologies in the mobility sector (big data, artificial intelligence, cloud computing, algorithms).
• Attitude of civil servants towards the use of new and disruptive technologies (big data, artificial intelligence, cloud computing, algorithms).
• Level of trust of citizens and other stakeholders as a result of the use of a wide spectrum of disruptive technologies.
• Lessons learnt, recommendations and best practices from the application of disruptive technologies in different domains, beyond mobility and urban transformation.
• Suggestions on tool and techniques to use in co-creation sessions.