In the transformations process towards Smart Cities urban data is becoming increasingly important as a basis for public services and urban development. Though intelligent use of data opens the path towards overcoming social inequality, increasing efficiency of public services and public value creation as well as making public investments more profitable, the urban data market today is still in the exploratory phase and there are no universal approaches enabling cities to fully understand the potential of urban data for sustainable and smart urban development. In addition, there is lack of comprehensive city databases and suitable and efficient data-driven business models for Smart Cities operation.
The project focuses on identifying the greater value of urban datasets and transforming it into pricing and investment schemes. It is aimed at municipalities that are determined to pursue measurable progress in exploring new funding models, utilising the maximum potential of data, while capturing its value, grasping the benefits of Smart City insurance and repositioning digital governance approaches. At the same time, the research is important to financial, banking and insurance institutions that are seeking to invest in sustainable and innovative urban projects, while striving to improve their portfolio of products by better suiting the current demand of cities. It also addresses companies, which want to better understand the value of their own data sets for cities, ways to monetize them and integrate in larger urban development projects.
The approximate duration is 2 years. The project is based on a joined funding model:
The proposed research is aiming to provide in-depth insight into the untapped potential that lies within Smart City data. Moreover, the research will attempt to help cities develop the right balance between monetisation for value and monetisation for creating an equitable data market place. The research will focus on the complexities of the value of data and will develop the following deliverables:
An overview and description of data-based use cases for cities (both holistic data platforms as well as already well-functioning business models)
The joint platform for sharing data and understanding values and impacts will be set-up and operated through Fraunhofer IAO and Fraunhofer FOKUS. The Morgenstadt joint-up research project is based on the following six work packages, which are coordinated and managed by the Fraunhofer IAO team.
Ensuring thorough identification and collection of all the relevant data sets. Further, a pilot platform will be developed to enable the comparable and usable data to be located and subsequently managed at once place. Partners will be invited to provide their own data to a secure project platform.
The partner cities of London, Amsterdam, Berlin, Copenhagen and Dublin developing cutting-edge strategies and approaches towards efficient urban data management and usage will be approached in order to set out potential data use cases that would unlock significant shared value. Facilitated by research additional use cases will be identified and described.
In this work package, the identified data sets will be adjusted to the needs and requirements of the particular use-cases within each of the cities. Furthermore, the data will be refined within each of the data sets to ensure their full usability and impact potential.
A data evaluation model will be developed in order to assess the various value streams stemming from the data. Value creation areas associated with the use-cases will also be identified and recommended for follow-up. In addition, the potential for trading and exchange of data (with a focus on prospective monetisation) will be reflected in the model.
The different costs and benefits of data refinement, interpretation and application will be quantified and qualified. Key barriers to the usage of urban data within the respective cities will be clearly defined and recommendations for overcoming those will be provided.
A price modelling with a focus on the monetary value of data will be performed. Data value capture and relevant instruments will also be recommended to make sure that the value of data is territorially bound, while increasing local competitiveness.
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Petr Suska (Petr.email@example.com)