# Data as Infrastructure for Smart Cities: Linking Data Platforms to Business Strategies

**Authors:** Larissa Romualdo-Suzuki, Anthony Finkelstein  
**arXiv:** [2005.11414](https://arxiv.org/abs/2005.11414)  
**Date:** 2020-05-22  
**Summary page:** https://www.summarizepaper.com/en/arxiv-id/2005.11414v1/

## Key points

- Fragmented nature of city infrastructure systems
- Potential for integrating cross-domain city data to create smarter cities
- Limitations of current smart cities initiatives, focusing on technology and overlooking stakeholder input and data needs
- Proposal of a business-model-driven framework for designing large and interconnected data infrastructures supported by multiple stakeholders
- Consideration of aspects such as service, technology, organization, value, and governance requirements in the framework
- Use of exemplary scenarios and decision-making processes to design data infrastructures
- Sub-scale pilots/demonstrators and examples of fragmented and "deprived" data re-use provide further context
- Discussion on two prevailing approaches in the provision of city data and sample of London's city data landscape
- Emphasis on integrated approaches adopting local, national, and international standards for effective implementation of data infrastructures
- Importance of establishing a Data-Driven Value Network (DDVN) in the organization domain
- Categorization of stakeholders into platform keystone, structural partners, contributing partners, and supporting partners based on their power within the value network
- Information on architecture aspects of different datasets in terms of structure, real-time capabilities, and architecture type.

## Summary

The existing summary discusses the fragmented nature of city infrastructure systems and the potential for integrating cross-domain city data to create smarter cities. However, it also highlights the limitations of current smart cities initiatives, which mainly focus on technology and overlook stakeholder input and data needs. To address these issues, the paper proposes a business-model-driven framework for designing large and interconnected data infrastructures supported by multiple stakeholders. This framework considers various aspects such as service, technology, organization, value, and governance requirements. The paper demonstrates how this approach can be used to design data infrastructures through exemplary scenarios and decision-making processes. In addition to the existing summary, there is further context provided in the form of sub-scale pilots/demonstrators and examples of fragmented and "deprived" data re-use. The paper also discusses two prevailing approaches in the provision of city data and presents a sample of London's city data landscape. It emphasizes that integrated approaches adopting local, national, and international standards are necessary for implementing data infrastructures effectively. Furthermore, it highlights the importance of establishing a value network called a Data-Driven Value Network (DDVN) in the organization domain. This network consists of various actors with their own strategies, goals, resources, capabilities, influence, and requirements. These actors' value activities are orchestrated in a value chain that enables co-opetition in providing city data and services while fostering innovation and value creation. The paper categorizes stakeholders into four basic types: platform keystone, structural partners, contributing partners,
and supporting partners based on their power within the value network. It also provides information on the architecture aspects of different datasets in terms of structure (semi-structured or structured), real-time capabilities (near-real-time or non-real-time), and architecture type. Overall,this refined detailed longer summary provides a comprehensive overview of the paper's content by incorporating additional context from sub-scale pilots/demonstrators to London's city data landscape and discussing the importance of standards, value networks, and stakeholder roles in designing data infrastructures for smarter cities.