Personal Data-Smart Cities: How cities can Utilise their Citizen’s Personal Data to Help them Become Climate Neutral

Front matter

River Publishers Series in Energy Sustainability and Efficiency

PERSONAL DATA-SMART CITIES

How Cities Can Utilise Their Citizen's Personal Data To Help Them Become Climate Neutral

Foreword

Preface Acknowledgements List of Contributors List of Figures

List of Tables

List of Abbreviations

Introduction Shaun Topham, Paolo Boscolo, Michael Mulquin

1 Peril on the Road to Utopia — Opportunities and Risks of Infusing Personal Data into the Smart City Ecosystem Haydee S. Sheombar and Joseph V. Sheombar 1.1 Introduction...

14 Think os ia at e eed oe hide ee Ale xiii vi

Contents

1.6.1 Scenariodrivers. ... cc. 1.6.2 Fourscenarios. es ecos soa e r a e a

Ana García Garre, John Kaldis and Elena Palmisano

2.1 ProjectOverviews. ... cc. 2.2 Data Valts n eee em e e ha e e a e 2.3 ARRAREN pare ha Get e act a Beem ane, dă 24- Sate-DEED e za ee Bee Ba a Pe eS 25°. DUET Project.) eee Y hore eWeek ok edt Se bao 21" RUGGEDISED a rotar Bald ee a BGO 2/8 ‘DataPorts x, i rr ds a le Add 2:11: AURORATD: e ar pe lo lo a oe aa ge is sr ale 212 REPEICATE și no Aa poi A oe a agata die ace 24S 213: PIMC A AS Be eS 214 :smash HIT ye le ee ete ee Ba WS eee Ae a 215 PolieyCloud . a ee ee e ee e 2.17 SmattEnCity macia e a Pe eS

Best Practice in the General Use of Data in a City Annina Autero, Michail Bourmpos, Iván Carrillo Quero,

Emanuele Geri, Hervé Groléas, Alisa Jashari, Christina N. Karaberi,

María Jose Lopez Osa, Sari Maenpaa, Esben Pejstrup,

Elena Palmisano, Fabio Pazzaglia and Minna Sapyska

34: Trikala GTEecE s s wo iona a o Bae ak 325° “Umea: Sweden see A ee

Contents Vii

3:9 “Athens; Greece: na e uk ate A es 58 3.10 City Health Organisations and the KRAKEN

Health Application... n 59 3:12, Piraeus, Greece: e ee oss a ke, Be Ghia Ue BIA Gh ASS 62 3:14 Prato, Italy). oc poe a Se ee Dae ees să 64 3:15 Filat, Israel! ii dow ee ae Doce oe te ds 65 3:16: Florence Taly are Ae poke Mob eed he oan de AS 66

Case Studies Involving the Use of Personal Data in a

Smart City 71 Paolo Boscolo, Michail Bourmpos, Ilesh Datani, Ana Garcia Garre, Vincent Keunen, Borja Molina-Rios, Elena Palmisano and

Christina Tsiligkiri

4.5 Olimpiacos: Athletes Sports and Activity Data Sharing. . . . 87 The Local Data Economy 97 Shaun Topham

Sel: Introduction a a ne a A ee ek 97 5.2: 13 MARREI. se aie oud eke SO E og ea A 101 5:3). AURORAL ig. di ete OP a Ob ae Bk i la 102 5:0: ‘Conclusions: Mk os ek bog ai i te ră Mal 108 Technical Components 111 Sotiris Koussouris and Yury Glikman

6:1) Introduction + oo oe. Ps ce Aw Sek he Sa ae 111 6.2 Data Owners and Subjects Controlling their Own Data... . 112

Vili

Contents

6.3 Preserving Data Privacy and Data Quality Simultaneously. . 6.3.7 Artificial intelligence threat reporting and response SYSTEMS ¿Ei A A ee a poi E 6.4 Information Delivery on Privacy Metrics and Data 6.4.1 Privacy metrics and risk management and 6.5.1 Secure and trusted data communication channels. . . 6.6.1 EUHUBS4DATA 0.0.0... ooo... o... 6:0:2 -Mý Data: rei rc a hie RO de ak

Interoperability and the Minimal Interoperability Mechanisms Michael Mulquin

Contents 1x

ES: "MIMSIPIUSA a aoe cee ad ehh ed oe Eels 148 8 Health Data in a Smart City 151 Vincent Keunen 9 Personal Data Management and MIM4 161 Michael Mulquin 92 MIMA es a al & BO a ini du 162 9.2.1 Capabilities . . eee e e 163 9.2.2. Requirements: si asd e erai ee ata ee i 165 10 Standards for Citizens 169 John Ketchell 10.1 Introduction . . cc 169 11 Business Models 175 Shaun Topham 11.1. Introduction. e a oe ge ce i pei ee ta a e da aa ră 175 11.3 Smart City Networks Creating Best Practice Repositories . . 178 11.4 SmartEnCity Project... cc 178

11.6 REPLICATE Project. crs re ae e p ee ee ac i 180

Xx Contents

11:7 IRIS Project... sta. temida ana fe ad a aa a ee 11.8 IRIS Study and the Smart City Business Model

11.9 REPLICATE Project. ne e ee ea at Aa 11:11: Safe-DEED 5.8 eg aos ule ts Bone de dă a aan 11.13 DUET Project... . cc 11.14 DataVaults Project. ... cc

11.151, „Assentian suite ds eae el are ea eae

11.17 Conclusions s s în beach a4 Mean Be ee ake ®

12 (Digital) City Financing Platforms Juergen Ritzek 12.3 But Who are These Digital Financing Platforms —

12,3.3- Re-financing: : soe pionu pdre e Rama a a 12.3.4 Challenge project pipeline: the chicken and 12.4 “Conclusión: +. loa ee a a ee Te d e

Research Insights and Recommendations

Marina Micheli 13:1 Introduction o.s o ri is, a a a 13.3 City Administrations’ Access to Personal Data of

Public: Interest... a ke ew Se ta A ara de

14 Data Valuation and Its Applications for Smart Cities Mihnea Tufis 14.1 Introduction...

Contents Xi

14.2.1 Data through an economic lens — trading data. . . 220 14.2.2 The price of personal data — a chaotic landscapes. coo a Se A ee ee Be e dt 222 142.3 Challenges defining the value of data — beyond financial value... 2... . 2... ee .. 225 15 Does Everything Conform to Legal, Ethical, and Data Protection Principles? 245 Marina Da Bormida in Cugurra 15:1.. Introduction. ini e ig SO ek Tata al a 245 15.2 The Evolving Regulatory Framework Relevant to the 15.5 Main Legal and Ethical Challenges and Technology-enabled 15.6 The Need to Avoid Consent Fatigue and to Develop and Use User- and Data-Protection-Friendly User Interface . . . 259 15.7 Risk-based Approach and Risk-Exposure Dashboard .... 263 15.9 Challenges Related to Smart Contracts, the eIDAS

15.10 DataVaults as a Flagship Initiative for Personal Data Sharing Under User Control and Benefitting All the Actors

15.11 Case Study: Approach and Legal and Ethical 15.11.1 Ethics and data protection impact assessment xii Contents

16 Data-Driven and Citizens” Inclusive Smart Cities: Top-Down and Bottom-Up Approaches to Tackle Societal and Climate Challenges 283 Maria Sangiuliano

16.2 Sharing and Networking on Citizen Engagement in Europe. Resources and Lessons Learnt from the Citizen Focus Action Cluster of the Smart Cities Marketplace . . . . 284 16.3 Good Practices. Citizen Generated Data to Improve Urban Innovation and Smart Cities Policies. Top-Down 16.3.1 Harnessing open data for evidence-based urban 16.3.2 Crowdsourced data for enhancing safety perception 16.4 Envisioning the Future of Citizens” Intelligent Cities and 17 What Next? 299

Paolo Boscolo, Michael Mulquin and Shaun Topham

17.1 Moving Towards a European Model for the Data Economy . 299 17.8 Interoperability ... cc 308 179: Legality tada cure mă unt yg aa dos Weare Ad 309 Index 313 About the Contributors 321

About the Editors 327

Foreword

Johan Bodenkamp, Policy and Programme Officer at the European Commission, and DataVaults Project Officer

It is widely acknowledged that data has an enormous potential to contribute to better-informed decisions and to create new services and products for the benefit of all.

Every day, we generate an unprecedented amount of data, which is increasingly harvested and used to foster innovation and sustainable economic growth as well as to improve the overall wellbeing of society. Despite the current sanitary, economic, and geopolitical context, studies confirm this positive trend in the data economy. Having reached 440 billion euros in 2021, the latest European Data Market Study! estimates that the value of the EU27 data economy will reach 600 billion euros in 2025 and 1 trillion euros in 2030. It is, therefore, not surprising that stakeholders regularly refer to data as the new oil or electricity of our modern society.

The EU is fully committed to setting a framework to help ensure that the benefits of the ongoing data revolution are fully reaped. To this end, the European data strategy” aims to make the EU a leader in a data-driven society and to create a single European data space. This space would be a genuine European single market for data, open to data from across the world, in which an almost infinite amount of high-quality personal and non-personal data is secure and can be used in an ethical and trusted way to create value and boost growth, while minimising the environmental footprint related to its use.

To create the right conditions and gradually realise this bold vision for Europe, ambitious legislative, research, innovation, and deployment actions at EU and national level are underway. In particular, the recently adopted Data Governance Act? and the proposed Data Act“ are key EU legislative measures to enhance data availability and use in line with EU rules and values.

Despite this positive trend, the use and sharing of personal data is still limited. This is partly due to hesitations on how to benefit from such sensitive data in a trusted and secure way, ensuring respect of data protection legislation and allowing data subjects and data holders to remain in control of their xiii xiv Foreword data and its use. Fortunately, several EU-funded and national projects, some of which have been actively involved in the preparation of this work, concretely show how this can be done through the use of appropriate secure and privacy-preserving techniques.

This book provides valuable insights into how smart cities could use citizens’ personal data in a trusted and ethical way. It makes it an extremely useful source of information for city and municipal staff as well as for other interested stakeholders.

The hope is that it will inspire smart cities to engage more actively in using relevant data, and in particular citizens’ personal data, to support important local policy objectives, notably to become climate neutral as quickly as possible.

Brussels, July 20 2022

Preface

This book was produced in order to help grow a data economy in Europe, which reflects European values. It is argued that by adding a citizen's personal data, under their own control, to current and developing use of data in a smart city, a major contribution can be made to realising the ambition of many European cities of becoming carbon-neutral by 2030. And further, to contribute to building a mechanism for replicating the lessons which will be learned as cities utilise personal data and progress towards achieving both their environmental and smart city targets.

XV

Acknowledgements

BI | | Commission

An initiative of the Smart Cities +EUSmartCities Marketplace

Funded by the European Union

The 16 projects listed below have all received funding from the European Union's Horizon 2020 research and innovation programme under the respective Grant Agreements indicated.

“E DataVaults DataVaults This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871755

== EUHubs4Data project has received funding

— LI H q from the European Union's H2020 Research and Innovation Programme under the Grant Agreement No. 951771.

e ~ KRAKEN is a project which has received ig KRAKEN funding from the European Union’s Horizon

2020 (H2020) research and innovation programme under the Grant Agreement No. 871473.

xvil xviii Acknowledgements

DataPorts project has received fundin [r] DataPorts NE a s from the European Union’s Horizon 2020

ata Platform for the ,

Connection of Cognitive Ports Research and Innovation Programme under Grant Agreement No. 871493.

IS = ET) Safe-DEED is a project which has received e funding from the European Union's Horizon2020 research and innovation programme under grant agreement No. 825225.

Replicate project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 691735.

Ie ly lh

A | m y = : = m

RUGGEDISED is a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 731198.

RUGGE

Designing smart, resilient cities for all

PIMCity project has received funding from M the European Union Horizon 2020 Research and Innovation programme under the ICT e | theme: ICT-13-2018-2019 Grant Agreement No. 871370.

InteropEHRate project has received fund- | nt e rop a H R ate ing from the European Union’s Horizon | 2020 research and innovation programme EHR in people's hands across Europe under grant agreement No. 826106.

eee eee

SmashHit project has received funding Pe: from the European Union's Horizon 2020 research and innovation programme under

smashHit Grant Agreement No. 871477.

DUET is a project has received financial &, support from the European Union’s Horizon D U E T 2020 Programme under grant agreement No.

870697.

Acknowledgements Xix

PolicyCloud has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 870675.

Policy Cloud

Cloud for Data-Driven Policy Management i3-Market project is funded by the European Union's H2020 Research and Innovation Programme under the Grant Agreement No. 871754 (13-MARKET).

i3-MARKET te c IRIS project has received funding from the qe Son . .

E pă | R | fado] European Union's Horizon 2020 research Y integrated and Replicable Solutions : : are: Groocestoninsustenaecees and innovation programme under grant agreement No. 774199.

© Auroral project has received funding from AURORALN\- the European Union’s Horizon 2020 research and Innovation Programme under grant agreement No. 101016854.

SmartenCity project has received funding

smar- i

en from the European Union’s Horizon 2020 C ly research and innovation programme under grant agreement No. 691883

Major Cities of Europe:

Major Cities of Europe is a European independent organisation of local government CIOs, heads of departments, and policy-makers. They co-operate with academia, public and private organisations focused in that domain. They promote the development of new services for citizens and local businesses. They facilitate

MAJOR CITIES OF EUROPE š r . ap exchanges of strategies, experiences, ideas, and

IT USERS GROUP

5 https://www.majorcities.eu/ p y xx Acknowledgements solutions for the use of information and communication technology. Many of their members are also amongst those 100 cities selected by the Commission to lead, in becoming climate-neutral by 2030.

Open & Agile Smart Cities®

L Open and Agile Smart Cities bring together OAIGI® smart cities and communities worldwide to

ON A shape the global market for digital services. It OPEN & AGILE SMART CITIES is a network that connects cities and communities worldwide to learn from each other and exchange digital, data-driven solutions based on minimal interoperability mechanisms (MIMs). They are creating sustainable impact for their member cities by working towards a common technical ground for cities and communities — based on open standards, open APIs, and shared data models. As with Major Cities, many members are seeking to be climate-neutral by 2030.

Disclaimer

The information and views set out in this publication are those of the author(s) and do not necessarily reflect the official opinion of the European Communities. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein.

We can confirm that there are no conflicts of interest to report.

6 https://oascities.org/

List of Contributors

Alisa Jashari, Tampere, Finland

Ana García Garre, MIWenergia, Spain

Amnina Autero, SURE Project, Tampere, Finland Borja Molina-Ríos, MIWenergia, Spain

Christina N. Karaberi, e-trikala — Department of Research and Communication, Trikala, Greece

Christina Tsiligkiri, Olympiacos SFP, Pireas, Greece,

Elena Palmisano, Comune di Prato, Italy

Elena Palmisano, PIN, Prato, Italy

Emanuele Geri, Information Systems Directorate, City of Florence, Italy Esben Pejstrup, ICLEI, Germany

Fabio Pazzaglia, Information Systems Directorate, City of Florence, Italy

Haydee S. Sheombar, Founder Kankan*Tree, Research Affiliate, Erasmus University Rotterdam, Netherlands

Hervé Groléas, Chief Digital and Information Officer, Grand Lyon, France Ilesh Datani, Assentian, Ireland

Ivan Carrillo Quero, ATOS, Spain,

John Kaldis, Unisystems, Greece

John Ketchell, European Association for Coordinating Consumer Representation in Standardisation (ANEC)

Joseph V. Sheombar, Master Student Built Environment, Delft University of Technology, Netherlands

Juergen Ritzek, EEIP, Brussels, Belgium Maria Sangiuliano, Research Director, Smart Venice, Venice, Italy

Marina Da Bormida in Cugurra, Genoa, Italy

XXI xxii List of Contributors

Marina Micheli, Scientific Project Officer, Digital Economy Unit, European Commission’s Joint Research Centre (JRC), Ispra, Italy

Maria Jose Lopez Osa, Tecnalia, Spain Michael Mulquin, MIMs Ambassador, Open & Agile Smart Cities Michail Bourmpos, /T Department, City of Piraeus, Greece

Mihnea Tufis, Eurecat Technology Center of Catalunya, Carrer de Bilbao, Barcelona

Minna Sapyska, Tampere, Finland Paolo Boscolo, Comune di Prato, Italy Sari Maenpaa, Insta, Finland

Shaun Topham, Lead, EU Smart Cities Marketplace, “Citizen’s Control of Data” Initiative

Sotiris Koussouris, Suite5, Cyprus Vincent Keunen, Andaman7, Belgium

Yury Glikman, Fraunhofer, Germany

Figure 1.1 Figure 1.2

Figure 1.3 Figure 1.4 Figure 1.5 Figure 1.6 Figure 7.1 Figure 7.2 Figure 7.3 Figure 7.4 Figure 8.1 Figure 9.1 Figure 13.1 Figure 13.2 Figure 14.1 Figure 14.2

Figure 14.3

List of Figures

A smart city as a bounded “system of systems”. . . . 7 The Urban Data Platform, personal data vaults and

the smart city ecosystem (based on RUGGEDISED). 8 A citizen journey reveals points of sensing and

Reasons for companies and companies to engage

What is the impact of personal data on individuals

and’ on:the City? wei ve hee bok ce oe hee ae dania 17 The future impact of personal data (vaults) in terms

of four scenarios. o co s ecra oa i 20 Summary of emerging data governance models.

Summary of the approaches adopted by local administrations to access private sector data of public

A ui sist se Rd, Aa dee wit of 210 Data value network as illustrated by Attard et al.. . . 227 Overview of the components of the data valuation

The aggregation of the scores generated from the different sub-components of the DVC into the data xxiii xxiv List of Figures

Figure 14.4 Data value scorecard. A combined view over the general data quality score and its composing data quality metrics... 2... ee a ee.

Figure 14.5 Data value scorecard. A multi-dimensional view of

Table 1.1

Table 7.1

List of Tables

Highlights of both the negative and the positive impact MIMS: 1-10. aise oi ce aint anit Bd pa ca aia 0

XXV

List of Abbreviations

ABAC Attribute-based access control

ABE Access-based enumeration

AI Artificial intelligence

API Application programming interface

CERTs Computer emergency response (or readiness) team CIM City innovation models

CRUD Create, read, update, and delete

CSIRT Computer security incident response team DGA Data governance act

DLT Distributed ledger technology

DMA. Digital markets act

DQA Data quality assessment

DQD Data quality dimension

DQM Data quality metric

DSA Digital services act

DVC Data valuation component

DVP Data valuation process

EEA European economic area

eIDAS Electronic identification, authentication and trust services EOSC European open science cloud

ESCO Energy service company

EU European union

FAIR Findable-accessible-interoperable-reusable GDPR The general data protection regulation

GIS Geographic information system

GPS Global positioning system

HMRC Her majesty’s revenue and customs service ICT Information and communications technology IoT Internet of things xxvii xxviii List of Abbreviations

ITU JRC MIM NSO PDV PIMS PSI PV R&D SME SSI TPM UDP USD VAT WIMAX

International telecommunication union Joint research centre

Minimal interoperability mechanisms National statistics organisation

Personal data vault

Privacy information management system Public sector information

Photovoltaics

Research and development

Small- and medium-sized enterprise Self-sovereign identity

Trusted platform module

Urban data platform

United states dollar

Value added tax

Worldwide interoperability for microwave access