The Data Shake : : Opportunities and Obstacles for Urban Policy Making.

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Place / Publishing House:Cham : : Springer International Publishing AG,, 2021.
©2021.
Year of Publication:2021
Edition:1st ed.
Language:English
Series:SpringerBriefs in Applied Sciences and Technology Series
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spelling Concilio, Grazia.
The Data Shake : Opportunities and Obstacles for Urban Policy Making.
1st ed.
Cham : Springer International Publishing AG, 2021.
©2021.
1 online resource (134 pages)
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
SpringerBriefs in Applied Sciences and Technology Series
Intro -- Preface -- Contents -- Editors and Contributors -- About the Editors -- Contributors -- Part IThe Data Shake: Open Questions and Challenges for Policy Making -- 1 The Data Shake: An Opportunity for Experiment-Driven Policy Making -- 1.1 Introduction -- 1.2 Evidence-Based Policy Making: New Chances Coming from the Data Shake -- 1.2.1 About Evidence-Based Policy Making -- 1.2.2 Evidence-Based Policy Making and the Data Shake: The Chance for Learning -- 1.3 The Smart Revolution of Data-Driven Policy Making: The Experimental Perspective -- 1.3.1 About Policy Experiments and Learning Cycles -- 1.3.2 Policy Cycle Model Under Experimental Dimension -- 1.3.3 The Time Perspective in the Experimental Dimension of Policy Making -- 1.4 Conclusions: Beyond the Evidence-Based Model -- References -- 2 Data Ownership and Open Data: The Potential for Data-Driven Policy Making -- 2.1 Introduction and Context -- 2.1.1 From Smart City to Data City -- 2.1.2 Exploring the Cities' Points of View -- 2.2 Challenges and Questions Related to (Open) Data Policies -- 2.2.1 Data Hygiene in the Organization -- 2.2.2 IoT and Open Data -- 2.2.3 Centralization vs Decentralization -- 2.2.4 Government and the Market -- 2.2.5 Open Data Checklist -- 2.3 Data and Procurement -- 2.3.1 Examples of Model Clauses -- 2.4 Discussion and Conclusion -- References -- 3 Towards a Public Sector Data Culture: Data as an Individual and Communal Resource in Progressing Democracy -- 3.1 The Balance of a Data-Driven Democracy -- 3.2 The Conflicting Logics of Emerging Public Sector Data Cultures -- 3.3 The Project Democracy Data-Lessons on Cultivating Local Data Culture from the Swedish Social Services -- 3.3.1 Proposals 1: Promote Holistic Data-Literacy -- 3.3.2 Proposals 2: Design Your Data-Driven Services as if Democracy Depended on It (Because It Does).
3.3.3 Proposals 3: Conceptualize Data as Democratic Artifact -- References -- 4 Innovation in Data Visualisation for Public Policy Making -- 4.1 Introduction: Data Visualisation Between Decision Support and Social Influence -- 4.2 Scoping the Experiences of Data Scientists -- 4.2.1 Multiple Data Source Management -- 4.2.2 Rigorous Data Integration -- 4.2.3 Actionable Information Delivery -- 4.2.4 Personalised User Experience -- 4.3 A Critical Eye on Technology Innovation Trends -- 4.4 Conclusions and Way Forward -- References -- Part IIThe PoliVisu Project -- 5 Policy-Related Decision Making in a Smart City Context: The PoliVisu Approach -- 5.1 Evidence-Based Policy Making and the Rise of ICT -- 5.2 ICT-Enabled Policy Making in a Smart City Context -- 5.3 The Unique Characteristics of the PoliVisu Approach -- 5.4 Barriers and Limitations to the Full Exploitation of Data Potential in Policy Making -- 5.5 Conclusion -- References -- 6 Turning Data into Actionable Policy Insights -- 6.1 Introduction -- 6.2 Policy Making Supported by Data -- 6.2.1 Policy Design -- 6.2.2 Policy Implementation -- 6.2.3 Policy Evaluation -- 6.3 Policy-Oriented Data Activities -- 6.3.1 Differentiating Roles and Competences -- 6.3.2 Balancing Flexibility and Usability -- 6.3.3 Transforming Iterations into Experimental Drivers -- 6.4 Conclusions -- References -- 7 Data-Related Ecosystems in Policy Making: The PoliVisu Contexts -- 7.1 Introduction -- 7.2 The PoliVisu Project as a Testbed for Digital Innovation -- 7.3 Actors and Roles in Data-Related Policy Making Ecosystems -- 7.4 Data-Related Relations -- 7.5 Conclusion: Dealing with Complexity in the Era of the Data Shake -- References -- 8 Making Policies with Data: The Legacy of the PoliVisu Project -- 8.1 Data Supported Policy Making Through the Eyes of the PoliVisu Pilots -- 8.1.1 Data for Dialogue.
8.1.2 Between Precision and Usability -- 8.1.3 Proneness to Iterative Process -- 8.1.4 Actors Involved in Data Supported Policy Making -- 8.2 Bottlenecks and New Practices Detected in Policy Making -- 8.2.1 Bottlenecks -- 8.2.2 New Practices and Knowledge -- 8.3 Conclusions -- 8.3.1 Lessons Learnt from the PoliVisu Project -- 8.3.2 Some Recommendations -- References -- Acknowledgments.
Description based on publisher supplied metadata and other sources.
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
Electronic books.
Pucci, Paola.
Raes, Lieven.
Mareels, Geert.
Print version: Concilio, Grazia The Data Shake Cham : Springer International Publishing AG,c2021 9783030636920
ProQuest (Firm)
https://ebookcentral.proquest.com/lib/oeawat/detail.action?docID=6511378 Click to View
language English
format eBook
author Concilio, Grazia.
spellingShingle Concilio, Grazia.
The Data Shake : Opportunities and Obstacles for Urban Policy Making.
SpringerBriefs in Applied Sciences and Technology Series
Intro -- Preface -- Contents -- Editors and Contributors -- About the Editors -- Contributors -- Part IThe Data Shake: Open Questions and Challenges for Policy Making -- 1 The Data Shake: An Opportunity for Experiment-Driven Policy Making -- 1.1 Introduction -- 1.2 Evidence-Based Policy Making: New Chances Coming from the Data Shake -- 1.2.1 About Evidence-Based Policy Making -- 1.2.2 Evidence-Based Policy Making and the Data Shake: The Chance for Learning -- 1.3 The Smart Revolution of Data-Driven Policy Making: The Experimental Perspective -- 1.3.1 About Policy Experiments and Learning Cycles -- 1.3.2 Policy Cycle Model Under Experimental Dimension -- 1.3.3 The Time Perspective in the Experimental Dimension of Policy Making -- 1.4 Conclusions: Beyond the Evidence-Based Model -- References -- 2 Data Ownership and Open Data: The Potential for Data-Driven Policy Making -- 2.1 Introduction and Context -- 2.1.1 From Smart City to Data City -- 2.1.2 Exploring the Cities' Points of View -- 2.2 Challenges and Questions Related to (Open) Data Policies -- 2.2.1 Data Hygiene in the Organization -- 2.2.2 IoT and Open Data -- 2.2.3 Centralization vs Decentralization -- 2.2.4 Government and the Market -- 2.2.5 Open Data Checklist -- 2.3 Data and Procurement -- 2.3.1 Examples of Model Clauses -- 2.4 Discussion and Conclusion -- References -- 3 Towards a Public Sector Data Culture: Data as an Individual and Communal Resource in Progressing Democracy -- 3.1 The Balance of a Data-Driven Democracy -- 3.2 The Conflicting Logics of Emerging Public Sector Data Cultures -- 3.3 The Project Democracy Data-Lessons on Cultivating Local Data Culture from the Swedish Social Services -- 3.3.1 Proposals 1: Promote Holistic Data-Literacy -- 3.3.2 Proposals 2: Design Your Data-Driven Services as if Democracy Depended on It (Because It Does).
3.3.3 Proposals 3: Conceptualize Data as Democratic Artifact -- References -- 4 Innovation in Data Visualisation for Public Policy Making -- 4.1 Introduction: Data Visualisation Between Decision Support and Social Influence -- 4.2 Scoping the Experiences of Data Scientists -- 4.2.1 Multiple Data Source Management -- 4.2.2 Rigorous Data Integration -- 4.2.3 Actionable Information Delivery -- 4.2.4 Personalised User Experience -- 4.3 A Critical Eye on Technology Innovation Trends -- 4.4 Conclusions and Way Forward -- References -- Part IIThe PoliVisu Project -- 5 Policy-Related Decision Making in a Smart City Context: The PoliVisu Approach -- 5.1 Evidence-Based Policy Making and the Rise of ICT -- 5.2 ICT-Enabled Policy Making in a Smart City Context -- 5.3 The Unique Characteristics of the PoliVisu Approach -- 5.4 Barriers and Limitations to the Full Exploitation of Data Potential in Policy Making -- 5.5 Conclusion -- References -- 6 Turning Data into Actionable Policy Insights -- 6.1 Introduction -- 6.2 Policy Making Supported by Data -- 6.2.1 Policy Design -- 6.2.2 Policy Implementation -- 6.2.3 Policy Evaluation -- 6.3 Policy-Oriented Data Activities -- 6.3.1 Differentiating Roles and Competences -- 6.3.2 Balancing Flexibility and Usability -- 6.3.3 Transforming Iterations into Experimental Drivers -- 6.4 Conclusions -- References -- 7 Data-Related Ecosystems in Policy Making: The PoliVisu Contexts -- 7.1 Introduction -- 7.2 The PoliVisu Project as a Testbed for Digital Innovation -- 7.3 Actors and Roles in Data-Related Policy Making Ecosystems -- 7.4 Data-Related Relations -- 7.5 Conclusion: Dealing with Complexity in the Era of the Data Shake -- References -- 8 Making Policies with Data: The Legacy of the PoliVisu Project -- 8.1 Data Supported Policy Making Through the Eyes of the PoliVisu Pilots -- 8.1.1 Data for Dialogue.
8.1.2 Between Precision and Usability -- 8.1.3 Proneness to Iterative Process -- 8.1.4 Actors Involved in Data Supported Policy Making -- 8.2 Bottlenecks and New Practices Detected in Policy Making -- 8.2.1 Bottlenecks -- 8.2.2 New Practices and Knowledge -- 8.3 Conclusions -- 8.3.1 Lessons Learnt from the PoliVisu Project -- 8.3.2 Some Recommendations -- References -- Acknowledgments.
author_facet Concilio, Grazia.
Pucci, Paola.
Raes, Lieven.
Mareels, Geert.
author_variant g c gc
author2 Pucci, Paola.
Raes, Lieven.
Mareels, Geert.
author2_variant p p pp
l r lr
g m gm
author2_role TeilnehmendeR
TeilnehmendeR
TeilnehmendeR
author_sort Concilio, Grazia.
title The Data Shake : Opportunities and Obstacles for Urban Policy Making.
title_sub Opportunities and Obstacles for Urban Policy Making.
title_full The Data Shake : Opportunities and Obstacles for Urban Policy Making.
title_fullStr The Data Shake : Opportunities and Obstacles for Urban Policy Making.
title_full_unstemmed The Data Shake : Opportunities and Obstacles for Urban Policy Making.
title_auth The Data Shake : Opportunities and Obstacles for Urban Policy Making.
title_new The Data Shake :
title_sort the data shake : opportunities and obstacles for urban policy making.
series SpringerBriefs in Applied Sciences and Technology Series
series2 SpringerBriefs in Applied Sciences and Technology Series
publisher Springer International Publishing AG,
publishDate 2021
physical 1 online resource (134 pages)
edition 1st ed.
contents Intro -- Preface -- Contents -- Editors and Contributors -- About the Editors -- Contributors -- Part IThe Data Shake: Open Questions and Challenges for Policy Making -- 1 The Data Shake: An Opportunity for Experiment-Driven Policy Making -- 1.1 Introduction -- 1.2 Evidence-Based Policy Making: New Chances Coming from the Data Shake -- 1.2.1 About Evidence-Based Policy Making -- 1.2.2 Evidence-Based Policy Making and the Data Shake: The Chance for Learning -- 1.3 The Smart Revolution of Data-Driven Policy Making: The Experimental Perspective -- 1.3.1 About Policy Experiments and Learning Cycles -- 1.3.2 Policy Cycle Model Under Experimental Dimension -- 1.3.3 The Time Perspective in the Experimental Dimension of Policy Making -- 1.4 Conclusions: Beyond the Evidence-Based Model -- References -- 2 Data Ownership and Open Data: The Potential for Data-Driven Policy Making -- 2.1 Introduction and Context -- 2.1.1 From Smart City to Data City -- 2.1.2 Exploring the Cities' Points of View -- 2.2 Challenges and Questions Related to (Open) Data Policies -- 2.2.1 Data Hygiene in the Organization -- 2.2.2 IoT and Open Data -- 2.2.3 Centralization vs Decentralization -- 2.2.4 Government and the Market -- 2.2.5 Open Data Checklist -- 2.3 Data and Procurement -- 2.3.1 Examples of Model Clauses -- 2.4 Discussion and Conclusion -- References -- 3 Towards a Public Sector Data Culture: Data as an Individual and Communal Resource in Progressing Democracy -- 3.1 The Balance of a Data-Driven Democracy -- 3.2 The Conflicting Logics of Emerging Public Sector Data Cultures -- 3.3 The Project Democracy Data-Lessons on Cultivating Local Data Culture from the Swedish Social Services -- 3.3.1 Proposals 1: Promote Holistic Data-Literacy -- 3.3.2 Proposals 2: Design Your Data-Driven Services as if Democracy Depended on It (Because It Does).
3.3.3 Proposals 3: Conceptualize Data as Democratic Artifact -- References -- 4 Innovation in Data Visualisation for Public Policy Making -- 4.1 Introduction: Data Visualisation Between Decision Support and Social Influence -- 4.2 Scoping the Experiences of Data Scientists -- 4.2.1 Multiple Data Source Management -- 4.2.2 Rigorous Data Integration -- 4.2.3 Actionable Information Delivery -- 4.2.4 Personalised User Experience -- 4.3 A Critical Eye on Technology Innovation Trends -- 4.4 Conclusions and Way Forward -- References -- Part IIThe PoliVisu Project -- 5 Policy-Related Decision Making in a Smart City Context: The PoliVisu Approach -- 5.1 Evidence-Based Policy Making and the Rise of ICT -- 5.2 ICT-Enabled Policy Making in a Smart City Context -- 5.3 The Unique Characteristics of the PoliVisu Approach -- 5.4 Barriers and Limitations to the Full Exploitation of Data Potential in Policy Making -- 5.5 Conclusion -- References -- 6 Turning Data into Actionable Policy Insights -- 6.1 Introduction -- 6.2 Policy Making Supported by Data -- 6.2.1 Policy Design -- 6.2.2 Policy Implementation -- 6.2.3 Policy Evaluation -- 6.3 Policy-Oriented Data Activities -- 6.3.1 Differentiating Roles and Competences -- 6.3.2 Balancing Flexibility and Usability -- 6.3.3 Transforming Iterations into Experimental Drivers -- 6.4 Conclusions -- References -- 7 Data-Related Ecosystems in Policy Making: The PoliVisu Contexts -- 7.1 Introduction -- 7.2 The PoliVisu Project as a Testbed for Digital Innovation -- 7.3 Actors and Roles in Data-Related Policy Making Ecosystems -- 7.4 Data-Related Relations -- 7.5 Conclusion: Dealing with Complexity in the Era of the Data Shake -- References -- 8 Making Policies with Data: The Legacy of the PoliVisu Project -- 8.1 Data Supported Policy Making Through the Eyes of the PoliVisu Pilots -- 8.1.1 Data for Dialogue.
8.1.2 Between Precision and Usability -- 8.1.3 Proneness to Iterative Process -- 8.1.4 Actors Involved in Data Supported Policy Making -- 8.2 Bottlenecks and New Practices Detected in Policy Making -- 8.2.1 Bottlenecks -- 8.2.2 New Practices and Knowledge -- 8.3 Conclusions -- 8.3.1 Lessons Learnt from the PoliVisu Project -- 8.3.2 Some Recommendations -- References -- Acknowledgments.
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