Data Science for Public Policy
EMBARGOED UNTIL 2027-03-19
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Author / Producer
Date
2025
Publication Type
Doctoral Thesis
ETH Bibliography
yes
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EMBARGOED UNTIL 2027-03-19
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Abstract
Data science is increasingly recognized as a powerful tool for public policy, e.g., as a guide for the world's transformation towards a more sustainable society under complex interdependencies between economic, social, and environmental constraints. Despite this potential, the public sector often struggles with low data literacy and proprietary or outdated technological frameworks, hindering its ability to attract qualified talent and effectively use data for evidence-based decision making. This dissertation aims to increase the adoption of data science in the public sector and the social sciences by introducing fundamental technical concepts, highlighting successful use cases, and recognizing academia as an important driver of accountability for the 2030 Agenda for Sustainable Development and Goal 16 (Peace, Justice, and Strong Institutions) in particular.
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Publication status
published
External links
Editor
Contributors
Examiner : Ash, Elliott
Examiner : Asher, Sam
Examiner : Günther, Isabel
Book title
Journal / series
Volume
Pages / Article No.
Publisher
ETH Zurich
Event
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Natural Language Processing (NLP); Machine learning (artificial intelligence)
Organisational unit
09627 - Ash, Elliott / Ash, Elliott