CFP Topics

Topics invited include but are not limited to the following: 

Government & Policy: Digital era governance and democracy, data-driven service delivery in central and local government, algorithmic governance/regulation, open source and open data movements, sharing economy, digital public, multinational companies (Google, Amazon, Uber, etc.) and privatization of public services, public opinion and participation in democratic processes, data literacy, policy laboratories, case studies and best practices. 

Policy for Data & Management: Data governance; data collection, storage, curation, and access; distributed databases and data streams, psychology and behaviour of decision; data security, ownership, linkage; data provenance and expiration; private/public sector/non-profit collaboration and partnership; capacity-building and knowledge sharing within government; institutional forms and regulatory tools for data governance. 

Data Sources: Open, commercial, personal, proprietary sources; administrative data, official statistics, user-generated web content (blogs, wikis, discussion forums, posts, chats, tweets, podcasting, pins, digital images, video, audio files, advertisements, etc.), search engine data, data gathered by connected people and devices (e.g. wearable technology, mobile devices, Internet of Things), tracking data (including GPS/geolocation data, traffic and other transport sensor data, CCTV images etc.,), satellite and aerial imagery, and other relevant data sources. 

Data Analysis: Computational procedures for data collection, storage, and access; large-scale data processing, real-time and historical data analysis, spatial and temporal analysis, forecasting and nowcasting, dealing with biased/imperfect/missing/uncertain data, human interaction with data, statistical and computational models, networks & clustering, dealing with concept drift and dataset shift, other technical challenges, communicating results, visualisation, and other relevant analysis topics. 

Methodologies: Qualitative/quantitative/mixed methods, secondary data analysis, web mining, predictive models, randomised controlled trials, sentiment analysis, Blockchain distributed ledger and smart contract technologies, machine learning, Bayesian approaches and graphical models, biologically inspired models, simulation and modelling, small area estimation, correlation & causality-based models, gaps in theory and practice, other relevant methods. 

Policy/Application Domains: Public administration, cities and urban analytics, policing and security, health, economy, finance, taxation, law, science and innovation, energy, environment, social policy areas (education, migration, etc.), humanitarian and development policy, crisis response, public engagement and other relevant domains. 

Citizen Empowerment: Online platforms and communities, crowdsourcing, citizen science, community driven research, citizen expertise for local & central decision-making, mobile applications, user communities, other relevant topics. 

Ethics, privacy, security: Data and algorithms in the law; licensing and ownership; using personal or proprietary data; transparency, accountability, participation in data processing; discrimination- and fairness-aware data mining and machine learning; privacy-enhancing technologies (PETs) in the public sector; public rights, free speech, dialogue and trust.

Committee Members

Advisory Committee:
Jean Bacon – University of Cambridge
Kenneth Benoit – London School of Economics and Political Science
Jon Crowcroft – University of Cambridge; The Alan Turing Institute
Anthony Finkelstein – Government Office for Science; The Alan Turing Institute
David Hand – Winton Capital Management; Imperial College
Helen Margetts – University of Oxford; The Alan Turing Institute
Natasha McCarthy – The Royal Society
Beth Noveck – The GovLab, New York University
Quentin Palfrey – J-PAL North America, MIT
Alan Penn – University College London
Rob Procter – University of Warwick; The Alan Turing Institute
Peter Smith – UK Administrative Data Research Network (ADRN); University of Southampton
John Shawe-Taylor – University College London
John Taysom – Privitar; University College London
Philip Treleaven – University College London
Stefaan Verhulst – New York University
Sir David Wallace – University of Cambridge
Derek Wyatt – Royal Trinity Hospice; All Party Parliamentary Group on Data Analytics

Programme Committee:
Emanuele Baldacci – European Commission
Sarah Barns – Western Sydney University
Marcus Besley – Government Office for Science
Anil Bharath – Imperial College London
Daniel Castro – Centre for Data Innovation
Gabrielle Demange – Paris School of Economics
Suleyman Demirsoy – Intel
Yves-Alexandre de Montjoye – Imperial College London
Dawn Duhaney – Government Digital Service
Rayid Ghani – University of Chicago
Bilal Gokpinar – University College London
David Johnson – Office for National Statistics
Jose Manuel Magallanes – University of Washington; Pontificia Universidad Catolica del Peru
H Scott Matthews – Carnegie Mellon University
Eric Meyer – University of Oxford; The Alan Turing Institute
Slava Michaylov – University of Essex
Suzy Moat – University of Warwick; The Alan Turing Institute
Jessica Montgomery – The Royal Society
Will Moy – Full Fact
Mirco Musolesi – University College London; The Alan Turing Institute
Duccio Piovani – University College London
Martijn Poel – Technopolis Group
Tobias Preis – University of Warwick; The Alan Turing Institute
Charlotte Sausman – University of Cambridge
Ralph Schroder – University of Oxford
Gideon Shimshon – Leiden University
Jatinder Singh – University of Cambridge
Barbara Ubaldi – The Organisation for Economic Co-operation and Development (OECD)
Diana Vlad-Calcic – European Commission
Andrew Young – New York University

Local Committee:
Sarah Chaytor – University College London
George Dibb – Policy Connect; All Party Parliamentary Group on Data Analytics
Nathaniel Hayward – Data for Policy
Carina Schneider – University College London
Michael Veale – University College London
Matthew Wood – Government Office for Science

Summaries from Report

6 – 7 September, 2017, London

The 2017 conference was hosted by the UK Government Data Science Partnership, comprising the Government Office for Science, the Office for National Statistics, and the Government Digital Service, at the UK’s premier government venue for conferences, 1VS, with participation of 245 delegates. The conference posed the question “Government by Algorithm?” as its central theme (now a distinct area of research itself). This edition particularly challenged the hierarchical structure of governments; new concepts and tools from technologies including Artificial Intelligence, Blockchain, and the Internet of Things were enabling automation of the public sector, with the unsettling possibility of large-scale job losses. The conference also highlighted regulatory issues and potential threats to democratic processes emerging from ‘smartification’ of people, devices, institutions, cities and governments. Citizen empowerment therefore featured as a special area of coverage at this conference. The support network of the community also grew with involvement of the All-Party Parliamentary Group on Data Analytics of the UK Parliament, the University of Essex, Essex County Council, the UK Administrative Data Research Network, Privitar, and CognitionX.

Keynote Speakers
Stefaan Verhulst, GovLab, New York University
Philip Treleaven, University College London

Plenary Speakers
Helen Margetts, Oxford Internet Institute, University of Oxford; The Alan Turing Institute
Peter Smith, UK Administrative Data Research Network, University of Southampton
Stefaan Verhulst GovLab, New York University
Jon Crowcroft, University of Cambridge
Mariana Kotzeva Eurostat, European Commission
Heather Savory UK Office for National Statistics
Daniel Zeichner Member of Parliament for Cambridge; Chair of All Party Parliamentary group on Data Analytics, UK

University College London – Department of Computer Science and UCL Public Policy
University of Cambridge – Computer Laboratory and Centre for Science and Policy (CSaP)
UK Government Data Science Partnership – Government Office for Science (GO-Science), Office for National Statistics (ONS), and Government Digital Service (GDS)
All Party Parliamentary Group on Data Analytics, UK Parliament
Imperial College London – Data Science Institute
London School of Economics and Political Science – Department of Methodology
The Alan Turing Institute – UK National Institute for Data Science
The Royal Statistical Society
European Commission – Joint Research Centre and Eurostat
University of Oxford – Oxford Internet Institute
New York University – The Government Laboratory (GovLab) and the Open Governance Research Exchange (OGRX)
University of Essex – Institute for Analytics and Data Science
Essex County Council
UK Administrative Data Research Exchange (ADRN)