*Call for papers, presentations, sessions, and workshops – Deadline: 8th May* 3rd Annual International Conference *DATA FOR POLICY 2017* Government by Algorithm? 6-7 September 2017 | London dataforpolicy.org | @dataforpolicy <https://twitter.com/dataforpolicy> Governments are being transformed under the impact of the digital revolution, although the speed of change is behind that of the commercial sector. Policy-makers in all domains are facing increasing pressures to interact with citizens more efficiently, and make better decisions in the light of data flooding in all forms, sophisticated computing technologies, and analytics methods. The hierarchical structures of governments are also being challenged as these technologies equip individuals and informal networks with the necessary tools to better participate in public decision making processes, and have a societal impact at a much faster pace than ever before. The concepts and tools from artificial intelligence, machine learning, big data analytics, Internet of Things (IoT), and now blockchain technologies are also likely to automate many services in the public sector, greatly increasing its efficiency but at the cost of potentially millions of jobs. ‘Smartification’ of people, devices, institutions, cities, and governments also brings constant, ubiquitous surveillance which, together with inference and recognition technologies, creates the potential to regulate human behaviour and may even threaten democracy. The third of the *Data for Policy* conference series highlights *‘Government by Algorithm?’ *as its main theme, while also welcoming contributions from the broader Data Science and Policy discussions. All relevant formats including research and policy presentations, workshops, fringe events and other innovative formats will be considered by the committees. *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 modeling, 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. Extended abstracts for individual submissions should not exceed 1000 words and group/special session submissions are limited to 4500 words (including general session description and abstracts for each of the presentations in the session). All submissions will also be considered for post conference publications and those selected will be invited to submit full discussion papers prior to the conference. *Submissions are accepted through the official conference website – * *dataforpolicy.org* <http://dataforpolicy.org/> Special discounts with conference registration fees will be applied to students and early career researchers. Limited funding is also available to support travel expenses of exceptional candidates. For those wishing to be considered for travel support please send a CV and covering letter to the conference team after completing your submission and before the submission deadline. Partnership and exhibition opportunities are available and organisations can get in touch with the Data for Policy Team (team@dataforpolicy.org) to discuss opportunities for collaboration. All general enquiries about the conference should be directed to the Data for Policy Team at team@dataforpolicy.org *Important Dates: * Abstract submission deadline: Monday, 8 May 2017 Notification of acceptance: Wednesday, 14 June 2017 Presenters’ registration deadline: Tuesday, 1 August 2017 Discussion Paper submission deadline: Friday, 18 August 2017 Public registration deadline: Friday, 25 August 2017 Conference: Wednesday-Thursday, 6-7 September 2017 *Organising Bodies & Institutions: * *Data for Policy* is an independent initiative launched in 2015 at its inaugural conference *“Policy-making in the Big Data Era: Opportunities and Challenges” *that was hosted by the University of Cambridge. The second conference *“Frontiers of Data Science for Government: Ideas, Practices, and Projections”* was also held at the same venue in 2016. The series has proven to be a key international discussion forum around the theory and applications of Data Science as relevant to governments and policy research, and supported by a large number of key stakeholders including prestigious academic institutions, government departments, international agencies, non-profit institutions, and businesses. The *Government Data Science Partnership* brings together capability from ONS, GDS and GO-Science to support departments in applying data science and big data techniques to challenges. There are four activity streams: - Working in an open and ethical way - Unlocking practical barriers - Creating and developing data science projects - Building data science capability across government The Government Data Science Partnership vision is to improve government capacity to use data science to underpin decision-making, policy development, tailor services, and work efficiently. In doing so the UK government will be recognised as world leading in its use of open and ethical data science. The *All-Party Parliamentary Group on Data Analytics* is a new cross-party group of MPs and peers established by Daniel Zeichner MP to connect Parliament with business, academia and civil society to promote better policy making on big data and data analytics. *Policy Connect* is a not-for-profit social enterprise with two decades in policy work, overseeing the research and delivery of more than 50 key publications. We have a long history of success in running engaging forums, commissions and All-Party Parliamentary Groups. Data for Policy is grateful to the following institutions for their continuing support: - University College London - University of Cambridge - UK Government Data Science Partnership: Office for National Statistics (ONS), Government Digital Service (GDS), Government Office for Science (GO-Science) - All Party Parliamentary Group on Data Analytics - Imperial College London - London School of Economics and Political Science - University of Oxford - The Alan Turing Institute - Royal Statistical Society - European Commission - New York University - Leiden University