6/9/2017 - 7/9/2017

Data for Policy (London, UK)

 

Running for its third year, Data for Policy conference series has proven to be a leading international discussion forum around the theory and applications of Data Science as relevant to governments and policy research. The 2017 conference introduces a special Demonstration Track alongside the poster sessions to provide a showcasing opportunity for new tools, technological advances, and services offered in this emerging field.

Topics may 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.

Find out more on the event page here.

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