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Data for Policy 2016: Frontiers of Data Science for Government – Ideas, Practices and Projections
15th September 2016 - 16th September 2016£550
Data Science is emerging as a key interdisciplinary research field to address major contemporary challenges across sectors. Particular focus on the government sector offers huge potentials to advance citizen services and collective decision-making processes. To reflect the diversity of skills and knowledge required to tackle challenges in this domain, the conference offers an open discussion forum for all stakeholders. We invite individual and/or group submissions from all relevant disciplines and application domains. Topics covered include but are not limited to the following:
- Government & Policy: Digital era governance and citizen services, public demand vs. government response, using data in the policy process, open source and open data movements, policy laboratories, citizen expertise for government, public opinion and participation in democratic processes, distributed data bases and data streams, information and evidence in policy context, case studies and best practices.
- Policy for Data & Management: Data collection, storage, and access; psychology/behaviour of decision; privacy, trust, public rights, free speech, ethics and law; data security/ownership/linkage; provenance, curation, expiration; private/public sector/non-profit collaboration and partnership, etc.
- Data Analysis: Computational procedures for data collection, storage, and access; large-scale data processing, dealing with biased/imperfect/uncertain data, human interaction with data, statistical/computational models, technical challenges, communicating results, visualisation, etc.
- Methodologies: Qualitative/quantitative/mixed methods, gaps in theory and practice, secondary data analysis, web scraping, randomised controlled trials, sentiment analysis, Bayesian approaches and graphical models, biologically inspired models, real-time and historical data processing, simulation and modeling, small area estimation, correlation & causality based models, and other relevant methods.
- Data Sources: Government administrative data, official statistics, commercial and non-profit data, 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.
- Policy/Application Domains: Security, health, cities, public administration, economy, science and innovation, finance, energy, environment, social policy areas (education, migration, etc.) and other relevant domains.
Data for Policy 2016 Conference Programme is available here!