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NTTS 2017 conference topics

The Scientific Committee welcomes the submission of abstracts on the following topics:

Track A. Data collection

  • Survey design
  • Measurement of longitudinal phenomena
  • Pilot experiments and experiments embedded in statistical production.
  • Non-response, response propensity, respondent behaviour and response burden
  • Multi-mode data collection
  • Web data collection
  • Crowdsourcing
  • Designed data collection by (mobile) devices or other non-traditional approaches
  • Administrative and registry data
  • Big Data (and other non-traditional) sources
  • Integrated data collection systems
  • Adaptive and responsive survey designs
  • Sample design 
  • Non-probability and convenience sampling
  • Collection of Paradata

Track B. Data integration

  • Data warehousing
  • Data linking, statistical matching
  • Linked Open Data
  • Integration of survey, administrative and Big Data sources
  • Reconciliation of information from different sources
  • Multinational repositories and exchange of micro-data
  • Accounting frameworks

Track C. Estimation and analysis

  • Survey estimation
  • Estimation based on administrative data
  • Estimation based on Big Data
  • Estimation based on multiple sources
  • Variance estimation
  • Small Area Estimation
  • Detection and treatment of outliers 
  • Statistical data preparation, including validation, editing and imputation
  • Data mining
  • Machine learning
  • Spatial statistics
  • Indicators
  • GDP and beyond
  • Analysis of panel data and analysis of change
  • Time series analysis, seasonal adjustment, forecasting, nowcasting and prediction
  • Using paradata in estimation and analysis 

Track D. Dissemination and visualisation

  • Open Data dissemination
  • Visualisation, GIS
  • Storytelling
  • Continuous publication of statistical information
  • Statistical disclosure control
  • Secure data access
  • Mobile applications
  • Data analytics and data as a service
  • Methods for catering to the needs of different user communities
  • Enhancing the user experience

Track E. Statistics and Society – stakeholder relations

  • Methods for user analytics
  • Methods for capturing user input and assessing user needs
  • Methods for assessing user satisfaction
  • Methods for stakeholder management
  • Literacy in the data age
  • The value proposition of official statistics in a world with multiple suppliers
  • Ethics and good governance
  • Transparency
  • Innovation in quality and risk management frameworks

Track F. Innovation in information models and standards

  • New metadata concepts, structures and formats (Semantic web, RDF etc.)
  • Information models
  • IT systems to support a corporate statistical Enterprise Architecture
  • Shared services, data sharing and statistical registries for standards

Track G. Enablers of modernisation

  • Enabling conditions for the use of Big Data in statistical production
  • Skills for tomorrow’s official statisticians
  • Enterprise architecture and integration
  • Collaboration models