Scientific Programme
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Draft programme
Please note that this is a draft program and is subject to change.
Monday, August 24, 2026 (Day 1)
Day Theme: Survey Design in Modern Official Statistics Adaptation of survey designs to new data sources and changing data environments. | ||
| Time | Activity | Speaker |
| 12.00-13.00 | Registration | |
| 13.00-13.15 | Welcome and opening remarks | Jeļena Voronova (Central Statistical Bureau of Latvia, representative of Latvia in BNU Network) Jānis Valeinis (head of the Laboratory of Statistical Research and Data Analysis, University of Latvia) Raimonds Lapiņš (Central Statistical Bureau of Latvia) |
| 13.15-14.00 | Session 1 Invited lectures Chair: Jeļena Voronova | Representative of Eurostat (EUROSTAT) Topic to be confirmed |
| 14.00-14.45 | Jānis Lapiņš (one of the founders of BNU Network) Historical Aspects of the Establishment of the BNU Network | |
| 14.45-15.20 | Break | |
| 15.20-15.40 | Session 2 Contributed presentations with discussions Chair: TBA | Open presentation slot |
| 15.40-16.00 | Open presentation slot | |
| 16.00-16.20 | Open presentation slot | |
| 16.20-16.40 | Speaker (Central Statistical Bureau of Latvia) Survey Design and Implementation Challenges in a Light Commercial Vehicles Survey | |
| 16.40-17.00 | Walk to the opening reception venue | |
| 17.00-19.00 | Welcome event | |
Tuesday, August 25, 2026 (Day 2)
Day Theme: Machine Learning in Data Preparation and Analysis Use of machine learning methods to improve data cleaning, integration, and statistical analysis. | ||
| Time | Activity | Speaker |
| 8.00-9.00 | Registration | |
| 9.00-9.45 | Session 3 Invited lectures Chair: | Marco Puts (Statistics Netherlands) Methodological foundations of using Machine Learning in official statistics |
| 9.45-10.30 | Open presentation slot | |
| 10.30-11.00 | Break | |
| 11.00-11.20 | Session 4 Contributed presentations with discussions Chair: Maria Valaste | Open presentation slot |
| 11.20-11.40 | Open presentation slot | |
| 11.40-12.00 | Open presentation slot | |
| 12.00-12.20 | Open presentation slot | |
| 12.20-12.40 | Open presentation slot | |
| 12.40-14.00 | Lunch break | |
| 14.00-14.45 | Session 5 Invited lectures Chair: Jānis Valeinis | Anastasija Tetereva (Erasmus University Rotterdam) Tree-Based Methods for Survey Data and Beyond: Modeling Structured Heterogeneity with Interpretable ML |
| 14.45-15.30 | Henri Luomaranta-Helmivuo (Statistics Finland) Topic to be confirmed | |
| 15.30-16.00 | Group photo; guided tour of the House of Science | |
| 16.00-16.20 | Break | |
| 16.20-16.40 | Session 6 Contributed presentations with discussions Chair: | Open presentation slot |
| 16.40-17.00 | Open presentation slot | |
| 17.00-17.20 | Open presentation slot | |
| 17.20-17.40 | Open presentation slot | |
| 17.40-18.00 | Speaker (Unversity of Latvia) Development of an automated method for household nucleus identification using machine learning algorithms | |
| 18.00-18.10 | Conclusions of the day | |
| 18.10-19.00 | Steering committee meeting | |
Wednesday, August 26, 2026 (Day 3)
Day Theme: Probability and Non-Probability Sampling Methods for integrating different data sources to produce reliable and efficient statistical estimates from both probability and non-probability data. | ||
| Time | Activity | Speaker |
| 9.00-9.45 | Session 7 Invited lectures Chair: Biruta Sloka | Danutė Krapavickaitė (Vilnius Gediminas Technical University) Non-Probability Samples – an Overview of the Problem |
| 9.45-10.30 | Kaja Sõstra (Statistics Estonia/Eurostat) Developing transparent and harmonised publication thresholds for EU-LFS data dissemination | |
| 10.30-11.00 | Break | |
| 11.00-11.20 | Session 8 Contributed presentations with discussions Chair: Vilma Nekraisite-Liege | Speaker (Central Statistical Bureau of Latvia) Nonresponse Bias Adjustment in Household Budget Survey Using Response Propensity Weighting |
| 11.20-11.40 | Speaker (Central Statistical Bureau of Latvia) Income Imputation Challenges in Labour Force Survey: Methods and Practical Issues | |
| 11.40-12.00 | Speaker (Central Statistical Bureau of Latvia) Automating Imputation Processes in Construction Statistics: Methodological and Operational Challenges | |
| 12.00-12.20 | Biruta Sloka (University of Latvia (UL)) Use of Official Statistics Survey’s (EU-SILC, Labour Force Survey, ICT-Individuals Survey, etc) Micro Data in Studies and Research | |
| 12.20-12.40 | Open presentation slot | |
| 12.40-14.00 | Lunch break | |
| 14.00-15.00 | Trip to the main building of University of Latvia | |
| 15.00-16.00 | Meeting with University of Latvia management on statistical analysis support Round table discussions | |
| 16.00-16.15 | Break | |
| 16.15-17.00 | Guided tour of the main building of the University of Latvia | |
| 17.30-20.00 | Guided tour in Riga | |
Thursday, August 27, 2026 (Day 4)
Day Theme: Small Area Estimation and Nonparametric Approaches Development of detailed statistics using small-area models and classical, robust, and nonparametric statistical methods. | ||
| Time | Activity | Speaker |
| 9.00-9.45 | Session 9 Invited lectures Chair: Danutė Krapavickaitė | Tomasz Żądło (University of Economics in Katowice) Fundamentals and Recent Developments in Small Area Estimation |
| 9.45-10.30 | Open presentation slot | |
| 10.30-11.00 | Break | |
| 11.00-11.20 | Session 10 Contributed presentations with discussions Chair: Thomas Laitila
| Speaker (Central Statistical Bureau of Latvia) Small Area Estimation Approaches for Measuring Undeclared Employment |
| 11.20-11.40 | Anželika Ņesterova (Faculty of Science and Technology, UL) Small Area Estimation for Household Budget Survey: Producing Reliable Estimates for Municipal Domains | |
| 11.40-12.00 | Open presentation slot | |
| 12.00-12.20 | Open presentation slot | |
| 12.20-12.40 | Open presentation slot | |
| 12.40-14.00 | Lunch break | |
| 14.00-14.45 | Session 11 Invited lectures Chair: | Volodymir Sarioglo (Institute for Demography and Social Studies) Population Sample Surveys in Ukraine during Wartime: Challenges and Lessons |
| 14.45-15.30 | Open presentation slot | |
| 15.30-16.00 | Break | |
| 16.00-16.20 | Session 12 Contributed presentations with discussions Chair: | Jānis Valeinis (Laboratory of Statistical Research and Data Analysis, UL) Potential of robust and nonparametric methods in survey sampling (tbc) |
| 16.20-16.40 | Emīls Siliņš (Laboratory of Statistical Research and Data Analysis, UL) Topic to be confirmed | |
| 16.40-17.00 | Sofiia Lukashevych (Laboratory of Statistical Research and Data Analysis, UL) Topic to be confirmed | |
| 17.00-17.20 | Open presentation slot | |
| 17.20-17.40 | Open presentation slot | |
| 17.40-17.50 | Conclusions of the day | |
| 18.30-21.00 | Farewell party | |
Friday, August 28, 2026 (Day 5)
Day Theme: AI and Automation in Statistical Production Application of AI and automation to improve the efficiency and quality of statistical production processes. | ||
| Time | Activity | Speaker |
| 9.00-9.45 | Session 13 Invited lectures Chair: | Marcin Szymkowiak ((Poznan University of Economics and Business) A joint calibration approach for totals and quantiles for probability and nonprobability samples |
| 9.45-10.30 | Open presentation slot | |
| 10.30-11.00 | Break | |
| 11.00-11.20 | Session 14 Contributed presentations with discussions Chair:
| Open presentation slot |
| 11.20-11.40 | Open presentation slot | |
| 11.40-12.00 | Open presentation slot | |
| 12.00-12.20 | Open presentation slot | |
| 12.20-12.40 | Open presentation slot | |
| 12.40-13.00 | Closing remarks | Programme & Organising committees |
Last updated 27.04.2026.
Call for Papers
The workshop invites contributions on methodological and applied aspects of survey sampling in modern data environments. Topics include, but are not limited to:
- Survey sampling design, stratification, clustering, multi-stage and rotation sampling
- Adaptive and responsive survey designs and modern data collection strategies
- Sampling frames, coverage diagnostics, and frame maintenance
- Nonresponse mechanisms, response propensity modelling, and use of paradata
- Survey estimation methods: weighting, calibration, model-assisted estimation, and variance estimation
- Treatment of missing data: imputation and machine-learning approaches
- Integration of survey data with administrative registers and alternative data sources
- Data fusion and combining probability and non-probability samples
- Small area estimation, spatial methods, and domain estimation
- Machine learning and AI applications in survey statistics
- Automated workflows and reproducible pipelines for survey production
- Quality assessment, total survey error, and methodological challenges in modern survey statistics