List of Publications
Statistics Netherlands publication period (2015 - 2019)
Links to other publications 1, 2, 3, 4, 5, 6, 7.
Daas, P., Burger, J. (2015) Profiling Big Data sources to assess their selectivity. Abstract for the New Techniques and Technologies for Statistics 2015 conference, Brussels, Belgium. (abstract).
Puts, M., Daas, P., de Waal, T. (2015) Finding errors in Big Data. Significance 12 (3), pp. 26-29. DOI-link (paper).
Karlberg, M., Biffignandi, S., Daas, P.J.H., Holmberg, A., Hulliger, B., Jacques, P., Lehtonen, R., Münnich, R.T., Shlomo, N., Silberman, R., Stoop, I. (2015) Preface. Journal of Official Statistics 31(2), pp. 149-153. DOI-link (paper).
Daas, P.J.H., Puts, M.J., Buelens, B., van den Hurk, P.A.M. (2015) Big Data and Official Statistics. Journal of Official Statistics 31 (2), pp. 249-262. DOI-link (paper).
Puts, M., Daas, P. (2015) Editing Big Data: an holistic approach. Paper for the Work Session on Statistical Data Editing, United Nations Economic Commission for Europe, Budapest, Hungary, (pdf-version).
Van den Brakel, J., Sohler, E., Daas, P., Buelens, B. (2016) Social media as a data source for official statistics; the Dutch Consumer Confidence Index. Discussion paper 201601, Statistics Netherlands, The Hague/Heerlen, The Netherlands. (pdf-version).
Puts, M., Tennekes, M., Daas, P.J.H., de Blois, C. (2016) Using huge amounts of road sensor data for official statistics. Paper and presentation for the European Conference on Quality in Official Statistics 2016, Madrid, Spain. (paper and presentation).
Oostdijk, N., Hurriyetoglu, A., Puts, M., Daas, P., van den Bosch, A. (2016) Information extraction from the social media: a linguistically motivated approach. Paper for the TALN 2016 workshop, 23rd French Conference on Natural Language Processing, session Risk and NLP: detection, prevention, management, Paris, France. (paper and presentation).
Daas, P.J.H., Burger, J., Quan, L., ten Bosch, O., Puts, M. (2016) Profiling of Twitter Users: a big data selectivity study. Discussion paper 201606, Statistics Netherlands, The Hague/Heerlen, The Netherlands. (paper).
Daas, P.J.H., Braaksma, B., Aly, R., Engelhardt, Y., Hiemstra, D., Zurita Milla, R. (2016) Big Data Masterclass and DataCamp 2015. Discussion paper 201615, Statistics Netherlands, The Hague/Heerlen, The Netherlands. (paper).
Puts, M., Daas, P., de Waal, T. (2017) Finding Errors in Big Data. In: The Best Writing on Mathematics 2016, Princeton, USA. (Pitici, M., ed), pp. 291-299, Princeton University Press, USA. DOI-link (table of content).
Luomaranta, H., Daas, P., Nowitzka, A., Nikic, B. (2016) Recommendations about IT tools for collection of data for purposes of Consumer Confidence Index and NowCasts of Turnover Indices. Deliverable 6.2, Workpackage 6 Early Estimates, ESSnet Big Data, Version 16 June 2016. (report).
Luomaranta, H., Daas, P., Nowitzka, A., Nikic, B. (2016) Recommendations about methodology for processing the data for purposes of Consumer Confidence Index and NowCasts of Turnover Indices. Deliverable 6.3, Workpackage 6 Early Estimates, ESSnet Big Data, Version 16 June 2016. (report).
Daas, P., De Broe, S., van Meeteren, M. (2017) Center for Big Data Statistics at Statistics Netherlands. Abstract for the New Techniques and Technologies for Statistics 2017 conference, Brussels, Belgium. (abstract and presentation).
Daas, P., Abbott, O., Alexandru, C., Bisioti, E., Chavdarov, V., Debusschere, M., Horvat, V., Museux, J-M., Reis, F., Ilves, M., Langsrud, O., Maslankowski, J., Portugal, A., Puts, M., Tennekes, M., Sanguiao, L., Six, M., Wu, D. (2017) Results of Workshop on: Important topics in the area of methodology, quality and IT when using big data for official statistics. Workpackage 8, ESSnet Big Data, Heerlen, The Netherlands. Version 19 June 2017. (report).
Van den Brakel, J., Sohler, E., Daas, P., Buelens, B. (2017) Social media as a data source for official statistics; the Dutch Consumer Confidence Index. Survey Methodology 43 (2), pp. 183-210. (English and French version of paper).
Daas, P., Puts, M., Renssen, R. (2017) On Big Data based Statistical Inference. Abstract and poster for the 3rd UCL Workshop on the Theory of Big Data, June 26th-28th, London, UK. (abstract and poster).
Daas, P.J.H., Buelens, B. (2017) Big data, bias and ways to correct for it. Abstract for the Big Data and ethics session at the 61st World Statistics Congress (ISI 2017), July 16th-21st, Marrakech, Morocco. (abstract and slides).
Hurriyetoglu, A., Daas, P. (2018) Using Location and Dialect to Classify Twitter Users from the Netherlands and Flanders. Poster at the 28th conference of Computers in Linguistics In the Netherlands (CLIN28), January 26th, Nijmegen, The Netherlands. (poster).
Consten, A., Chavdarov, V., Daas, P.J.H., Horvat, V., Maslankowski, J., Quaresma, S., Scannapieco, M., Six, M., Tuoto, T. (2018) Report describing the IT-infrastructure used and the accompanying processes developed and skills needed to study or produce Big Data based official statistics. Deliverable 8.3, Workpackage 8, ESSnet Big Data, 5 March 2018. report).
Daas, P., Puts, M. (2018) Big data methods and techniques. Webinar for the European Master in Official Statistics (EMOS) 2018. ( slides, web page with links, and YouTube recording).
Nowicka, A., Maslankowski, J., Blaszczyk, L., Wojcik, S., Sheridan, J., Daas, P.J.H., Alves, R., Fernandes, M.J., Quaresma, S., Sozzi, A. (2018) List of potential pilots and domains with successful implementation potential for further elaboration in the second wave of pilots in 2018. Milestone 7.9, Workpackage 7, ESSnet Big Data, Version 27 April 2018. (report).
Consten, A., Chavdarov, V., Daas, P., Horvat, V., Maslankowski, J., Quaresma, S., Six, M., Tuoto, T. (2018) Report describing the quality aspects of Big Data for Official Statistics. Deliverable 8.2, Workpackage 8, ESSnet Big Data, 7 May 2018. (report).
Consten, A., Chavdarov, V., Daas, P., Horvat, V., Maslankowski, J., Quaresma, S., Six, M., Tuoto, T. (2018) Report describing the methodology of using Big Data for official statistics and the most important questions for future studies. Deliverable 8.4, Workpackage 8, ESSnet Big Data, 31 May 2018. (report).
Van Delden, A., Daas, P., ten Bosch, O., Windmeijer, D. (2018) Text analysis methods: application in official statistics (in Dutch). STAtOR 2 (juni), pp. 8-12. ( paper).
Daas, P.J.H. (2018) Big Data Methodology. Methods for Big Data in Official Statistics seminar, October 4-5, Heerlen, the Netherlands (abstract).
Van der Doef, S., Daas, P.J.H., Windmeijer, D. (2018) Identifying Innovative Companies from Their Website. BigSurv18 conference, October 27, Barcelona, Spain ( abstract).
Karlberg, M., Biffignandi, S., Daas, P.J.H., Di Consiglio, L., Holmberg, A., Lehtonen, R., Münnich, R.T., Nikic, B., Paasi, M., Shlomo, N., Silberman, R., Stoop, I. (2018) Preface. Journal of Official Statistics 34(4), pp. 797-809. DOI-link (paper).
Puts, M.J.H., Daas, P.J.H., Tennekes, M., de Blois, C. (2019) Using huge amounts of road sensor data for official statistics. AIMS Mathematics 4(1), pp. 12-25. DOI-link paper).
Daas, P. (2019) Using Big Data in Official Statistics. Presentation at the Deutsche Arbeitsgemeinschaft Statistik (DAGStat) Conference, München, 18-22 March. (abstract).
Daas, P., Harmsen, C., Offermans, M. (2019) Mezuro Quality Evalution (in Dutch: Kwaliteitstoets Mezuro). Statistics Netherlands internal report, March 2019, Statistics Netherlands, Heerlen/The Hague, The Netherlands. (report).
Daas, P., Gootzen, Y., van der Doef, S. (2019) Detecting Innovative Companies via Their Website. Abstract for the 2nd annual Symposium on Data Science and Statistics, Bellevue, WA, USA. (abstract).
Daas, P. (2019) Big Data interview (in Dutch). 4TU Carrière special, pp 28-29. (interview).
The list of publications continuous here.
Daas, P., Burger, J. (2015) Profiling Big Data sources to assess their selectivity. Abstract for the New Techniques and Technologies for Statistics 2015 conference, Brussels, Belgium. (abstract).
Puts, M., Daas, P., de Waal, T. (2015) Finding errors in Big Data. Significance 12 (3), pp. 26-29. DOI-link (paper).
Karlberg, M., Biffignandi, S., Daas, P.J.H., Holmberg, A., Hulliger, B., Jacques, P., Lehtonen, R., Münnich, R.T., Shlomo, N., Silberman, R., Stoop, I. (2015) Preface. Journal of Official Statistics 31(2), pp. 149-153. DOI-link (paper).
Daas, P.J.H., Puts, M.J., Buelens, B., van den Hurk, P.A.M. (2015) Big Data and Official Statistics. Journal of Official Statistics 31 (2), pp. 249-262. DOI-link (paper).
Puts, M., Daas, P. (2015) Editing Big Data: an holistic approach. Paper for the Work Session on Statistical Data Editing, United Nations Economic Commission for Europe, Budapest, Hungary, (pdf-version).
Van den Brakel, J., Sohler, E., Daas, P., Buelens, B. (2016) Social media as a data source for official statistics; the Dutch Consumer Confidence Index. Discussion paper 201601, Statistics Netherlands, The Hague/Heerlen, The Netherlands. (pdf-version).
Puts, M., Tennekes, M., Daas, P.J.H., de Blois, C. (2016) Using huge amounts of road sensor data for official statistics. Paper and presentation for the European Conference on Quality in Official Statistics 2016, Madrid, Spain. (paper and presentation).
Oostdijk, N., Hurriyetoglu, A., Puts, M., Daas, P., van den Bosch, A. (2016) Information extraction from the social media: a linguistically motivated approach. Paper for the TALN 2016 workshop, 23rd French Conference on Natural Language Processing, session Risk and NLP: detection, prevention, management, Paris, France. (paper and presentation).
Daas, P.J.H., Burger, J., Quan, L., ten Bosch, O., Puts, M. (2016) Profiling of Twitter Users: a big data selectivity study. Discussion paper 201606, Statistics Netherlands, The Hague/Heerlen, The Netherlands. (paper).
Daas, P.J.H., Braaksma, B., Aly, R., Engelhardt, Y., Hiemstra, D., Zurita Milla, R. (2016) Big Data Masterclass and DataCamp 2015. Discussion paper 201615, Statistics Netherlands, The Hague/Heerlen, The Netherlands. (paper).
Puts, M., Daas, P., de Waal, T. (2017) Finding Errors in Big Data. In: The Best Writing on Mathematics 2016, Princeton, USA. (Pitici, M., ed), pp. 291-299, Princeton University Press, USA. DOI-link (table of content).
Luomaranta, H., Daas, P., Nowitzka, A., Nikic, B. (2016) Recommendations about IT tools for collection of data for purposes of Consumer Confidence Index and NowCasts of Turnover Indices. Deliverable 6.2, Workpackage 6 Early Estimates, ESSnet Big Data, Version 16 June 2016. (report).
Luomaranta, H., Daas, P., Nowitzka, A., Nikic, B. (2016) Recommendations about methodology for processing the data for purposes of Consumer Confidence Index and NowCasts of Turnover Indices. Deliverable 6.3, Workpackage 6 Early Estimates, ESSnet Big Data, Version 16 June 2016. (report).
Daas, P., De Broe, S., van Meeteren, M. (2017) Center for Big Data Statistics at Statistics Netherlands. Abstract for the New Techniques and Technologies for Statistics 2017 conference, Brussels, Belgium. (abstract and presentation).
Daas, P., Abbott, O., Alexandru, C., Bisioti, E., Chavdarov, V., Debusschere, M., Horvat, V., Museux, J-M., Reis, F., Ilves, M., Langsrud, O., Maslankowski, J., Portugal, A., Puts, M., Tennekes, M., Sanguiao, L., Six, M., Wu, D. (2017) Results of Workshop on: Important topics in the area of methodology, quality and IT when using big data for official statistics. Workpackage 8, ESSnet Big Data, Heerlen, The Netherlands. Version 19 June 2017. (report).
Van den Brakel, J., Sohler, E., Daas, P., Buelens, B. (2017) Social media as a data source for official statistics; the Dutch Consumer Confidence Index. Survey Methodology 43 (2), pp. 183-210. (English and French version of paper).
Daas, P., Puts, M., Renssen, R. (2017) On Big Data based Statistical Inference. Abstract and poster for the 3rd UCL Workshop on the Theory of Big Data, June 26th-28th, London, UK. (abstract and poster).
Daas, P.J.H., Buelens, B. (2017) Big data, bias and ways to correct for it. Abstract for the Big Data and ethics session at the 61st World Statistics Congress (ISI 2017), July 16th-21st, Marrakech, Morocco. (abstract and slides).
Hurriyetoglu, A., Daas, P. (2018) Using Location and Dialect to Classify Twitter Users from the Netherlands and Flanders. Poster at the 28th conference of Computers in Linguistics In the Netherlands (CLIN28), January 26th, Nijmegen, The Netherlands. (poster).
Consten, A., Chavdarov, V., Daas, P.J.H., Horvat, V., Maslankowski, J., Quaresma, S., Scannapieco, M., Six, M., Tuoto, T. (2018) Report describing the IT-infrastructure used and the accompanying processes developed and skills needed to study or produce Big Data based official statistics. Deliverable 8.3, Workpackage 8, ESSnet Big Data, 5 March 2018. report).
Daas, P., Puts, M. (2018) Big data methods and techniques. Webinar for the European Master in Official Statistics (EMOS) 2018. ( slides, web page with links, and YouTube recording).
Nowicka, A., Maslankowski, J., Blaszczyk, L., Wojcik, S., Sheridan, J., Daas, P.J.H., Alves, R., Fernandes, M.J., Quaresma, S., Sozzi, A. (2018) List of potential pilots and domains with successful implementation potential for further elaboration in the second wave of pilots in 2018. Milestone 7.9, Workpackage 7, ESSnet Big Data, Version 27 April 2018. (report).
Consten, A., Chavdarov, V., Daas, P., Horvat, V., Maslankowski, J., Quaresma, S., Six, M., Tuoto, T. (2018) Report describing the quality aspects of Big Data for Official Statistics. Deliverable 8.2, Workpackage 8, ESSnet Big Data, 7 May 2018. (report).
Consten, A., Chavdarov, V., Daas, P., Horvat, V., Maslankowski, J., Quaresma, S., Six, M., Tuoto, T. (2018) Report describing the methodology of using Big Data for official statistics and the most important questions for future studies. Deliverable 8.4, Workpackage 8, ESSnet Big Data, 31 May 2018. (report).
Van Delden, A., Daas, P., ten Bosch, O., Windmeijer, D. (2018) Text analysis methods: application in official statistics (in Dutch). STAtOR 2 (juni), pp. 8-12. ( paper).
Daas, P.J.H. (2018) Big Data Methodology. Methods for Big Data in Official Statistics seminar, October 4-5, Heerlen, the Netherlands (abstract).
Van der Doef, S., Daas, P.J.H., Windmeijer, D. (2018) Identifying Innovative Companies from Their Website. BigSurv18 conference, October 27, Barcelona, Spain ( abstract).
Karlberg, M., Biffignandi, S., Daas, P.J.H., Di Consiglio, L., Holmberg, A., Lehtonen, R., Münnich, R.T., Nikic, B., Paasi, M., Shlomo, N., Silberman, R., Stoop, I. (2018) Preface. Journal of Official Statistics 34(4), pp. 797-809. DOI-link (paper).
Puts, M.J.H., Daas, P.J.H., Tennekes, M., de Blois, C. (2019) Using huge amounts of road sensor data for official statistics. AIMS Mathematics 4(1), pp. 12-25. DOI-link paper).
Daas, P. (2019) Using Big Data in Official Statistics. Presentation at the Deutsche Arbeitsgemeinschaft Statistik (DAGStat) Conference, München, 18-22 March. (abstract).
Daas, P., Harmsen, C., Offermans, M. (2019) Mezuro Quality Evalution (in Dutch: Kwaliteitstoets Mezuro). Statistics Netherlands internal report, March 2019, Statistics Netherlands, Heerlen/The Hague, The Netherlands. (report).
Daas, P., Gootzen, Y., van der Doef, S. (2019) Detecting Innovative Companies via Their Website. Abstract for the 2nd annual Symposium on Data Science and Statistics, Bellevue, WA, USA. (abstract).
Daas, P. (2019) Big Data interview (in Dutch). 4TU Carrière special, pp 28-29. (interview).
The list of publications continuous here.