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The annual conference on the Use of R in Official Statistics will take place at the premises of Statistics Austria, 6-8 May 2020. The conference consists of one tutorial day (6 May 2020) and two days of scientific conference (7-8 May 2020).
We are also excited to announce an “unconference” “Use of R in Official Statistics” back-to-back with the uRos2020 conference, scheduled on 4-5 May 2020.
Over the last two decades R has become the lingua franca for statisticians, methodologists and data scientists worldwide. The reasons why the official statistics community is rapidly embracing R are clear: it has an active worldwide community of users, there is wide support from the industry and it combines a vast amount of functionalities for data preparation, methodology, visualisation and application building. Moreover, R-based software is exchanged through strictly enforced technical standards: “R is probably the most thoroughly validated statistics software on Earth.” – Uwe Ligges, CRAN maintainer (useR!2017).
Finally, R is a free (libre) Open Source software product, making it an ideal environment for sharing, collaboration and industrialising official statistics.
The annual event “use of R in Official Statistics” started as a local conference at the Statistical Office of Romania in 2013, with the first international edition being held at that same office in 2014. In 2018, Statistics Netherlands hosted the sixth edition of this event, which brought together official statisticians, scientists, and prominent members of the R community to share ideas on using and developing R tools in the area of official statistics.
Now it is Statistics Austria’s turn to host this stimulating meeting and we very much look forward to welcoming you to Vienna in 2020.
You can browse all the accepted abstracts at https://uros.hopto.org.
We are happy to have three excellent keynote talks by Isabel Molina Peralta, Matthias Templ and Kurt Hornik.
is associate professor at the Department of Statistics of Universidad Carlos III de Madrid since 2009. She got her Ph. D. in Statistics and Operations Research in 2003 at Universidad Miguel Hernández de Elche. She has published more than 30 papers in peer-reviewed statistical journals, most of them on small area estimation, and has received several awards. She is currently associate editor for the scientific journals “Survey Methodology” and “Journal of Survey Statistics and Methodology”. She is co-author, together with J.N.K. Rao, of the Wiley book “Small area estimation, 2nd Ed.”
“Small area estimation using R, with application to poverty mapping.”
Small area estimation is a promising, but also well established and well developed family of methods to gain insights on detailed domains or areas. Not widely used in statistical offices yet, available resources in R provide an opportunity to change that. Existing R packages designed for small area estimation with a special focus on the applicability for poverty mapping are reviewed. Applications to poverty mapping are presented to illustrate some of the available functions.
made his PhD in technical mathematics and the venia legendi (habilitation) in statistics at the Vienna University of Technology (TU Wien). He was associated professor at the TU Wien and consultant at the Palacky University Olomouc. He is employed by the Institute for Data Analysis and Process Design at the Zurich University of Applied Sciences, where he teaches and research in the area of statistical modelling and data science.
His main research interests include computational statistics, compositional data analysis, imputation and statistical disclosure control. He published more than 50 papers in well-known indexed scientific journals and he is author of several R packages.
Matthias Templ is editor-in-chief of the Austrian Journal of Statistics.
“Functional data analysis in Bayes Spaces with an Application to spatio-temporal population data”
Probability density functions are frequently used to characterize the distributional properties of large-scale database systems. As functional compositions, densities carry primarily relative information. As such, standard methods of functional data analysis (FDA) are not appropriate for their statistical processing and thus a compositional alternative is proposed. The aim of this presentation is to outline a concise methodology for functional principal component analysis of densities based on the geometry of the Bayes space B2 of functional compositions. Advances of the proposed approach are demonstrated using a real-world example of population pyramids in Upper Austria. For compositional analysis we also introduce the R package robCompositions.
is the head of the Institute for Statistics and Mathematics and the Research Institute for Computational Methods at WU Vienna. His main research interests include statistical computing, statistical and machine learning and quantitative risk management. He is a member of the R Development Core Team and hosting the central CRAN server at WU.
Jaap Walhout, researcher at Statistics Netherlands
The data.table package is well known for its speed and memory efficiency when manipulating data. A bit less well known are the powerful capabilities of the data.table-package for joining datasets. The tutorial will start with a short refresher of data.table’s syntax. After this short introduction the following topics will explained:
Participants are expected to have read the data.table vignettes “Introduction to data.table” and “Reference semantics” (see: http://r-datatable.com).
Participants should bring their own laptops with a recent version of R (3.6+) and a recent version of data.table (1.12.8+)
Peter Meißner, Senior Technical Consultant at virtual7 GmbH
Over the last decade the internet has become a prominent source of information for everyone. While the internet is not without challenges when used as a source of data its omnipresence in everyday live, industry, social activity, tourism, commerce and many-many more areas opens the door to a myriad of possible applications some of them yet unthought of.
The tutorial will cover how to get started in the realm of web data collection by shedding some light on the:
- general technologies involved
- best practice R packages to use
- importing, processing, and extracting data
- some general decisions to make when starting a web scraping project
The tutorial will assume that participants have basic understanding of using R but requires no prior knowledge in the field of web technologies.
Marco Ballin, Italian National Statistical Institute and Giulio Barcaroli, Independent Consultant, former Italian National Statistical Institute
The aim of this tutorial is to enable the participants to learn how to use the R package “SamplingStrata” in order to optimize the design of stratified samples. The package offers an approach for the determination of the best stratification of a sampling frame, the one that ensures the minimum sample cost under the condition to satisfy precision constraints in a multivariate and multi-domain case. This approach is based on the use of the genetic algorithm: each solution (i.e. a particular partition in strata of the sampling frame) is considered as an individual in a population; the fitness of all individuals is evaluated applying the Bethel algorithm to calculate the sampling size satisfying precision constraints on the target estimates. Functions in the package allows to: (a) prepare necessary inputs and check their validity; (b) perform the optimization step choosing the values of the most important parameters; (c) assign the optimized strata labels to the sampling frame; (d) select a sample from the new frame accordingly to the best allocation; (e) test the compliance of the design to the given precision constraints. The package also allows to consider the anticipate variance when the survey target variables are not available in the frame, but only proxy ones. Hints on recent extensions to spatial sampling will be given.
Valentin Todorov, United Nations Industrial Development Organization (UNIDO)
The official statistics are central in setting policies and measuring their outcomes and the national statistical offices (NSOs) are responsible for carrying out the national statistical programs by setting the standards, designing and implementing large-scale data collection programs, guaranteeing the quality, reliability, and availability of official statistics at country level. The collected data are further passed to international organization to facilitate cross country comparison and analysis. The accessibility dimension of data quality reflects the ease of attainability of the data which is the extent to which the data is easily accessible for the required by the user tasks. To improve on this dimension many international organizations but also some of the NSOs provide sophisticated APIs for accessing, navigating, processing and analysing the data available on their data portals. For many of these APIs R packages exist, to facilitate the access and manipulation of data: package ‘eurostat’ provides tools to download data from the Eurostat database together with search and manipulation utilities; ‘rilostat’ provides tools to access, download and work with the data contained in ILOSTAT, the ILO Department of Statistics’ online database; ‘FAOSTAT’ helps to automatically download data from FAOSTAT and WDI, and to harmonize different data sources under a common country coding system ,‘indstat’ allows access to the unique industrial statistics database maintained by UNIDO. While this list is not complete (‘comtrade’, ‘cbsodataR’, ‘ecb’ , ‘OECD’, ‘acs’, ‘sorvi’, ‘inegiR’ are further packages of this class), the purpose of all these packages is to help the end user easily find, access and analyse official statistics data.
In this tutorial we will consider, through a number of examples the approaches implemented in some of these packages. The objective of the tutorial is twofold:
(i) to help end users navigate through the available APIs for accessing and analyzing official statistics through R and
(ii) to give advice to developers for implementing such APIs and the corresponding R packages.
This course is designed for people who never used R but are familiar with basic statistical concepts. It aims to teach basics of the R language and also give an overview about important packages. The topics include data import, data cleaning and visualization as well as automatic reporting. The course will also contain exercises, where participants can practice the learned concepts. In addition participants will be introduced to general purpose packages such as rmarkdown and ggplot2 as well as a guide on how to find high quality packages for official statistics.
Trainers: Gregor De Cillia and Johannes Gussenbauer (Statistics Austria)
Participation in the course is limited to participants of the uRos2020 conference and the registration will be together with the conference registration. The fee for the R Course is 200 €.
4 May 2020: 09:30 – 16:30
5 May 2020: 09:30 – 16:30
The programme will start on 6 May 2020 at 9:30 and on 7 May 2020 at 10:00. We plan to end the conference on 8 May 2020 15:30.
More information can be found at the unconfUROS github page.
Some ideas have been developed, but please submit your own ideas through the github repository until 31st of March 2020:
Ideas are welcome, also if you do not want to participate actively.
We would like participants to have some experience with R programming and the ability to work with git/GitHub.
If you are interested in participating, please contact us by e-mail to: uRos2020 [at] statistik.gv.at with a short summary of your motivation and your experience in R.
Please register through this form
The registration fee for the conference is 210 € (tutorial trainers are exempt from this registration fee).
We have limited capacities, so please register early. A couple of days after your registration you will receive an invoice by email to the email address provided in the registration form which must be paid in order to confirm your registration.
We are cordially inviting you to submit papers to and attend the International Conference The Use of R in Official Statistics – uRos2020 until 15 January 2020.
There will be two kind of presentations “contributed presentations” with roughly 15 minutes time slots and “lighting presentations” with 5 minutes time slots and automatic cycling through the slides. Please indicate your preference, but the scientific committee will finally assign the presentations into the two categories.
The purpose of the conference is to provide a public forum for researchers from academia and institutes of official (government) statistics to present, exchange ideas and discuss developments in state-of-the-art statistical software commonly used in applied economics and statistics. The most focused debates are expected to be on the use of R in Official Statistics.
The topics covered by the conference are the following:
* R in census
* Sampling and estimation
* R in organization
* Data cleaning
* R in production: data analysis
* Methods for official statistics
* Shiny applications
* Time series
* Report and GUI programming
* R in production: automation
* Big data
* Dissemination and visualization
The participants are kindly asked to submit the abstract via e-mail to: uRos2020 [at] statistik.gv.at preferably as plain text or Word or PDF, there is no template for the abstract submission.
Tutorials will be 3 hours in length. Tutorials will be presented during the first day, during parallel sessions in the morning and in the afternoon. The scope of the tutorials comprises the whole statistical production process of official statistics. Deadline for tutorial submission is 15 January 2020.
Authors with an accepted abstract can submit a full-length paper for a journal special issue as described hereinafter. A maximum of ten selected research papers will be published in a special issue of the Romanian Statistical Review. Publications are subjected to passing the standard peer review process.
Papers should be submitted no later than 15 June 2020 to the uRos2020 secretariat via e-mail to: uRos2020 [at] statistik.gv.at
Please make sure to follow the RSR author guidelines.
The Romanian Statistical Review is included in the Web Of Science Core Collection - Emerging Sources Citation Index (ESCI), a Clarivate Analytics database. It aims to provide a favourable space for exchange of ideas and a challenge at the same time. Any paper that can contribute to the understanding of statistics as a science is welcome. It is open-access without any fees.
We look forward to welcoming you to Vienna for uRos2020! The conference secretariat can be reached via: uRos2020 [at] statistik.gv.at.
The conference will take place at Statistics Austria’s premises located at Guglgasse 13,1110 Vienna, see https://goo.gl/maps/dnbDiJfkVwNar5q46.
Vienna has a wide choice of hotels in different price categories. We do not have special arrangements with any hotels.
The hotel closest to our office is Hotel Roomz (https://www.roomz-hotels.com/roomz-vienna) and a cheaper second option within walking distance is Hotel ibis budget Sankt Marx (https://goo.gl/maps/WDvSjZndKyj33k597).
How to reach us
Underground 3 (orange line) will take you directly to us, station “Gasometer”.
From the airport you can use the “City Airport Train – CAT” or the (slower but cheaper) train S7 to the station “Landstraße – Wien Mitte” and from there the U3 to “Gasometer”.
Alternatively take the inexpensive “Airliner” bus (https://air-liner.at/en) to “Erdberg” (U3 underground station) and either walk to Statistics Austria (10min.) or take U3 to “Gasometer” (one station after Erdberg).
Info about public transportation in Vienna
Vienna has a well-developed public transport system. Please find details at the transport company’s webpage https://www.wienerlinien.at/eportal3/ep/tab.do?tabId=0.
If you have any questions, please do not hesitate to contact the secretariat by e-mail to: uRos2020 [at] statistik.gv.at
Organisers, speakers, registered participants, and sponsors of the uRos conference and/or unconfUROS hackathon, as well as persons or organizations following and discussing the conference through (social) media or internet are required to follow this Code of Conduct. We shall refer to the combined group as ‘participants’ of the uRos conference.
Privacy: participants respect each other’s privacy. In particular it is not allowed to systematically gather information on organisers, speakers and (registered) participants, including but not limited to personal life, professional position, political views, social media outings, open source contributions, or pictures.
Open: participants are open to collaboration, whether it’s on projects, working groups, packages, problems, or otherwise. Participants are receptive to constructive comment and criticism, as the experiences and skill sets of other participants contribute to the whole of our efforts. Participants are accepting of anyone who wishes to take part in their activities, fostering an environment where all can participate and everyone can make a difference.
Respectful: participants are respectful of others, their positions, their skills, their commitments, and their efforts. They are respectful of the volunteer efforts that permeate the R community. In the case of disagreement, participants are courteous in raising their issues. Participants are attentive in communication, whether in person or online, and tactful when approaching differing views. They refrain from demeaning, discriminatory, or harassing behaviour and speech.
Considerate: participants are considerate of their peers — fellow uRos participants. They are thoughtful when addressing the efforts of others, keeping in mind that oftentimes the labour was completed simply for the good of the community.
In case of violation, participants may be removed from the premises or blocked from communication with the organization. Where relevant, the proper authorities or organizations will be informed of inappropriate behaviour.
This chaptersets out the terms and conditions between organisers and you when you register as a participant for this conference and you are agreeing to comply with these terms and conditions.
Please read these terms and conditions carefully.
DECLARATION OF CONSENT
I hereby give my consent for organisers to collect, process and use my personal data for the purposes related to my participation to uRos Conference events and for any other use to which I have consented. The data that can be collected consist of:
USE OF PERSONAL DATA
Organisers will not sell your personal data.
The processing of the respective personal data involves communication with the authors in order to publish the studies, publication of the accepted studies in journals and indexation of the journal in international databases.
I hereby give my consent to organisers to use my personal data for the following purposes:
The usage of my personal data must comply with the requirements of the Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons about the processing of personal data and on the free movement of such data (“GDPR“).
You can ask organisers at any time to have an unrestricted access to your personal data and exercise your rights to: consult, modify, erase, export your personal information, by sending a message to the conference secretariat e-mail: uRos2020 [at] statistik.gv.at.
You will find all data protection information (name and address of Statistics Austria as controller within the meaning of the GDPR, name and address of the data protection officer of Statistics Austria as well as information on the data protection rights and rights of complaint to which you are entitled) in the data protection information about this website.