Driving Open Source Adoption in Government | Vytas Vaiciulis | Data Science Hangout
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This week's guest was Vytas Vaiciulis, Lead Data Scientist at the Central Statistics Office (CSO) Ireland!
Some topics covered in this week's Hangout were leading a large-scale SAS-to-R migration in a government statistics office, building and scaling an analytics and AI section from a team of one to thirteen, modernizing official statistics with new data sources (administrative, transactional, and satellite/GIS data), and driving open source adoption in a highly regulated public sector environment.
One community member asked: I work in government and have faced very slow adoption and acquisition of open source tools. It took nine months for my agency to approve Positron for use. Do you encounter the same issue, and if so, how have you addressed that inertia?
Vytas answered (paraphrased): It's become easier because open source is being embraced globally, and organizations like the UN are championing it at a very high level, which creates helpful top-down pressure. When he began, though, that wasn't the case. The main concern was always support, since the office couldn't adopt something without official backing. His strategy throughout has been to "show the value," repeatedly and explicitly. That's where Posit came in: they wanted the flexibility of open source (all the R libraries) but also wanted support, so they use supported offerings, right down to running Red Hat for a supported Linux base. Demonstrating value clearly, combined with buy-in from the top, is what overcomes the inertia.
Resources mentioned in the video and chat:
🔗 Eurostat Database → https://ec.europa.eu/eurostat/data/database
🔗 European Union Open Data Portal → https://data.europa.eu/en
🔗 The Use of R in Official Statistics (uRos) Conference → https://r-project.ro/conference2026.html
🔗 Tidy Dev Day 2026 Announcement → https://opensource.posit.co/blog/2026-06-25_tidy-dev-day-2026/
🔗 varunayanR – R package to process ERA5 and IMD weather data → https://github.com/saketlab/varunayanR
🔗 Shiny Accessibility Sample App (Abigail Stamm) → https://github.com/ajstamm/shiny-a11y-app
🔗 Oregon Health Authority Overdose Dashboard (Shiny example) → https://oregoninjurydata.shinyapps.io/overdose/
🔗 "How to Find a Side Project" – Present of Coding blog (Abigail Haddad) → https://presentofcoding.substack.com/p/how-to-find-a-side-project
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Follow Us Here:
Website: https://www.posit.co
Hangout: https://pos.it/dsh
The Lab: https://pos.it/dslab
LinkedIn: https://www.linkedin.com/company/posit-software
Bluesky: https://bsky.app/profile/posit.co
Thanks for hanging out with us! 💛
Timestamps:
00:00 Introduction
02:21 "How did you get to CSO?"
03:28 "Is statistics your background?"
04:19 "Could you tell us a little bit about what CSO does, and give an example of the types of data that you work with and see on a daily or weekly basis?"
08:15 "What programming languages do you use in your work, and was that the same language you studied in school?"
11:05 "Did you have any pushback on implementing or growing the statistical analysis team, and how did you convince people on the value of statistics?"
15:01 "How are you incorporating geospatial data into the statistics and data that you were already processing? Can you give us a case example of how you might put it in?"
18:01 "For the administrative data, how easy is it for other organizations to provide the needed information?"
20:11 "How did you find communicating the uncertainty and interpretation of statistical analysis?"
22:57 "Do you work with other governmental departments in Ireland?"
24:04 "Which books, newsletters, and the like do you follow?"
27:10 "Do you use non-traditional data, such as sentiment analysis of social media?"
29:50 "Do you analyze any free text data? And if so, how do you deal with the poor data quality that is always present in free text data?"
32:28 "I work in government, and I've faced very slow adoption and acquisition of open source tools. It took nine months for my agency to approve Positron for use. Do you encounter the same issue, and if so, how have you addressed that inertia?"
34:53 "How many SAS users did you have to convert?"
38:39 "The U.S. has multiple agencies that do statistics. What do you all do in Ireland with that respect, and do you find that doing it that way is better or worse in terms of maintaining methodology and code bases and things of that nature?"
41:21 "What are some of the unique challenges and security limitations involved with integrating AI and other AI-like systems into your infrastructure?"
43:22 "Do you use Shiny?"
45:49 "Do you have issues recoding old data to new data standards?"
48:43 "Do you have a piece of career advice that maybe you wish you knew before you got into the data field, or that you think would be helpful for others?"
This week's guest was Vytas Vaiciulis, Lead Data Scientist at the Central Statistics Office (CSO) Ireland!
Some topics covered in this week's Hangout were leading a large-scale SAS-to-R migration in a government statistics office, building and scaling an analytics and AI section from a team of one to thirteen, modernizing official statistics with new data sources (administrative, transactional, and satellite/GIS data), and driving open source adoption in a highly regulated public sector environment.
One community member asked: I work in government and have faced very slow adoption and acquisition of open source tools. It took nine months for my agency to approve Positron for use. Do you encounter the same issue, and if so, how have you addressed that inertia?
Vytas answered (paraphrased): It's become easier because open source is being embraced globally, and organizations like the UN are championing it at a very high level, which creates helpful top-down pressure. When he began, though, that wasn't the case. The main concern was always support, since the office couldn't adopt something without official backing. His strategy throughout has been to "show the value," repeatedly and explicitly. That's where Posit came in: they wanted the flexibility of open source (all the R libraries) but also wanted support, so they use supported offerings, right down to running Red Hat for a supported Linux base. Demonstrating value clearly, combined with buy-in from the top, is what overcomes the inertia.
Resources mentioned in the video and chat:
🔗 Eurostat Database → https://ec.europa.eu/eurostat/data/database
🔗 European Union Open Data Portal → https://data.europa.eu/en
🔗 The Use of R in Official Statistics (uRos) Conference → https://r-project.ro/conference2026.html
🔗 Tidy Dev Day 2026 Announcement → https://opensource.posit.co/blog/2026-06-25_tidy-dev-day-2026/
🔗 varunayanR – R package to process ERA5 and IMD weather data → https://github.com/saketlab/varunayanR
🔗 Shiny Accessibility Sample App (Abigail Stamm) → https://github.com/ajstamm/shiny-a11y-app
🔗 Oregon Health Authority Overdose Dashboard (Shiny example) → https://oregoninjurydata.shinyapps.io/overdose/
🔗 "How to Find a Side Project" – Present of Coding blog (Abigail Haddad) → https://presentofcoding.substack.com/p/how-to-find-a-side-project
â–º Subscribe to Our Channel Here: https://bit.ly/2TzgcOu
Follow Us Here:
Website: https://www.posit.co
Hangout: https://pos.it/dsh
The Lab: https://pos.it/dslab
LinkedIn: https://www.linkedin.com/company/posit-software
Bluesky: https://bsky.app/profile/posit.co
Thanks for hanging out with us! 💛
Timestamps:
00:00 Introduction
02:21 "How did you get to CSO?"
03:28 "Is statistics your background?"
04:19 "Could you tell us a little bit about what CSO does, and give an example of the types of data that you work with and see on a daily or weekly basis?"
08:15 "What programming languages do you use in your work, and was that the same language you studied in school?"
11:05 "Did you have any pushback on implementing or growing the statistical analysis team, and how did you convince people on the value of statistics?"
15:01 "How are you incorporating geospatial data into the statistics and data that you were already processing? Can you give us a case example of how you might put it in?"
18:01 "For the administrative data, how easy is it for other organizations to provide the needed information?"
20:11 "How did you find communicating the uncertainty and interpretation of statistical analysis?"
22:57 "Do you work with other governmental departments in Ireland?"
24:04 "Which books, newsletters, and the like do you follow?"
27:10 "Do you use non-traditional data, such as sentiment analysis of social media?"
29:50 "Do you analyze any free text data? And if so, how do you deal with the poor data quality that is always present in free text data?"
32:28 "I work in government, and I've faced very slow adoption and acquisition of open source tools. It took nine months for my agency to approve Positron for use. Do you encounter the same issue, and if so, how have you addressed that inertia?"
34:53 "How many SAS users did you have to convert?"
38:39 "The U.S. has multiple agencies that do statistics. What do you all do in Ireland with that respect, and do you find that doing it that way is better or worse in terms of maintaining methodology and code bases and things of that nature?"
41:21 "What are some of the unique challenges and security limitations involved with integrating AI and other AI-like systems into your infrastructure?"
43:22 "Do you use Shiny?"
45:49 "Do you have issues recoding old data to new data standards?"
48:43 "Do you have a piece of career advice that maybe you wish you knew before you got into the data field, or that you think would be helpful for others?"
