Measuring Construction Activities using data from the web - New Date

Welcome to the European Statistical System Collaborative Network (ESSnet) Web Intelligence Network project, which began in April 2020 and will run until March 2025. This is a continuation of the previous ESSnet Big Data and ESSnet on Big Data II projects, which commenced in 2016. The aim of the network is to contribute to National Statistical Institutes (NSI) understanding the need to change and advance the production of national statistics. New technologies and data sources have tremendous potential to improve statistical production. They offer a way to generate statistics in an effective, accurate, and cost-effective manner.

ESSnet Web Intelligence Network Project

The webinar will cover the main steps of web data acquisition and processing illustrated with the use-case for the construction industry.

Trusted Smart Statistics – Web Intelligence NetworkBackgroundThe<a href="https://ec.europa.eu/eurostat/cros/WIN" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer"> Web Intelligence Network</a> (WIN) project is creating an environment where an array of non-traditional data sources can be accessed by members of the European Statistical System (ESS) and beyond. This project works hand in hand with the Web Intelligence Hub (WIH), a platform where data is accessed. The Web Intelligence Hub (WIH) is designed to provide National Statistical Institutes (NSIs) exposure to new data sets, enabling data sharing within a trusted, secure environment. New data sets collated from modern technologies can help produce statistics more cost-effectively by harnessing the power of the digital era. The WIH will harness technology and, in turn, allow collaboration to benefit the modernisation of official statistics. The WIH will create a community of collaboration to: <ul><li>Learn together</li><li> Share knowledge, data, and methods </li><li>Build a partnership between NSIs </li><li>Enable cooperation and sharing of statistical solutions for NSIs</li></ul>Webinar ContentIn recent years, there has been a growing exploration of incorporating internet data sources into Official Statistics within the ESSnet and WIN. In recent years, there has been a growing exploration of incorporating internet data sources into Official Statistics within the ESSnet and WIN. This webinar concentrates on using web scraping to extract data from real estate web portals for Official Statistics. Participants will be introduced to the structure of real estate portals and the importance of data from the web for Official Statistics. The example we present will cover German real estate portals. However, the approaches discussed are transferable to portals in other countries. General and practical aspects of web scraping will be discussed, including methods for identifying, extracting, and storing web-scraped data. Special attention will be paid to the HTML/XML-structure of the web pages. Participants will be able to solidify their knowledge of this through practical exercises. The webinar will conclude with a Q&amp;A. Participants will have the opportunity and are encouraged to ask questions and contribute to the discussion via Slido at various points during the webinar.1.	Introduction: <ul><li>Real estate data in Official Statistics </li><li>Web scraping in Official Statistics</li></ul>2.	Data acquisition: <ul><li>Navigating German real estate web portals</li><li>Understanding the underlying html/xml-structure of real estate web portals</li><li>Walkthrough of one example</li></ul>3.	Data preparation: <ul><li>Aggregating data meaningfully (e.g., NUTS level, address level)</li></ul>4.	Conclusion and Q&amp;ALearning ObjectivesThe primary learning objective for this webinar is for participants to understand the relevance of web scraping in Official Statistics, with particular attention given to the value of German real estate data.Furthermore, the webinar will give participants an overview on how to harvest the underlying structure of (German real estate) web portals and utilise it for effective data extraction.Concerning data analysis, participants will acquire a foundational understanding of the html/xml-structure of web portals as a basis for automatic data collection. Additionally, participants will learn how scraped data can be prepared and analysed. Special emphasis will be given to challenges concerning web scraping and working with web scraped data from German real estate web portals. Learning Outcomes<ul><li>An understanding of the relevance of web scraping data to enhance official statistics. </li><li>How to harvest the underlying structure of web portals and utilising it for data extraction</li><li>A foundation understanding of HTML/XML-structure of web portals for automatic data collection.</li></ul>Target AudienceEveryone interested in web scraping and processing web scraped data for Official Statistics. Pre-requisites<ul><li>Basic knowledge of Official Statistics</li><li>Basic knowledge of web technologies (HTML, XPath, web scraping techniques) as well as knowledge of R or Python is optional.</li></ul>Duration: Two hours Presenters:Tobias Gramlich Alexandra Ils

Biographies:Tobias Gramlich is a social scientist who worked in survey methods research for some years before joining Statistics Hesse in 2017. Since then, he has been engaged in several projects that involved gathering data from the web via web scraping. But more generally, his interest lies in privately held data and its use for Official Statistics. He describes his programming skills as “sufficient” for some pilots, but he’s happy to leave the task of professional programming to his much more experienced colleagues. Alexandra Ils is a data scientist who started working in Official Statistics in 2021. Since then, she has been involved in the ESSnet Smart Surveys project and is an active member of the ESSnet WIN. At her current position at Statistics Hesse, her primary focus lies in web scraping as well as extracting information from web-scraped text using various NLP methods. Privacy noticeThe data you provide will be used by the Office for National Statistics to contact you in connection with the above event and to understand the attendance level and interest in the event. ONS will store your data securely on our IT infrastructure and your data will not be shared with other organisations. Personal data will be kept until the end of the project (March 2025) and then deleted. From time to time, we will contact you to keep you up to date with new events we have planned.If you have a question about how we process your personal data and you can’t find the answer on our website, you can contact our Data Protection Officer at DPO@statistics.gov.uk or 0845 6013034. To find out more about your rights under data protection legislation, or how to raise a concern with the Information Commissioner, see our website www.ons.gov.uk/dataprotection or the Information Commissioners Office at https://ico.org.uk.Your data will be processed by Eventbrite – please read their privacy policy.

Our {communityGuidelinesLink} describe the sort of content we prohibit on Eventbrite. If you suspect an event may be in violation, you can report it to us so we can investigate.

To report other categories of prohibited or illegal content, submit {link}

Measuring Construction Activities using data from the web - New Date

More events from ESSnet Web Intelligence Network Project

Discover more events from ESSnet Web Intelligence Network Project, from Science & Tech to other experiences you might love.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.

Measuring Construction Activities using data from the web - New Date

More events from ESSnet Web Intelligence Network Project

Discover more events from ESSnet Web Intelligence Network Project, from Science & Tech to other experiences you might love.

You might also like...

Browse more events with different dates, prices, and formats to find your next great experience.

Still looking for the right event?

Explore all online events to browse and filter by date, category, and more.