Salīdzināt metodes

	Attālinātā tīmekļa datu ieguve	Tīmekļa datu ieguve
Nozare	Aptauju metodoloģija	Aptauju metodoloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2000s–2010s (cloud infrastructure era)	Late 1990s–2000s
Autors	Distributed computing and web automation communities	Early internet practitioners; systematised in research contexts from the late 1990s onward
Tips	Automated remote data collection technique	Automated digital data collection technique
Pirmavots	Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571	Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571
Citi nosaukumi	cloud web scraping, server-side scraping, remote automated data extraction, distributed web scraping	web harvesting, screen scraping, web crawling, automated data extraction
Saistītās	3	5
Kopsavilkums	Remote web scraping is a data collection approach in which automated scripts or bots harvest publicly accessible web content — text, tables, metadata, or links — running on remote servers or cloud infrastructure rather than on the researcher's local machine. This separation allows continuous, large-scale, or geographically distributed crawling that local setups cannot sustain, making it particularly suited to longitudinal or high-volume data collection tasks.	Web scraping is a computational data collection technique in which software automatically retrieves and extracts structured or semi-structured content from websites. Widely used in social science, computational linguistics, economics, and information science, it enables researchers to assemble large datasets from publicly accessible web sources — such as news archives, social media platforms, government portals, and online marketplaces — that would be impractical to collect manually.