Porovnať metódy

	Pilotné testovanie zberu dát zo senzorov	Zber dát prostredníctvom API
Odbor	Metodológia dotazníkových prieskumov	Metodológia dotazníkových prieskumov
Rodina	Process / pipeline	Process / pipeline
Rok vzniku	1990s–2000s (formalized with proliferation of digital sensing technologies)	2000s–2010s (formalized as a research method)
Tvorca	General research methods practice; sensor pilot testing codified through IoT and environmental monitoring literature	Emerged from computational social science and web 2.0 platform practices
Typ	Data collection procedure with pre-deployment validation phase	Digital data collection technique
Pôvodný zdroj	Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). Sage Publications. ISBN: 978-1506386706	Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648
Ďalšie názvy	sensor pilot study, sensor pre-deployment testing, instrument validation with sensors, sensor calibration pilot	API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection
Príbuzné	6	5
Zhrnutie	Pilot-tested sensor data collection is a structured data gathering approach in which sensor instruments — hardware or software-based devices that measure physical, environmental, physiological, or behavioral signals — are deployed in a small-scale trial before the main study. The pilot phase verifies sensor accuracy, communication reliability, data format consistency, and placement adequacy, allowing researchers to identify and correct technical problems before full-scale data collection begins.	API-based data collection is a systematic technique in which a researcher sends structured requests to an application programming interface to retrieve data automatically from digital platforms, databases, or services. It is the primary method used in computational social science to gather large-scale social media records, government open data, financial data streams, and scientific repository content in machine-readable formats such as JSON or XML, enabling reproducible and scalable data acquisition that manual collection cannot match.