قارن الطرق

	جمع البيانات المستند إلى واجهة برمجة التطبيقات (API) والذي تم اختباره تجريبيًا	جمع البيانات المستند إلى واجهة برمجة التطبيقات
المجال	منهجية المسح	منهجية المسح
العائلة	Process / pipeline	Process / pipeline
سنة النشأة	2000s–2010s	2000s–2010s (formalized as a research method)
صاحب الطريقة	Convergence of survey pilot-testing tradition (Presser et al., 2004) and computational social science API methods (Salganik, 2018)	Emerged from computational social science and web 2.0 platform practices
النوع	Applied data-collection variant	Digital data collection technique
المصدر التأسيسي	Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 978-0691158648	Salganik, M. J. (2018). Bit by Bit: Social Research in the Digital Age. Princeton University Press. ISBN: 9780691158648
الأسماء البديلة	pilot API data collection, pre-tested API harvesting, API data collection pilot study, pilot-validated API scraping	API data harvesting, API-driven data collection, programmatic data retrieval, API research data collection
ذات صلة	4	5
الملخص	Pilot-tested API-based data collection is a structured digital data-gathering approach in which a researcher designs an API query or harvesting script and then runs a small-scale trial before executing the full collection. The pilot phase exposes authentication issues, rate-limit constraints, schema inconsistencies, and coverage gaps, enabling targeted refinements that protect the integrity and completeness of the final dataset. It bridges the software-engineering practice of integration testing with the social-science tradition of instrument pre-testing.	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.