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| オンラインセンサーデータ収集× | Web Scraping× | |
|---|---|---|
| 分野 | 調査方法論 | 調査方法論 |
| 系統 | Process / pipeline | Process / pipeline |
| 提唱年≠ | Late 1990s–early 2000s (Internet of Things paradigm formalized ~2000) | Late 1990s–2000s |
| 提唱者≠ | Akyildiz et al. (foundational survey); DARPA SensIT programme (~2000) | Early internet practitioners; systematised in research contexts from the late 1990s onward |
| 種類≠ | Quantitative / mixed-mode data collection technique | Automated digital data collection technique |
| 原典≠ | Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 38(4), 393–422. DOI ↗ | Mitchell, R. (2018). Web Scraping with Python: Collecting More Data from the Modern Web (2nd ed.). O'Reilly Media. ISBN: 978-1491985571 |
| 別名 | networked sensor data collection, IoT data collection, remote sensor monitoring, wireless sensor data acquisition | web harvesting, screen scraping, web crawling, automated data extraction |
| 関連≠ | 6 | 5 |
| 概要≠ | Online sensor data collection is a systematic technique for gathering continuous or event-triggered measurements from physical sensors that transmit readings in real time over a network — the internet, a local wireless network, or a dedicated IoT protocol. It is used widely in environmental monitoring, health informatics, smart-city research, industrial systems, and behavioral science to capture objective, high-frequency data without requiring manual recording by participants or observers. | 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. |
| ScholarGateデータセット ↗ |
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