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Surv."],"published-print":{"date-parts":[[2023,5,31]]},"abstract":"<jats:p>Recent industrial and academic research has focused on data-driven analytics with smartphones by collecting user interaction, context, and device systems data through Application Programming Interfaces (APIs) and sensors. The Android operating system provides various APIs to collect such mobile usage and sensor data for third-party developers. Usage Statistics API (US API) and Accessibility Service API (AS API) are representative Android APIs for collecting app usage data and are used for various research purposes, as they can collect fine-grained interaction data (e.g., app usage history and user interaction type). Furthermore, other sensor APIs help to collect a user\u2019s context and device state data, along with AS\/US APIs. This review investigates mobile usage and sensor data-driven research using AS\/US APIs by categorizing the research purposes and the data types. In this article, the surveyed studies are classified as follows: five themes and 21 subthemes and a four-layer hierarchical data classification structure. This allows us to identify a data usage trend and derive insight into data collection according to research purposes. Several limitations and future research directions of mobile usage and sensor data-driven analytics research are discussed, including the impact of changes in the Android API versions on research, the privacy and data quality issues, and the mitigation of reproducibility risks with standardized data typology.<\/jats:p>","DOI":"10.1145\/3530814","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T12:44:24Z","timestamp":1650372264000},"page":"1-38","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["A Systematic Survey on Android API Usage for Data-driven Analytics with Smartphones"],"prefix":"10.1145","volume":"55","author":[{"given":"Hansoo","family":"Lee","sequence":"first","affiliation":[{"name":"School of Computing, KAIST, Yuseong-gu, Daejeon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3513-0660","authenticated-orcid":false,"given":"Joonyoung","family":"Park","sequence":"additional","affiliation":[{"name":"Graduate School of Knowledge Service Engineering, KAIST, Yuseong-gu, Daejeon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1888-1569","authenticated-orcid":false,"given":"Uichin","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Computing, KAIST, Yuseong-gu, Daejeon, South Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,12,3]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2632048.2632100"},{"key":"e_1_3_2_3_2","unstructured":"Stadd Allison. 2013. 79% of people 18\u201344 have their smartphones with them 22 hours a day. 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