{"title":"Epistenet:促进程序化访问和处理语义相关的移动个人数据","authors":"Sauvik Das, Jason Wiese, Jason I. Hong","doi":"10.1145/2935334.2935349","DOIUrl":null,"url":null,"abstract":"Effective use of personal data is a core utility of modern smartphones. On Android, several challenges make developing compelling personal data applications difficult. First, personal data is stored in isolated silos. Thus, relationships between data from different providers are missing, data must be queried by source of origin rather than meaning and the persistence of different types of data differ greatly. Second, interfaces to these data are inconsistent and complex. In turn, developers are forced to interleave SQL with Java boilerplate, resulting in error-prone code that does not generalize. Our solution is Epistenet: a toolkit that (1) unifies the storage and treatment of mobile personal data; (2) preserves relationships between disparate data; (3) allows for expressive queries based on the meaning of data rather than its source of origin (e.g., one can query for all communications with John while at the park); and, (4) provides a simple, native query interface to facilitate development.","PeriodicalId":420843,"journal":{"name":"Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Epistenet: facilitating programmatic access & processing of semantically related mobile personal data\",\"authors\":\"Sauvik Das, Jason Wiese, Jason I. Hong\",\"doi\":\"10.1145/2935334.2935349\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Effective use of personal data is a core utility of modern smartphones. On Android, several challenges make developing compelling personal data applications difficult. First, personal data is stored in isolated silos. Thus, relationships between data from different providers are missing, data must be queried by source of origin rather than meaning and the persistence of different types of data differ greatly. Second, interfaces to these data are inconsistent and complex. In turn, developers are forced to interleave SQL with Java boilerplate, resulting in error-prone code that does not generalize. Our solution is Epistenet: a toolkit that (1) unifies the storage and treatment of mobile personal data; (2) preserves relationships between disparate data; (3) allows for expressive queries based on the meaning of data rather than its source of origin (e.g., one can query for all communications with John while at the park); and, (4) provides a simple, native query interface to facilitate development.\",\"PeriodicalId\":420843,\"journal\":{\"name\":\"Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2935334.2935349\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th International Conference on Human-Computer Interaction with Mobile Devices and Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2935334.2935349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Epistenet: facilitating programmatic access & processing of semantically related mobile personal data
Effective use of personal data is a core utility of modern smartphones. On Android, several challenges make developing compelling personal data applications difficult. First, personal data is stored in isolated silos. Thus, relationships between data from different providers are missing, data must be queried by source of origin rather than meaning and the persistence of different types of data differ greatly. Second, interfaces to these data are inconsistent and complex. In turn, developers are forced to interleave SQL with Java boilerplate, resulting in error-prone code that does not generalize. Our solution is Epistenet: a toolkit that (1) unifies the storage and treatment of mobile personal data; (2) preserves relationships between disparate data; (3) allows for expressive queries based on the meaning of data rather than its source of origin (e.g., one can query for all communications with John while at the park); and, (4) provides a simple, native query interface to facilitate development.