CAREER: Querying Beyond Keyboards: Gesture-driven Querying of Databases

无论是普通用户还是高级用户，使用非传统方法(例如，手势)与数据交互的计算设备正迅速变得越来越流行。这种情况下的应用程序和用户界面提出了一组完全不同的期望，而传统数据库并不能很好地适应：用户已经开始期望响应时间是可预测的，并且几乎是即时的。诸如加速滚动之类的交互对底层数据库造成了截然不同的工作负载，并且可能会使它们不堪重负。没有键盘，一些数据库查询操作就不那么简单了：手势输入没有明确的方法可以映射到传统查询。传统的查询-结果模型不足以处理手势交互的细微差别，如快速变化的输入和界面的敏感度。传统的数据库查询范式需要从根本上重新思考，以支持手势交互。PI将为交互和手势工作负载处理数据库堆栈中缺失的关键组件，统称为“GestureDB”。这项拟议的研究将使一种全新的设备和用户能够访问数据交互。手势交互正在迅速普及，其中数据访问是关键，但键盘访问有限，例如残疾用户和工厂车间和实验室等环境。GestureDB以交互为中心的设计也有望在生物信息学和大数据分析等数据驱动领域产生革命性影响。此外，GestureDB的互动性将使其成为一个创造性地与学生和公众互动的极好平台。借助GestureDB，PI将首先构建一个新的查询模型，该模型具有“查询意图”的概念，并具有表现力的“手势查询语言”，允许用户使用手势作为唯一的数据交互模式。其次，他将研究“意图解释”的方法，允许系统在手势期间更好地识别用户的查询意图。第三，PI将研究“反馈生成”的方法，允许系统在手势发音期间提供反馈。所有组件都将在设计时考虑互动性，以保持低延迟循环并确保流畅的用户体验。虽然几十年来对数据库的研究一直在提高数据库的性能，但重点通常是大规模的管道，而不是最终用户。人机交互和可视化的研究最近一直在研究用户界面的数据管理概念。GestureDB弥合了这一鸿沟，并采用了一种新的方法来实现交互的手势数据查询。该提案中提出的想法并不局限于手势交互：其中几个也可以用来解决传统数据库查询中典型的困难问题。启用手势交互将改变默认的、传统的数据库临时查询模式。提出的解决方案可以在查询界面、查询意图解释和反馈生成方面开辟几个新的研究途径，并将启发底层数据库堆栈的所有级别的研究。建议的机制将能够建立高度交互的应用程序，并对重新思考未来的数据库系统产生重大影响。有关更多信息，请参阅项目网站：http://interact.osu.edu/gesturedb

Computing devices that use non-traditional methods (e.g., gestures) to interact with data are rapidly becoming more popular, for both casual and power users. Applications and user interfaces for such cases pose a fundamentally different set of expectations that traditional databases are not well-suited for: users have come to expect response-times that are predictable and nearly instantaneous. Interactions such as accelerated scroll pose drastically different workloads to underlying databases and may overwhelm them. Without keyboards, several database query operations are nontrivial: gestural inputs have no clear way to be mapped to traditional queries. The traditional query-result model is insufficient to deal with nuances of gestural interaction, such as rapidly changing inputs and sensitivity of interfaces. The traditional database query paradigm needs fundamental rethinking to support gestural interaction. The PI will work on the missing key components of the database stack for interactive and gestural workloads, collectively entitled "GestureDB". The proposed research will make data interaction accessible to an entirely new category of devices and users. Gestural interaction is rapidly gaining popularity where data access is key but there is limited keyboard access, e.g. users with disabilities and environments such as factory floors and laboratories. GestureDB's interaction-focused design is also expected to have a transformative impact in data-driven fields such as bioinformatics and "big data" analytics. Further, the interactive nature of GestureDB will make it an excellent platform for creatively engaging with both students and the general public.With GestureDB, the PI will first build a new query model featuring the concept of a "query intent", and an expressive "gestural query language," allowing users to use gestures as the sole mode of data interaction. Second, he will work on methods for "intent interpretation," allowing the system to better recognize the user's query intent during the gesture. Third, the PI will investigate methods for "feedback generation," allowing the system to provide feedback during the gesture articulation. All components will be designed while keeping interactivity in mind, in order to maintain a low-latency loop and ensure a fluid user experience. While decades of research in databases have gone into making databases more performant, the focus has typically been on large-scale pipelines, and not end users. Research in human-computer interaction and visualization has recently been investigating data management concepts for user interfaces. GestureDB bridges this gap, and takes a new approach towards enabling interactive, gestural querying of data. Ideas presented in this proposal are not restricted to gestural interaction: several can be adapted to solve classically hard problems in traditional database querying as well. Enabling gestural interaction will transform the default, traditional modes of ad-hoc querying of databases. The proposed solutions can open up several new avenues of research in query interfaces, query intent interpretation and feedback generation, and will also inspire research at all levels of the underlying database stack. The mechanisms proposed will enable building of highly interactive applications, and have a significant impact in rethinking future database systems.For further information see the project web site at: http://interact.osu.edu/gesturedb