Streamlined Tools for Personal Analytics

该发现基金将专注于设计新的工具和应用程序，以实现“以思维的速度记录”，允许人们在不消耗大量时间或注意力的情况下捕获关于他们的思想和活动的详细、频繁的观察。***最近的个人传感器和自我跟踪工具浪潮有望帮助人们利用数据更好地了解自己。通过跟踪我们的生理和活动，自我跟踪工具应该允许日常用户测量、理解和处理诸如慢性疼痛和情绪健康之类的问题，或者支持持续的目标，如学习一门新语言。然而，像步数和应用程序日志这样容易自动化的度量通常都太低级，无法回答这类问题。与此同时，目前用于手动日志的移动应用程序通常非常繁琐、耗时，并且与日常活动不兼容，以至于人们无法保持一致或准确的记录。然而，许多重要的个人数据，包括疼痛日志、情绪日志和语言使用笔记，需要人类的判断和观察，必须手工记录。我的研究将探索简化个人数据收集和分析的工具和技术。通过最小化与自记录相关的开销，我们的原型将使收集和分析大量丰富的个人数据成为可能。这些工具将允许人们在他们的日常活动和想法的背景下快速记录信息（我在哪里经历疼痛，疼痛有多严重？）我的环境发生了什么变化吗？是我把这个词念错了吗？)，有时我很难这样做。轻量级的记录工具将帮助人们记录活动，而不会失去对当前任务的关注，从而可以记录和分析更多类型的活动，并且还支持诸如疼痛跟踪之类的应用程序，理想情况下，记录不应该将人们的注意力集中在正在发生的症状上。***我的团队的研究将通过设计一个简化数据收集和分析的工具包来检查这些挑战。我们将基于语音和触摸设计尽可能流畅和可靠的极简日志记录方法，并探索微妙的反馈机制，帮助人们检测错误并添加结构以支持以后的分析。这些日志工具将由定制的处理和分析工具提供支持，这些工具允许人们在分析之前轻松地过滤、清理和组织日志，并构建可重用的分析管道，他们可以使用这些分析管道来检查未来的数据。最后，我们将探讨这些轻量级日志工具在一系列特定领域应用中的潜力，包括用于疼痛管理和语言学习的工具。**

This Discovery Grant will focus on the design of new tools and applications that enable "logging at the speed of thought"allowing people to capture detailed, frequent observations about their thoughts and activities without consuming significant time or attention. ***The recent wave of personal sensors and self-tracking tools has promised to help people use data to better understand themselves. By making it possible to track our physiology and our activities, self-tracking tools should allow everyday users to measure, understand, and deal with issues like chronic pain and emotional health, or support ongoing goals like learning a new language. However, easily automated measurements like step counts and application logs are often too low-level to answer these kinds of questions. Meanwhile, current mobile applications for manual logging are often so cumbersome, time consuming, and incompatible with daily activities that people fail to keep consistent or accurate records. However, many important pieces of personal dataincluding pain logs, emotion journals, and notes on language userequire human judgement and observation and must be recorded manually.***My research will explore tools and techniques for streamlining personal data collection and analysis. By minimizing the overhead associated with self-logging, our prototypes will make it possible to collect and analyze much greater quantities of rich personal data. These tools will allow people to quickly record information in the context of their daily activities and thoughts (Where am I experiencing pain and how intense is it? Did something change in my environment? Did I just mispronounce that word?) at times when it would otherwise be difficult to do so. Lightweight recording tools will help people record activities without losing focus on their current taskmaking it possible to record and analyse more types of activities, and also supporting applications like pain tracking where logging ideally shouldn't focus the person's attention on symptoms as they are occurring. ***My team's research will examine these challenges through the design of a toolkit for streamlined data collection and analysis. We will design minimalist logging approaches based on speech and touch that are as smooth and reliable as possible, and explore subtle feedback mechanisms that help people detect errors and add structure to support later analysis. These logging tools will be backed by tailored processing and analysis tools that allow people to easily filter, clean, and organize their logs before analysis and build reusable analysis pipelines that they can use to examine future data. Finally, we will explore the potential of these lightweight logging tools in a series of domain-specific applications, including tools for pain management and language learning. **