Qualified Selves: Co-Creating Meaning Post-Big Data

合格的自我：共同创造后大数据的意义

• 批准号: EP/R033064/1
• 负责人: Chris Speed
• 金额: $ 54.72万
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FR033064%2F1
• 关键词: Qualified; Selves; Co; Creating; Meaning

Individuals are increasingly reliant on digital applications and services to store photos, documents, notes and other valued personal data. They are also accustomed to - and tacitly accept as a hidden cost of using otherwise 'free' services - these applications amassing activity data and metadata from which companies derive significant business value. For example, Facebook makes much of its £22bn yearly revenue by being able to precisely target advertisements to users by deciphering their unique preferences from their likes, tags, contacts, updates, photos, travel patterns etc (some accessed through permissions to Facebook via other apps) [BBC]. There is a highly lucrative, if shadowy, trafficking in users' data: data brokering companies such as Acxiom and Epsilon compile thorough dossiers on people's physical and mental health conditions, sexual orientation, personal vices, and vulnerabilities to aid companies in identifying likely consumers [CBS,SCH]. Meanwhile, there are no corresponding tools accessible for individuals to learn about themselves through their personal data. Within recent years, there is a growing literacy around data as a medium for generating information and key insights. This is represented in the Quantified Self movement (see, e.g.: http://feltron.com), with individuals self-tracking their patterns of behaviour, physiological responses, productivity, correspondences etc with a view toward enabling personal reflection and gaining greater self-knowledge [LI]. Wearable activity trackers have been appropriated by some for self-diagnostic purposes: e.g. finding correlations between activities and symptoms to make informed changes to improve personal wellbeing [ROO]. There is untapped potential in applying this sensibility toward broader and deeper personal sense-making by drawing connections between the full diversity of one's personal data currently siloed in various services and applications - from the wide array of web services, to mobile applications, wearable and home IoT devices.Personal Information Management (PIM) is a growing ICT sector with an estimated market worth of £16.5bn [NES]. Focusing on four major activities - keeping, finding, organizing and maintaining - PIM offers valuable insights into how to develop and sustain practices for effectively managing one's own data [KLI]. A particular challenge in developing PIM solutions is the individuality of lay data management techniques and strategies, which map onto people's individual strengths and familiar, established practices; in short, individuals thrive when they are able to develop strategies that work for them and for the particular goals they have defined. Given that many services ostensibly offer information management to users (albeit with pre-set UX constraints), an especially interesting frontier for extending PIM research lies in lifting data out from the applications that are currently managing them to support individualised, goal oriented collection and management of personal data - and further, offering techniques for managing between diverse data types (e.g. the minutia of metadata, narrative/textual data, photographic data, activity data, etc).This project will fill several important gaps in understandings of personal sense-making, including: 1) in contrast to commercial ends for extracting, collecting and analysing people's personal data, understanding what kinds of self-knowledge would offer significant value to individuals, and how bridging personal data between applications and services might uniquely afford these personal insights; and 2) understanding how people can derive meaning from mixed data types and across applications, unbounded by the goal orientations of the individual applications or services they use to capture their personal data.

个人越来越依赖于数字应用程序和服务来存储照片、文档、笔记和其他有价值的个人数据。他们也习惯了——并且默认为使用“免费”服务的隐性成本——这些应用程序积累了活动数据和元数据，公司从中获得了重要的商业价值。例如，Facebook每年220亿英镑的收入中，有很大一部分来自于能够通过解读用户的喜好、标签、联系人、更新、照片、旅行模式等（其中一些是通过其他应用程序访问Facebook的权限获得的）来精确地向用户投放广告。用户数据交易虽然不为人知，但利润丰厚：Acxiom和Epsilon等数据经纪公司会收集人们的身心健康状况、性取向、个人恶习和弱点等详尽的档案，以帮助公司识别潜在消费者。同时，个人也没有相应的工具可以通过自己的个人数据来了解自己。近年来，越来越多的人认识到数据是生成信息和关键见解的媒介。这体现在量化自我运动中（例如：http://feltron.com），个人自我跟踪他们的行为模式、生理反应、生产力、通信等，以实现个人反思和获得更多的自我认识[LI]。可穿戴式活动追踪器已被一些人用于自我诊断目的：例如，发现活动和症状之间的相关性，从而做出明智的改变，以改善个人健康[ROO]。通过将目前孤立在各种服务和应用程序中的个人数据的多样性（从广泛的网络服务到移动应用程序、可穿戴设备和家庭物联网设备）联系起来，将这种敏感性应用于更广泛、更深入的个人意义构建，这方面还有未开发的潜力。个人信息管理（PIM）是一个不断增长的信息通信技术领域，估计市场价值为165亿英镑。PIM专注于四个主要活动——保存、发现、组织和维护——为如何开发和维持有效管理个人数据的实践提供了有价值的见解[KLI]。开发PIM解决方案的一个特殊挑战是外行数据管理技术和策略的个性，这些技术和策略映射到人们的个人优势和熟悉的既定实践；简而言之，当个人能够制定出适合自己的策略，并为自己确定的特定目标而努力时，他们就会茁壮成长。考虑到许多服务表面上为用户提供信息管理（尽管有预先设置的用户体验限制），扩展PIM研究的一个特别有趣的前沿是将数据从当前管理它们的应用程序中提出来，以支持个性化的、面向目标的个人数据收集和管理——进一步，提供管理不同数据类型的技术(例如元数据的细节、叙述/文本数据、照片数据、活动数据等)。该项目将填补在理解个人意义构建方面的几个重要空白，包括：1)与提取、收集和分析人们个人数据的商业目的相比，了解哪些类型的自我认识将为个人提供重要价值，以及如何在应用程序和服务之间架起个人数据桥梁，以独特的方式提供这些个人见解；2)理解人们如何从混合数据类型和跨应用程序中获得意义，而不受用于捕获个人数据的单个应用程序或服务的目标方向的限制。

项目成果

Deliberating Data-Driven Societies Through Live Action Role Play

通过真人角色扮演思考数据驱动的社会

• DOI: 10.1145/3461778.3462028
• 发表时间: 2021
• 作者: Pothong K

Multitudes: Widening the research agenda for personal informatics design

众多：扩大个人信息学设计的研究议程

• DOI: 10.21606/drs.2022.415
• 发表时间: 2022
• 作者: Winter E

Designing transformative futures

设计变革性的未来

• DOI: 10.21606/drs.2022.896
• 发表时间: 2022
• 作者: Light A

Problematising Transparency Through LARP And Deliberation

通过 LARP 和审议解决透明度问题

• DOI: 10.1145/3461778.3462120
• 发表时间: 2021
• 作者: Pothong K

Investigating materiality for a renewed focus on data design practice

研究重要性以重新关注数据设计实践

• DOI: 10.21606/drs.2022.350
• 发表时间: 2022
• 作者: Lee Y