John Snow, “the father of epidemiology,” is famous for his cholera maps. These maps represent so many of our aspirations as data-designers. By obsessively (heroically!) diving into London’s 1854 cholera outbreak, laboriously gathering an infection dataset (at his own peril!), then overlaying the data around the infamous pump on Broad Street, John Snow not only revealed a fundamental truth about London’s cholera outbreak, but he also made it inescapably obvious to stubborn public officials. John Snow and his visualization saved a city — or so the legend goes (src, src).

约翰·斯诺 ( John Snow )是“流行病学之父”，以霍乱地图闻名。 这些地图代表了我们作为数据设计人员的许多愿望。 约翰·斯诺(痴迷于(从神学上！)潜入伦敦1854年霍乱爆发，努力收集感染数据集(后果自负！)，然后将数据覆盖在臭名昭著的Broad街周围，约翰·斯诺(John Snow)不仅揭示了伦敦霍乱爆发的基本事实，但他也使顽固的公职人员不可避免地变得显而易见。 约翰·斯诺( John Snow) 和他的可视化保存了一座城市-传说就这样了( src ， src )。

True or not, the Guardian describes John Snow’s maps as “a model of how to work today” (src). We aspire toward visualizations like this because they enlighten. We judge their quality by “knowledge gain,” or how much insight a person gains for having experienced them.

不管是真的还是不是，《卫报》都将约翰·斯诺的地图描述为“今天工作方式的典范”( src )。 我们渴望这样的可视化，因为它们启发了我们。 我们通过“知识增益”或一个人通过体验他们获得的洞察力来判断他们的素质。

These singular acts of visualization brilliance are certainly worthy of admiration. But data visualization doesn’t need to reveal the secrets of the universe to make the world a better place.

这些奇异的可视化光辉行为当然值得钦佩。 但是，数据可视化不需要揭示宇宙的秘密就可以使世界变得更美好。

dataviz是否需要洞察力才能发挥影响力？ (Does dataviz need to be insightful to be influential?)

A more common experience with data, I suspect, is much more personal even if more mundane. It’s looking at our checking accounts, glancing at our car’s (literal) dashboards, watching step counts climb on Fitbits, checking our blood-glucose monitors, tracking our periods, etc.

我怀疑 ，即使是更为平凡的数据，更常见的数据体验也会更加个人化。 它正在查看我们的支票帐户，浏览我们的汽车(文字)仪表盘，观看Fitbits上的步数攀升，检查我们的血糖监视器，跟踪我们的月经等。

None of these experiences necessarily offer life-changing analysis. But because these data interactions reach so many people, so frequently — and, often, they’re designed to nudge us in the right direction— I suspect their aggregate impact is at least comparable to legendary works such as Snow’s.

这些经验都不能提供改变生活的分析。 但是，由于这些数据交互如此频繁地接触到如此多的人，并且经常是为了将我们推向正确的方向，所以我怀疑它们的总体影响至少可以与斯诺的传奇作品相媲美。

dataviz的发展分支…… (A developing branch of dataviz…)

Dataviz doesn’t need to reveal the secrets of the universe to be impactful.

Dataviz无需透露宇宙的秘密就可以产生影响。

As more of everything we do leaves a trail of data, there are growing opportunities to surface this data in ways that positively impact users’ lives. (And, conversely, there is a greater risk of doing harm.)

随着我们所做的每一件事都留下数据痕迹，越来越多的机会以对用户生活产生积极影响的方式显示这些数据。 (相反，存在更大的遭受伤害的风险。)

The growing ocean of personal data means new opportunities to make the world a better place by focusing on smaller, more intimate, everyday visualizations. In particular, I think there are significant, untapped and under-appreciated opportunities helping people, as users of various products and services, to visualize their own data.

不断增长的个人数据海洋意味着通过专注于更小巧，更贴心的日常可视化，可以使世界变得更加美好。 我特别认为，存在大量的，尚未开发的和未被重视的机会，它们可以帮助人们(作为各种产品和服务的用户)可视化自己的数据。

This type of design is worth highlighting because, even though it draws heavily from two well-established disciplines (dataviz & UX), the intent is different. Instead of optimizing for revelation (as with dataviz) or utility/delight (as with UX), user-data visualization centers more on personal reflection. It’s more about motivation than information, and this brings unique considerations, opportunities and risks (as we’ll see below!).

值得一提的是这种类型的设计，因为即使它大量借鉴了两个行之有效的学科(dataviz和UX)，其目的也有所不同。 用户数据可视化不是针对显示(如dataviz)或实用程序/工具(如UX)进行优化，而是将更多的精力放在个人反思上。 与其说动机，不如说是信息 ，这带来了独特的考虑因素，机遇和风险(我们将在下文中看到！)。

In this post, we’ll examine 7 examples of “motivational visualization” (i.e. helping people visualize themselves & make positive change). I hope this accomplishes the following:

在本文中，我们将研究“动机可视化”的7个示例(即帮助人们可视化自己并做出积极的改变)。 我希望这可以实现以下目标：

1. Draw attention to the practice of motivational visualization to help seed further conversation within the Dataviz community.
   提请注意动机可视化的实践，以帮助在Dataviz社区内进行进一步的对话。
2. By highlighting the methods behind these examples, help dashboard and product designers realize a few superpowers they might not be tapping into.
   通过突出显示这些示例背后的方法，可以帮助仪表板和产品设计人员实现他们可能无法利用的一些超能力。
3. Inspire other practitioners to explore new ways of conveying smaller, more personal truths.
   激发其他从业者探索传达较小，更多个人真理的新方法。

可视化功耗 (Visualizing Power Consumption)

In 2008, in an effort to reduce electricity consumption, the Sacramento Municipal Utility District tried a new technique. They sent 35,000 customers a letter with a few simple charts, showing customers their electricity consumption compared to their neighbors.

2008年，为减少电力消耗，萨克拉曼多市政公用事业区尝试了一项新技术。 他们给了35,000个客户一封信，并附有一些简单的图表，显示了与邻居相比客户的用电量。

In the charts above you can see a bar graph with 3 bars, representing power consumption for 3 different groups: “efficient” neighbors, all neighbors and the recipient’s household. This showed customers if they were consuming more or less electricity than their neighbors.

在上面的图表中，您可以看到带有3条柱形图的条形图，代表3个不同组的功耗：“有效”邻居，所有邻居和接收者的家庭。 这向客户显示了他们消耗的电量是否比邻居多。

Customers who received these letters reduced their power consumption by 2% on average (src). While this seems small in terms of an individual’s power bill, across all the customers this amounts to terawatts of electricity and millions of dollars saved collectively. Since then, other utilities around the country have adopted this approach.

收到这些信函的客户平均将其功耗降低了2％( src )。 虽然就个人的电费而言，这似乎很小，但在所有客户中，这总计相当于数兆瓦的电，并且集体节省了数百万美元。 从那以后，全国其他公用事业都采用了这种方法。

超级大国： (Superpower:)

What makes these charts impactful isn’t just the feedback (“you consumed X of electricity”), it’s the context the feedback is presented in (“you consumed X, most of your neighbors consumed Y”). As people, we look to others’ behaviors as norms for our own. So by seeing others’ power consumption, people change their own consumption habits to be more consistent with the social norm.

使这些图表具有影响力的不仅是反馈(“您消耗了X的电量”)，还在于显示了反馈的上下文(“您消耗了X的电量，大多数邻居消耗了Y”)。 作为人，我们将他人的行为视为自己的规范。 因此，通过查看他人的用电量，人们可以改变自己的用电习惯，使其更符合社会规范。

In a related experiment, Schultz & friends found that the same message with an additional smiley or frowny face amplified the effect even further by reinforcing the behaviors of households that were already doing a good job (src).

在一项相关的实验中，舒尔茨和朋友们发现，同一条带有额外笑脸或皱眉的信息通过增强已经做好工作的家庭的行为进一步扩大了效果( src )。

带走： (Takeaway:)

Nothing about the electricity usage charts are profoundly insightful, at least not in the way we might think of John Snow’s cholera maps. But even simple visualizations, when paired with an understanding of human and social psychology, can be impactful to large numbers of people. These types of visualizations won’t win a Pulitzer, but in aggregate they can make a big difference in our lives and our communities.

用电量图表并没有什么深刻的见识，至少在我们可能不会想到约翰·斯诺的霍乱地图方面。 但是，即使简单的可视化与对人类和社会心理学的理解相结合，也可能对大量人产生影响。 这些类型的可视化不会赢得普利策奖，但总的来说，它们可以对我们的生活和社区产生巨大的影响。

可视化血糖 (Visualizing Blood Glucose)

For the 1.6M people in the US with Type1 Diabetes, graphs like these are never far from top-of-mind. As Continuous Glucose Monitoring (CGM) becomes widespread, these charts have become part of daily life.

对于美国160万患有1型糖尿病的人来说，像这样的图表从来都不是最重要的。 随着连续血糖监测(CGM)的普及，这些图表已成为日常生活的一部分。

Often, the plot of your blood glucose is the story of your day.

通常，您的血糖情节就是您今天的故事。

If you search Twitter for #T1D you’ll find example after example like the tweets above. What makes these so compelling is that they’re lived data. They’re a reflection of the user’s life. The value is not just the information, it’s visualization as a satisfying memento.

如果您在Twitter上搜索＃T1D，则会在示例之后找到类似上述推文的示例。 是什么使得这些如此引人注目的是，他们居住的数据。 它们反映了用户的生活。 价值不仅仅是信息，它还可以看作是令人满意的纪念品。

Of course, these charts are also effective. In multiple studies, giving subjects with Type1 Diabetes a CGM helped improve blood sugar control significantly (src, src). For people with Type1, the CGM and these simple plots, are life-changing (and occasionally life-saving).

当然，这些图表也是有效的。 在多项研究中，对1型糖尿病受试者进行CGM有助于显着改善血糖控制( src ， src )。 对于拥有Type1的人来说，CGM和这些简单的图可以改变生活(并有时可以挽救生命)。

超级大国： (Superpower:)

Like Tufte and Powsner’s “Graphical Summary of Patient Status” (src), which show data in the context of a historic normal range, the chart above from Matthaei & friends presents a target range for blood glucose (because levels shouldn’t be too high or too low). This helps users quickly identify dangerous deviations, so they can take appropriate action (e.g. administering insulin).

就像Tufte和Powsner的“ 患者状况的图形摘要 ”( src )在历史正常范围内显示数据一样，上图由Matthaei＆friends绘制的图表提出了血糖的目标范围 (因为水平不应过高)或太低)。 这可以帮助用户快速识别危险的偏差，以便他们可以采取适当的措施(例如，服用胰岛素)。

While presenting goals as a range is necessary for glucose monitoring, there’s also evidence that representing any goal as a range is more effective than a point value. Targeting a range of acceptable outcomes is simultaneously more forgiving and ambitious, encouraging users to persevere over the long-term (src, src).

虽然将目标显示为范围对于葡萄糖监测是必要的，但也有证据表明，将任何目标表示为范围比点值更有效。 瞄准一系列可接受的结果同时更宽容和雄心勃勃，鼓励用户长期坚持不懈( src ， src )。

带走： (Takeaway:)

User data is lived data. This enables visualizations that are functional and can also involve unique dimensions of nostalgia, intimacy and affirmation. Even without revealing new insights (e.g. users already know what grandma’s cooking is likely to do to their levels), there’s still value in visualization as a memento.

用户数据是实时数据。 这使功能化的可视化成为可能，并且还可能涉及到怀旧，亲密和肯定的独特维度。 即使没有透露新见解(例如，用户已经知道奶奶的烹饪可能会达到他们的水平)，可视化仍然是一种纪念品。

可视化屏幕时间 (Visualizing Screen-Time)

Older millennials may remember the Tamagotchi invasion of 1997. Suddenly, everyone in 6th grade had a colorful plastic ornament hanging off a belt loop or tucked in a baggy pocket. Several researchers have shown that the attachment we felt toward these digital creatures is transferable to other parts of our lives that actually deserve our vigilance.

千禧一代可能会记得1997年的“塔玛哥奇”入侵。突然之间，六年级的每个人都有五颜六色的塑料装饰品挂在皮带环上或藏在宽松的口袋里。 一些研究人员表明，我们对这些数字生物的依恋可以转移到我们生活中的其他部分，这些部分实际上值得我们保持警惕。

One challenge many of us face is limiting screen time. In 2019, Kenny Chow showed that representing screen time as an infliction on a “lively” animated avatar was a promising intervention toward reducing participants’ screen time (src). The more time users spent with devices open, the sicklier the avatar becomes.

我们许多人面临的挑战之一是限制屏幕时间。 在2019年，Kenny Chow展示了将屏幕时间表示为对“生动”动画化身的侵犯，这是减少参与者屏幕时间( src )的有前途的干预措施。 用户打开设备花费的时间越多，虚拟化身就变得越病态。

This model of creature-as-data has worked in other contexts. Lin & friends showed that representing physical activity as a virtual fish tank helped participants become more physically active (src). Consolvo and friends showed a similar effect for visualizations of flowers and butterflies standing in for exercise events and goals (src).

这种作为数据的生物模型在其他情况下也起作用。 Lin和他的朋友表明，将体育活动表现为虚拟鱼缸有助于参与者提高体育活动( src )。 Consolvo和朋友对参加运动项目和目标( src )的花朵和蝴蝶的可视化显示了相似的效果。

At first glance, these representations seem more like “data art” than “data visualization.” But I think the effect is the same. Instead of encoding data for preattentive processing via our brains’ spatial wiring, the avatars encode the data for the parts of our brains that make us social and supportive. We feel the data through our empathy for the “living” character on the screen.

乍一看，这些表示形式更像是“数据艺术”而不是“数据可视化”。 但我认为效果是一样的。 化身不是对数据进行编码，而是通过大脑的空间布线进行细心的处理，而是对使我们变得社交和支持的大脑各部分的数据进行编码。 我们通过同情屏幕上的“活着”角色来感受数据。

超级大国： (Superpowers:)

This probably doesn’t make sense for a Tableau dashboard at work. For many use-cases (e.g. journalism, BI, reporting, etc), immediacy, precision and depth are supreme. For personal-viz, though, some of these constraints can be relaxed:

对于工作中的Tableau仪表板，这可能没有任何意义。 对于许多用例(例如新闻，BI，报告等)，即时性，准确性和深度都是至高无上的。 但是，对于个人而言，可以放宽一些约束：

• If you can assume the user will interact with the visualization multiple times, a longer learning curve is sometimes acceptable (and to the extent that learning the viz can instill feelings of mastery, a steeper learning curve might be desirable).
  如果您可以假设用户将与可视化进行多次交互，则有时可以接受更长的学习曲线(并且在某种程度上，学习Viz可以灌输掌握的感觉，可能更陡峭的学习曲线是可取的)。
• Precision is sometimes undesirable (e.g. for weight loss, users can overly fixate on natural ups-and-downs). Representing data on a vague scale like “sick avatar” to “healthy avatar” can help users gain sensitivity to the metric without fixation.
  有时精度是不可取的(例如，为了减轻体重，用户可能过度偏爱自然的起伏)。 用诸如“病化身”到“健康化身”这样的模糊表述数据可以帮助用户无需度量即可获得对指标的敏感性。
• If the underlying data is relatively simple and a shallower representation creates a sense of emotional attachment, forgoing depth for extended engagement is an easy tradeoff to make.
  如果基础数据相对简单，并且较浅的表示形式产生了情感依恋感，那么放弃长期参与的深度就很容易做出权衡。

带走： (Takeaway:)

The goals and constraints for motivational viz can be quite different from traditional dataviz, making very non-traditional visualizations like Avatars, Fish and Flowers potentially very effective. When the goal is not just conveying information, but creating an emotional connection, tapping into users’ empathy through tactics like anthropomorphization can help form an emotional bond to the underlying data.

为激励即目标和约束可以从传统的DataViz公司完全不同，使得像化身，鱼和花卉非常非传统的可视化可能非常有效。 当目标不仅是传达信息，而是建立情感联系时，通过拟人化等策略利用用户的同理心可以帮助与基础数据形成情感纽带。

可视化财务目标 (Visualizing Financial Goals)

Most brokerage services encourage bad investing habits. From the moment users login, they see charts & graphs of their portfolio performance in the past or the market’s performance right now.

大多数经纪服务会鼓励不良的投资习惯。 从用户登录的那一刻起，他们就可以查看过去或现在的市场表现的图表。

When I spoke with Dan Egan (Head of Behavioral Finance at Betterment), he said this backward-looking focus leads users to reactionary decision making, ultimately hurting their long-term financial outcomes (e.g. “Oh! The market just went down, I have to sell out because I don’t want it to go down more”).

当我与丹尼尔·埃根(Betterment行为金融学负责人)交谈时，他说，这种向后看的重点使用户做出了反动的决策，最终损害了他们的长期财务成果(例如，“哦！市场刚刚下跌，我有卖光了，因为我不想让它下跌更多”。

Egan’s research suggests that the more users fixate on portfolio performance, the more likely they are to fidget, and fidgeting lowers users’ expected returns (src).

埃根(Egan)的研究表明，用户对投资组合绩效的关注程度越高，他们越容易坐立不安，而坐立不安会降低用户的预期收益( src )。

According to Dan: “In investing, people spend a lot of time looking at history. But you just can’t change history. You can’t change that outcome.” Instead, “the only thing that matters is what you decide to do with today and how that sets you up for the future.”

丹说：“在投资中，人们花很多时间看历史。 但您只是无法更改历史记录。 您无法改变结果。” 取而代之的是，“唯一重要的是您决定今天如何做以及如何为将来做准备。”

So Betterment encourages users to look forward by offering visualizations like the Goal Forecaster, designed to “focus you on the future and where you want to end up.” It helps you see “how your actions today put you in a better position in the future.”

因此，Betterment通过提供诸如“目标预测器”之类的可视化工具来鼓励用户前瞻 ，这些可视化工具旨在“使您着眼于未来以及最终目标。” 它可以帮助您了解“您今天的行为如何使您将来处于更好的位置。”

Research backs this up. Simulating various saving schedules helps users connect the cause and effect of their actions now (auto-deposit) with likely future outcomes (boat). Making these relationships concrete helps people grasp the effects of complex concepts like exponential growth and motivates users to save more (src, src). Another 2015 study suggests that highlighting the difference between savings goals and savings projections helps participants make better decisions, using the endowment effect to their advantage (src).

研究对此提供了支持。 模拟各种保存计划可以帮助用户将其行动的因果关系(自动存款)与可能的未来结果(船)联系起来。 使这些关系具体化可以帮助人们掌握复杂概念(如指数增长)的影响，并激励用户节省更多( src ， src )。 2015年的另一项研究表明，强调储蓄目标与储蓄预测之间的差异有助于参与者利用the 赋效应发挥其优势( src )，从而做出更好的决策。

Finally, the Goal Forecaster helps set realistic expectations. Realistic expectations about future goals make us more likely to achieve them (src). Presenting the projected savings in a fan-chart helps reinforce the message that there’s uncertainty in any financial journey, while still conveying the benefits of investing over the long term.

最后，目标预测器可帮助设定切合实际的期望。 对未来目标的现实期望使我们更有可能实现这些目标( src )。 在扇形图中显示预计的节省额有助于进一步增强信息，即任何财务旅程都存在不确定性，同时仍可以传达长期投资的好处。

超级大国： (Superpower:)

Dan says, consider “showing not telling: “If you let people simulate their outcomes — if you let them experience parallel universes — that is more effective in getting them to understand what’s going to happen than if you describe it. Allowing people to really experience it and see the variations allows them to internalize it as real.”

丹说，请考虑“不要说： ”如果让人们模拟他们的结果-如果让他们体验平行的宇宙-相对于描述它，它更能使他们了解即将发生的事情。 让人们真正体验它并看到其变化，就可以将其内部化为真实。”

带走： (Takeaway:)

For Betterment, letting users look ahead is informational and motivational. Simulating short term actions playing out over the long term helps educate users about difficult-to-imagine cause and effect relationships, giving them the confidence to make smarter choices. Having realistic expectations about the future helps users prepare themselves for a long journey.

为了改善，让用户放眼未来是信息和激励。 模拟长期的短期行为可以帮助用户了解难以想象的因果关系，使他们有信心做出更明智的选择。 对未来抱有切合实际的期望，可以帮助用户为漫长的旅途做好准备。

可视化健身活动 (Visualizing Fitness Activity)

Tracking physical activity helps many people stay active (src). The challenge is maintaining users’ attention and getting them to stick with the intervention. In this context, visualization can be a tool for both conveying data and rewarding users for collecting the data in the first place.

跟踪身体活动有助于许多人保持活跃( src )。 挑战在于保持用户的注意力并使他们坚持干预。 在这种情况下，可视化可以既是传达数据又是奖励用户收集数据的工具。

颚骨向上 (Jawbone UP)

Jawbone’s UP app (circa ~2012) was one of my favorite examples of this. In the screenshots above, there are two bar charts of users’ step counts. For most of the day, you’re seeing a chart like the left, but by the end of the day, once you’ve crossed your goal threshold (e.g. 10,000 steps), the background explodes into a happy sunburst, helping you celebrate the accomplishment!

Jawbone的UP应用程序(大约2012年)是我最喜欢的示例之一。 在上面的屏幕截图中，有两个用户步数的条形图。 在一天的大部分时间里，您会看到如左图所示的图表，但是到一天结束时，一旦您越过了目标阈值(例如10,000步)，背景就会爆炸成快乐的朝阳状态，从而帮助您庆祝成就！

With wanton disregard for data-ink ratios, Jawbone’s designers were masters at conjuring up visual joy. The effect was users who felt supported and encouraged to keep hitting their goals (and, implicitly, to continue tracking and interacting with the data).

Jawbone的设计师无视数据墨水比率，因此他们在唤起视觉愉悦方面是大师。 结果是用户感到支持并鼓励他们继续实现他们的目标(并隐式地继续跟踪数据并与之交互)。

Notch.me (Notch.me)

With Notch.me, we did similar work using emailed “postcard visualizations” to heighten user’s sense of accomplishment at various milestones (and create a sense of anticipation for future milestones). The data was sourced from user’s personal activity tracking (e.g. via Fitbit) and presented back to users in various encouraging visualizations like the ones above.

使用Notch.me，我们使用电子邮件发送的“明信片可视化”来完成类似的工作，以增强用户在各个里程碑的成就感(并为将来的里程碑创建一种期待感)。 数据来自用户的个人活动跟踪(例如，通过Fitbit)，并通过各种令人鼓舞的可视化形式(如上图所示)呈现给用户。

The two top postcards above, use visual metaphor to compare a user’s activity to something unexpected and silly; they’re extremely low data-density, but still quite effective in directing recipients’ attention toward their data.

上方的两张最上面的明信片使用视觉隐喻将用户的活动与意外和愚蠢的事物进行比较； 它们的数据密度极低，但在将收件人的注意力引向其数据方面仍然非常有效。

The two bottom postcards show users’ activity for a set time period (left: 1 year, right: 1 week); this encouraged users to track more consistently during those periods in anticipation of a more elaborate, pleasant visualization (the more you track, the cooler it looks).

底部的两个明信片显示了用户在设定时间段内的活动(左：1年，右：1周)； 这鼓励用户在那些时期内更一致地进行跟踪，以期获得更加精致，令人愉悦的可视化效果(跟踪的次数越多，外观越酷)。

In various experiments, visualizations like the above captured user attention and boosted engagement with the data. And, as you might expect from “sugary,” chart-junky visualizations, users loved them.

在各种实验中，像上面这样的可视化吸引了用户的注意并增强了对数据的参与。 而且，正如您可能从“杂乱无章”的图表式可视化中期望的那样，用户喜欢它们。

超级大国： (Superpowers:)

Remember Nigel Holmes and the power of humor (src): “My feeling then, and now, is that humor is a good way to get people’s attention. Get a reader to smile or recognize a visual reference and they’ll surely read on.”

记得奈杰尔·福尔摩斯(Nigel Holmes)和幽默的力量( src )：“我当时和现在的感觉是，幽默是引起人们关注的好方法。 让读者微笑或识别视觉参考，他们一定会继续阅读。”

In addition to capturing attention, Holmes’ style of visualization has also been shown to increase the memorability of the content (src). Perhaps an overlooked aspect of Holmesian visualizations is that they feel good. This is powerful in its own way: Positive feedback and positive affect (emotion) is important for helping people make positive changes.

除了吸引注意力之外，霍姆斯的可视化样式还被证明可以增加内容( src )的可记忆性。 Holmesian可视化的一个可能被忽视的方面是它们感觉良好。 这有其自身的强大功能：积极的反馈和积极的情感(情感)对于帮助人们做出积极的改变很重要。

带走： (Takeaway:)

For information to make a difference, it has to be seen. Humor, visual metaphor and even pleasant visual flourishes not only serve to draw users’ attention, but they’re also emotionally and viscerally rewarding methods to reinforce engagement with the data. For Jawbone’s visual flourishes and, pretty much everything with Notch.me, the goal for each visualization was as much about information as it was affirmation.

为了使信息有所作为，必须看到它。 幽默，视觉隐喻甚至愉悦的视觉效果不仅可以吸引用户的注意力，而且在情感上和内在上都是奖励与数据互动的方法。 对于Jawbone的视觉蓬勃发展以及Notch.me的几乎所有内容而言，每种可视化的目的都与信息有关，而与信息有关。

可视化阅读活动 (Visualizing Reading Activities)

Kindle’s “Reading Insights” is a relatively new addition to the Kindle iOS / Android apps. I think there’s a lot to praise with this. Reading is another of life’s many activities that, despite wanting to do more of it, we struggle to make it happen as often as we’d like. So offering users a way to track and reflect on their reading could see a meaningful increase in time spent reading.

Kindle的“ Reading Insights”是Kindle iOS / Android应用程序的一个相对较新的功能。 我认为这值得赞扬。 阅读是生活中许多活动中的另一项，尽管它想做更多事情，但我们努力使它尽可能多地发生。 因此，为用户提供一种跟踪和反思其阅读方式的方法可能会导致阅读时间的显着增加。

I think it’s also emotionally satisfying. In the same way, a physical bookshelf is like a trophy case for nerds, seeing the books you’ve read front and center feels good. Like stickers, it’s a visual representation of your accomplishments that you can feel proud of.

我认为这在情感上也令人满意。 同样，实体书架就像书呆子的奖杯盒一样，看到您在书架正面和中央阅读的书感觉很好。 就像贴纸一样，它是成就感的直观体现，令人感到骄傲。

The downside, and this is true of many similar visualizations, is it gives Amazon a justification for even further surveillance (src). This serves as an important reminder that, with this new frontier of data there are ways that it can be legitimately useful to end-users, but that’s not without tradeoffs. As makers and designers, we should keep the ethics of personal data use top of mind. (As a silver lining, thanks to CCPA, you can now request all of Amazon’s data on your reading habits to visualize for yourself!)

不利的一面(在许多类似的可视化中都是如此)是，它为亚马逊提供了进行进一步监视( src )的理由。 这是一个重要的提醒，在这种新的数据领域中，有一些方法可以对最终用户合法有用，但这并非没有取舍。 作为制造商和设计师，我们应该牢记个人数据使用的道德规范。 (作为一线希望，多亏了CCPA ，您现在可以根据自己的阅读习惯要求获取Amazon的所有数据，以便自己查看！)

带走： (Takeaway:)

Visualizing user data creates exciting opportunities for both users and designers, but it also brings new responsibilities. For every thoughtful blood-glucose visualization attempting to empower users, there’s an Uber out there using behavioral data to manipulate. As we rightly question the role of data and algorithms in a just world, we shouldn’t forget that visualizations, like any non-neutral technology, can be used for harm and for good.

可视化用户数据为用户和设计人员都带来了令人兴奋的机遇，但同时也带来了新的责任。 对于每一次试图增强用户可视化的血糖可视化尝试，都有一个Uber 使用行为数据进行操作 。 当我们正确地质疑数据和算法在公正世界中的作用时，我们不应忘记，可视化像任何非中立技术一样，可以带来伤害和好处。

外卖 (Takeaways)

• Epic, John Snow-eque, Pulitzer-worthy dataviz is amazing, but dataviz can also be impactful in everyday use. This seems worth celebrating.

  史诗般的约翰·斯诺克(Epic)，普利策(Pulitzer)值得一看的dataviz 令人惊叹，但是dataviz在日常使用中也会产生影响。 这似乎值得庆祝。

• Instead of revealing the secrets of the universe, motivational visualization is about offering lenses on a subject that users are already intimately familiar with: themselves.
  动机可视化不是揭示宇宙的秘密，而是提供用户已经非常熟悉的主题镜头：自己。
• While the medium is the same, design goals for “motivational visualization” differ from traditional dataviz. Instead of singular dedication to information gain and/or impacting big decisions, user-data visualizations tend to benefit everyday behaviors and micro-decisions.
  尽管媒介是相同的，但“动机可视化”的设计目标却不同于传统的数据可视化。 用户数据可视化不是单单致力于获取信息和/或影响重大决策，而是倾向于使日常行为和微观决策受益。
• Motivational viz can help in a variety of ways (e.g. encouraging adoption of social initiatives, managing health conditions, helping people persevere toward long-term goals or developing new habits, etc). As the field evolves we should keep our eyes peeled for emerging tactics and new opportunities to apply them (while keeping vigilant against anti-patterns and dark-patterns that may emerge as well).
  动机性视觉可以多种方式提供帮助(例如，鼓励采取社会措施，管理健康状况，帮助人们坚持长期目标或养成新习惯等)。 随着领域的发展，我们应该对新兴的策略和应用这些策略的新机会保持警惕(同时还要警惕可能出现的反模式和暗模式)。

• If you’re a dashboard designer, product designer or anyone else helping visualize user data, you’ve got superpowers to inform and inspire.

  如果您是仪表板设计师，产品设计师或任何其他帮助可视化用户数据的人员，那么您将拥有超能力来提供信息和启发。

You can follow the TLDR thread here on Twitter!

您可以在Twitter上关注TLDR线程！

Who am I? No, no, who are you?!

我是谁？ 不，不，你是谁？

Hi! I’m Eli Holder. I help clients use data to create positive change by engaging audiences not just rationally, but also emotionally and culturally. Change happens in the head and the heart.

嗨！ 我是Eli Holder。 我帮助客户不仅通过理性地而且在情感上和文化上吸引受众，从而利用数据创造积极的变化。 变化发生在头部和心脏。

If you’re a founder, maker, storyteller or business leader working at the intersection of data, design and user psychology, I’d love to connect and trade stories.

如果您是在数据，设计和用户心理的交汇处工作的创始人，制造商，讲故事者或业务负责人，那么我很想联系和交易故事。

You can email me at hi@elih.co or follow me on Twitter.

您可以通过hi@elih.co给我发送电子邮件，或者在Twitter上关注我。