The Datarella World Map Of Behavior

Every smartphone user produces more than 20 MB of data collected by her phone’s sensors per day. Now, imagine the sensor data of 2 billion smartphone users worldwide, translated into realtime human behavior, shown on a global map. That is the vision of the Datarella World Map of Behavior.

A typical 2015 generation smartphone sports up to 25 sensors, measuring activities as diverse as movements, noise, light, or magnetic flux. Most smartphone users aren’t even aware of the fact that their phone’s camera or microphone never are really „off“ but that they constantly collect data about the noise level or the intensity of light the user is experiencing.

Actions speak louder than words
Actions speak louder than words – if we want to really know a person we have to know how she behaves, and not only what she says. And that’s not only true for politicians. We all form our opinions on others by looking at their actions, more than their words. Many inter-personal problems result from NOT looking at people’s actions, but focusing on other aspects, such as their looks or their words. Behind superficial distinctions such as physical appearances, over time we often realize similarities with other people based on their and our actions.

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Our vision of a World Map of Behavior
At Datarella, our vision is to show the actions of people around the world on a global map. By displaying the actions of people of all continents, we want to tell stories about the differences and similarities of global human behavior – to draw a picture of human co-existence. There already are snapshots of global behavior, provided by data focused companies, such as Jawbone, who map sleep patterns worldwide. From that we know that Russians get up latest, and Japanese get the least sleep in total . And there are different behavior-related maps, showing the world’s most dangerous places, defined by the number and seriousness of crimes or actions of war.

Co-operation & Participation
To create the World Map of Behavior is our ambitious project for 2015 that we won’t complete alone. We need your support: if you are an expert in the field of mobile sensor data or if your company already focuses on collecting and interpreting mobile sensor data in the fields of mobility, finance, health or transport and travel. If you are interested to play a role in this project, please send us an email with a brief description of how you would like to contribute. We are looking forward to hearing from you!

The Datarella Data Timeline

If you live in the Americas, Europe, Asia-Pacific or Australia, you probably are one of 1.76 billion smartphone users. What do you do with your smartphone? You use apps for texting, social networking, gaming, etc. And you produce data. Lots of data. Every move you make, every breath you take, your behavior results in data: location, movement, body functions, external situational data. And you produce all this data on the fly, passively, without any effort.

But where is this data? Can you see it? Do you know exactly which data you produce? At which times or to what extent? Do you know that your data can be of tremendous value for you? That you can improve your health by using it? Can you imagine knowing all about your data, that you see your data, in realtime, presented in a meaningful way that lets you understand its value?

Welcome to the Datarella Data Timeline 

The Data Timeline  is an app-centric timeline of your own behavior data and that of your social network. Using the Data Timeline is like looking into a mirror: you see yourself – not your external appearance but the visualization of your body data, you see the most complete picture of your Self. he Data Timeline presents your data in a contextualized way: you see the data and its meaning in individual contexts – your personal data moments.

Reason Why

Each day, an individual produces about 20MB of smartphone data. This data can be of vital relevance for her: it can save her life. Or it can help her optimize her life. Or the life of her friends. In order to make meaning of this data, the user needs her own individual data timeline, she needs to see her data, in its contexts and visualized in a comprehensible way.

You and your friends

And it’s not only your Self – but you see real time snapshots of your friends, too! You know about their well-being, their movements or the noise levels they are exposed to. So you already know that your significant other is quite exhausted before she returns from work and you could prepare a candlelight dinner for her. You can share snapshots of your Self with your friends right away from the Data Timeline using the integrated Twitter, Facebook et al. sharing options. You decide with whom you want to share your data.

Own your body’s data

You should own your body’s data – because your data can reveal much more than even your doctors know. Your data is a very important part of you. You can use the Data Timeline to get the meaning of your data and – if you are a geek – you might even download all your raw data, dive into it and analyze it with your own tools. You have full ownership, full transparency and full visibility of your data.

The Data Timeline essentially is a platform matching users with Quantified Self services. It comes as in the user-centric format of an app timeline displaying the user’s individual behavior data and that of her social network. It shows an individual’s body and environmental data in its specific contexts. Passively tracked data are complemented with interaction data, such as status updates, comments and answered surveys.

The Data Timeline provides the user with her data itself and – via its API – the Data Timeline matches the user’s individual needs based on her data with respective Quantified Self services in the areas of health, fitness & well-being, travel & tourism as well as finance.

The Data Timeline’s technology is based on open source software, but all algorithms, especially for the Complex Event Processing Engine, are fully owned by Datarella. All raw personal data of individuals is owned by its respective users, according to German law. However, all aggregated data, all visualizations, and all analysis based on that data is owned by Datarella.

 

Slow Data

Data is the new media. Thus the postulates of our Slow Media Manifesto should be applicable on Big Data, too. Slow Data in this sense is meaningful data, relevant for society, driving creativity and scientific thinking. Slow Data is beautiful data.
Read my new text „From Slow Media to Slow Data“ at http://beautifuldata.net

Data is the new media

Data storytelling, data journalism, and even data fiction – since the advent of Big Data, we find data more and more as tool of narratives. With pattern recognition, exploratory data analytics, and especially with data visualization, data has re-centered from the quantitative to the qualitative.

More and more applications support us in using data to tell a story. Dashboards like Tableau or DataLion plug into our data sources and translate the numbers into a visual format that can be much more easily digested. Even highly multivariate data can deliver straightforward meaning to us when we use tools like Gephi, or say, the notorious Palantir. These tools also make social media analytics and text mining feasible techniques to research society, advertising, and markets.

Jawbone Up not only tracks our sleep. The app also shares our data in a meaningful way with our friends - like we share our thoughts on Twitter.
Jawbone Up not only tracks our sleep. The app also shares our data in a meaningful way with our friends – like we share our thoughts on Twitter.
Data driven storytelling has conquered most non-fiction publication. News publishers like New York Times or The Guardian employ huge teams of infographic specialists to enrich their reports with meaningful data visualization. Some of their editors have put together awesome collections of beautiful examples, e.g. informationisbeautiful.net.

Our most personal data however is generated on our mobile and wearable devices. On our smartphones, wristbands, or smartwatches, some twenty sensors continuously track our behavior and our actions. There is a plenitude of apps making use of mobile data: To support our training, to guide our routes, to find friends nearby, to share images, etc. etc.

Many people already share their daily workout via apps like Strava or Runtastic. It is even quite common to let such apps automatically post your training results into your social media timeline, e.g. to Twitter or Facebook.
Many people already share their daily workout via apps like Strava or Runtastic. It is even quite common to let such apps automatically post your training results into your social media timeline, e.g. to Twitter or Facebook.

Apps like Jawbone Up or Strava not only track our workout, they also provide for an easy way to share what data they measured. We publish our training data the same way there, as we publish our stories on Twitter or Facebook. Our data becomes equivalent to the texts and images we post. The most highly integrated version of this data-as-story so far is Google Now.

Image on top: Google Now. Google Now follows the idea to display all kinds of information in the form of tiles, like Twitter or Facebook would display the posts of the people you follow in a timeline. Funny enough, Google obviously has no clue where my "place of work" seams to be.
Image on top: Google Now. Google Now follows the idea to display all kinds of information in the form of tiles, like Twitter or Facebook would display the posts of the people you follow in a timeline. Funny enough, Google obviously has no clue where my „place of work“ seams to be.

Data is media not only regarding the content. Advertising which has by and large been data driven for decades is facing a major transformation. Media planning and buying – the art of placing ads in the most efficient way, i.e. optimizing effect for a given budget – is changing dramatically. About 20% of all ads are placed programmatic now. Programmatic buying means that an algorithm decides which exact user would be appropriate to watch the ad instead of buying the spot via explicit insertion order, as it used to be. The decision if a certain user would match with the campaign’s objective is made by predictions based on the users‘ observed behavior. Data thus drives the ads we get displayed.

With the idea of ‚The Quantified Self‚, data starts to conquer even the concept of our identity. We are not only what we tell, how we appear, how we act voluntarily, but we are as well defined by our innards, by our bodies‘ functions, the data that comes from our physical being. The concept of ’self‘ is changing by this notion, overcoming the strict separation of mind and body, of conscious and unconscious. The physical aspects of our lives now get equal credit, as being veritable part of our being ourselves.

Data is becoming integral part to our stories. It pervades through all the media. We should learn to see data as part of our lives the same way, we are used to tell about things with words.

Further reading:

We are content!
Data stories: From facts to fiction.