If it’s smart, you can wear it!

It started with the first smart clothes in 2006, motivated luxury brands like TAG Heuer of LVMH to add some smartness to their watches and even lets farmers recognize patterns in dairy cow movements: wearables have become mainstream.

At our Wearable Data Hack this June, we partnered with Wearable Technologies, a Munich based company specialized in marketing wearables. One part of our hackathon’s prizes were tickets to the 2016 Wearable Technologies Conference, taking place in Munich, January 26-27. Looking at the impressive lineup of speakers at the conference, we’re sure that our winners will learn a lot about the near future of wearables!

If you also want to attend the conference, you might want to use this special link and our friends&family code Datarella_Friends for receiving a 15% discount. 

See you at the Wearable Technologies Conference 2016 in Munich!

Know And Speak To Your Customer Through The IoT

Equipped with sensors and microchips, ever more of objects can communicate, with each other and with human beings – the Internet of Things and Humans is born. Even washing powder is set to become smart through attached sensors on its packaging that detects when the product is being used, and that communicates with readers like smartphones when scanned. From today’s 5 billion to 21 billion by 2020, the number of wirelessly connected things will increase. 

Who will profit from the Internet of Things – or IoT – most?
Let’s look at the obvious applications, first: Stock-keeping and supply-chain management processes will have implemented technologies making objects communicating with each other, thus enabling businesses to follow the progress of their products from factories to shops to end-consumers. Espresso beans will tell baristas about the best temperature to keep them in stock. Batteries will inform their owners when reaching the last phase of their power-providing lives.
From our perspective, however, the biggest potential lies in customer relations. Brands are realizing that the best way to sell their products is to build personal relations with customers rather than to spend lavishly on marketing. Until today, many brands come only second behind retailers with regards to communication to their customers. Often, it’s the retailer who knows the customers‘ preferences best, and who is able to retain them through loyalty schemes. Ask yourself: where do you buy your stuff? Online retailers are the ones understanding their customers best, often they have the complete customer journey available.

Speak to your customer
Now it becomes cheaper to add sensors and microchips to products, and to connect them to the internet. The direct result of the IoT is a huge influx of customer or end-user data. Whereas nobody at manufacturers and brands had to – or better: was able to – gather data of actual customer behavior so far, there now arrives Big Data describing everything these companies have ever wanted to know. In theory, this data will help them develop their products and services more rapidly, fix any bugs more quickly and tailor products better to their end-users‘ needs.

In practice, the gigantic flood of data may imply significant structural changes for manufacturers: is the IT infrastructure set to cope with Big Data? Is the IT personnel eqipped with the necessary knowledge amd experience to handle data sampling and dara storage correctly? Are there adequate in-house resources to munge and analyze the data? And, after all, will anybody visualize and instrumentalize the data in a meaningful way? Sure, there already are best practices regarding individual steps of this Big Data process. And for each part of the process, there are tools that can be used a software-as-a-service. But it`s a long way from data sampling to a smoothly managed customer relation through objects.

A new era of competition
Managing and optimizing the company’s own customer relations through the IoT is just one part of the equation: when retailers start a direct communication with their end-users, retailers won’t passively stand on the sidelines. They will fight back trying to defend their position of being „first-to-the-customer‘. And on the operative level, retailers have a big advantage: they have always been the ones with a direct contact to the customer. They know their customers (or at least they should). Everybody who switched from working in a company without direct contact to the customer to an end-user shop has experienced a cultural clash: you won’t imagine the expectations of a typical end-user – i.e. ourselves. Let alone all additional privacy and cyber-security issues.

That said, the IoT offers manufacturers the biggest opportunity since the industrialization. They can understand and learn from their customers. They can even partner with them. But first they have to do their homework and provide all the needed resources in IT infrastructure, processes, and human resources.

Predictive modeling – an interview with Datarella CEO Joerg Blumtritt

Most of the time, we at Datarella deal with the very near future: what will be the most likely thing that individuals want or what they are up to next? We use mathematical models to predict human behavior. But not only human behavior is what Datarella is interested in. Research papers, internal customer data and external data are being used by Datarella to predict probabilities of success of specific products. We detecs patterns, weaknesses and events in behavior and product design and – together with our customers – we define workarounds, optimizations or completely new data-driven products.

Wearable Data Hack 2015 – Official Announcement

Wearable Data Hack 2015 – Official Announcement

Munich, 19 June 2015 – On the weekend of June, 19-21, Stylight, Datarella and Macromedia University proudly present the first hack day on wearable tech applications, data and design – the Wearable Data Hack 2015. the Wearable Data Hack 2015 will be the first occasion for most of the participants to share their views and ideas and jointly gather experience with the new data realm.

Apple calls the Apple Watch “Our most personal device ever”. And with good cause: The data from wearable tech, smartphones and smartwatches are really the most personal data ever. Our mobile devices accompany every step we take, every move we make. A plentitude of sensors on the devices draw multidimensional pictures of our daily lives. Applications of wearable data range from fitness to retail, from automotive to health. There is hardly an industry that cannot make direct use of it. And yet, wearable apps are still in their childhood.

Telling the stories of people’s lives

Wearable data is not an end in itself. Data is the raw material of our behavior. After data has been collected it has to be analyzed. There are algorithms which define the semi-finished results – these have to be enriched with other, contextual data. Analyzed and enriched data result in stories describing our lives.

Data & Design

For decades, designers have been seeking to design products to meet the seemingly never-ending rise of consumption. Since then, we appear to have evolved from an industrial economy to a knowledge- and data-driven economy. New models of thinking and new patterns of behavior and social values appear. Design thinking seems to provide some answers – it focuses on a human-centered approach, which combines design activities with research on human needs, and technological and business aspects, in order to create knowledge and solutions for highly complex problems.

The tracks

Hackers, designers and thinkers can choose from these tracks:

– Data-driven business models for wearables
– Data-driven wearables
– Smartphone app (Stand alone / comb with smartphone)
– User Experience
– Design
– API
– Open Data / Shared Data
– Medical data / mHealth

We invite hackers, designers and thinkers to meet each other, to discuss and find ways of using data in order to tell the people’s lives and create examples of socially relevant technology.

The date

Friday, 19 June – Sunday, 21 June

The location

Stylight, Nymphenburger Str. 86, München.

Stylight’s lofty office is well established as one of Munich’s coolest venues for Hackathons and perfectly suited to accommodate up to 100 participants.

The organizers

STYLIGHT is the first ‘shoppable’ fashion magazine in Germany. The STYLIGHT editorial team creates the best inspirational content every day, satisfying all the lifestyle news their users crave. No matter whether it’s fashion, beauty or stars – STYLIGHT is the number one website for inspirational excellence linked with innovative online shopping technology. With STYLIGHT you will never miss out on a trend again and can shop featured products instantly from all your favorite online stores.

Datarella is the mobile data technology company. The Munich-based startup taps into smartphones and wearable devices to harvest the data. Datarella supports data-driven analytics and product development for connected cars, smart home, mHealth, and retail.

Macromedia University follows these developments in its capacity as a university, and conceives itself as a place for reflecting on all aspects of media society. Our courses of study cover the broad spectrum of modern media careers, from management, and content jobs such as journalism, to the creative fields of design, gaming, and film and television. With over 80 professorships and over 2000 students in all five media centers of Munich, Stuttgart, Cologne, Hamburg, Berlin and Milan, the University trains the next generation of media talent for an international media society.

Telling the story of people’s lives – Strata+Hadoop, Feb 15, San Jose

We can draw a colorful picture of people’s everyday lives from the data we collect via smartphones. To tell the data-story, we need to translate the raw measurements into meaningful events, like “driving a car”, “strolling in a mall”, or even more intimate, like “being nervous”. We will show how to access the phone’s data, how to derive complex events from the phone’s raw data, and how to bring it into a meaningful story, and how to make it work for businesses.

Cases we’ll show: an app for the automotive industry to support ecological driving, learning about preferences of Chinese passengers at an international airport, and supporting people suffering from osteoporosis to stabelize their condition and maintain mobility.

More on Strata+Hadoop

 

Wearable Data Hack Munich 2015

Today, we would like to announce something special. Something we can’t wait to take place and until mid June it’s going to be tough to sit tight. Please, feel invited to our Wearable Data Hack Munich 2015!

The Wearable Data Hack Munich 2015 is the first hack day on wearable tech applications and data. It will take place right after the launch of Apple Watch – the gadget we expect to rise the tide for all wearables. Withe the Wearable Data Hack Munich 2105, we aim to kick-off app development for the emerging smartwatch and wearable tech market. During this weekend you will have the first occasion to share your views and ideas and jointly gather experience with the new data realm.

Apple calls the Apple Watch “Our most personal device ever”. And with good cause: The data from wearable tech, smartphones and smartwatches are really the most personal data ever. Our mobile devices accompany every step we take, every move we make. A plentitude of sensors on the devices draw a multidimensional picture of our daily lives. Applications of wearable data range from fitness to retail, from automotive to health. There is hardly an industry that cannot make direct use of it. And yet, wearable apps still are in their childhood. The Apple Watch will be hitting the street in April and will get the ball rolling.

The Wearable Data Hack Munich 2015 is jointly organized by Stylight and Datarella.

THREADS TO BE PURSUED
Developers, data geeks and artists will pursue one or more of these threads:
– Data-driven business models for wearables
– Data-driven wearables
– Smartphone app (Stand alone / combined with smartphone)
– User Experience
– API
– Open Data
– mHealth / Medical Data

So let’s explore what we can do with this data! Let’s play with the possibilities of our wearable gadgets and mobile sensors.

APPLICATION
To apply for the Wearable Data Hack Munich 2015, please send us an email with
– your name
– your profession
– your take on wearable data
– 3 tags describing yourself best.
Don’t wait for too long – the number of participants is limited.

For more information, please have a look here! See you at Wearable Data Hack Munich 2015!

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.

 

Sharing Goods And Sharing Data: Both Is Fun, Big Business And A Social Responsibility

Around 2010, Lisa Gansky coined the term Sharing Economy, or Mesh companies, offering their customers efficient shared access to their products instead of selling their products to them. Recently, it’s being called Collaborative Consumption or Collaborative Economy. It’s all about finding ways to make better use of valuable resources that have remained unused. Convenient access is being made affordable to people who can’t afford different products, or simply don’t need to own those products since they would only use them infrequently.

Typical mesh businesses like AirBnB, LendingClub or Cookening, demonstrate the power of sharing in very different ways: AirBnB is on the way to pass Hilton as the world’s largest hotelier in 2015, that is 7 years after its inception. The US peer-to-peer lending company Lending Club has originated over 4 billion USD in loans – it was originally founded as a Facebook app in 2006. The typical Mesh business runs a stylish app with a high usability. It’s service is new, easy to use and affordable. But all that does not fully explain the tremendous speed they conquer one market after the other. Who is the driver behind the Sharing Economy and it’s success?

It’s the user.
It’s the user. The user offers and asks for private overnight stays on AirBnB, the user provides and lends money on LendingClub. Even with services like Zipcar, when the product is provided by a company, the user „uses“ a product instead of buying and owning it. He has to rely on other users‘ good maintenance of Zipcars, since if there were too many ‚abusers‘ the company had to raise rates and the product would become unaffordable for most people. The same is true for AirBnB and others: users have to be sure that landlords don’t sell cubbyholes to them, whereas – vice versa – landlords have to trust their guests not to steal the TV or destroy the flat. So, the user has to use the service and she has to behave in an orderly manner – this is the foundation for a properly working and successful Sharing Economy.

The Sharing Economy

Image: The Sharing Economy, Latitude

Now let’s adopt the principles of the Sharing Economy to the individual who shares her statuses with her social graph on Facebook, discusses the latest news on Twitter and shares her preferred fashion designs on Pinterest. She dos it because she wants to express herself and she wants to communicate with a wider circle of friends than she can meet in person. She communicates in both, synchronous and asynchronous ways. She has learnt that the more she adds to discussions, the more she gets in return. In Social Media, she experiences the Pay-it-Forward principle in action at its best.

Sharing Economy has attained full age in 2014
Let’s assume we can all agree on that: communication openly and actively, sharing ideas, opinions, homes, cars, money and much more with others is not an extravagant imagination of Utopia, Inc., but a multi-billion dollar business eclipsing traditional business models around the world. Furthermore, it’s not just a gigantic business but a sympathetic and friendly way of matching supply and demand of individuals. Who wouldn’t prefer an individually furnished private home over a standard hotel room?

If we agree on the power of sharing the above mentioned martial and immaterial goods, can we also agree on the power of sharing data? Our data? Our own body’s data? Can we agree on the tremendously positive and socially relevant effects of sharing the data we produce ourselves, day by day? If you own a smartphone (you most probably will), you produce about 20 MB of smartphone data (i.e. data racked with your smartphone’s sensors) each day. Perhaps you haven’t been aware of that fact, or you just didn’t know how relevant this data could be for yourself, and for your social graph, respectively. Do you know how much you move each day? The U.S. Surgeon General wants you to move at least 10,000 steps a day to prevent and decrease overweight and obesity. (It’s very easy to know your steps: just get yourself one of those fitness trackers.)

And, did you know that your Vitamin D level is one of the key drivers of your well-being? Most North Americans, North and Central Europeans suffer from a Vitamin D deficiency. Do you actually know your Vitamin D level? Do you know that you can find it out yourself?

Let’s get more complex regarding data: microbes in the human body are responsible for how we digest food and synthesize vitamins, our overall health and metabolic disorders. The aggregate of microbes is called microbiome. Do you have any idea about your individual microbiome? Do you know that you can find out about your microbiome yourself, by using a simple kit?

Sharing Data still in its infancy, but…
So far, we have talked about the relevance and value of our data for ourselves. But – weren’t you interested in preventing your first stroke because thousands of other men at your age have provided their heart and respiratory rates anonymously and based on the analysis of this data you had been warned early enough to take appropriate action?

Wouldn’t you agree that the Pay-it-Forward principle works perfectly in the field of personal body data? The difference to the AirBnB model is that you provide your body data anonymously. It will be aggregated and used in a way that nobody knows that’s you behind your data. Since data analysis and respective actions or recommendations rely on big data, it’s necessary that many people participate and share their own data.

… will become a Social Responsibility in 2017
Today, in late summer of 2014, many people are sceptical and hesitate to provide their data. We think that personal body data sharing will be regarded as quite normal within a few years. If this movement takes up the same speed as the Sharing (Goods) Economy, it will be accepted as „normal“ within 2-3 years. We believe, that data sharing will become a social responsibility, comparable to fasten one’s seat belt or wearing a bike helmet. It probably won’t be called data sharing since this is a B2B term. There already is a very good term  – the Quantified Self, or QS. The term itself does not include the sharing element. But for every active members of the QS movement sharing is a relevant part of the quantification process because the value of an individual’s data is even bigger if used for general purposes.

We regard data sharing – our Quantified Self – as one of the most important movements of modern times and we would love to know how you think about it: please comment, provide us with your feedback: do you already share your data? How do you do it? Or, are you still sceptical?

Feature Image: Max Gotzler of Biotrakr, presenting findings of a Testosterone study at #QSEU14