Perspectives
on big data
It is not necessarily the size...
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Secure your data and protect
other people’s data too
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Where does data come from,
and how can we use it?
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Spot anomalies
with data analysis
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Large amounts of data require
more computing power
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Seven questions
(Big) data?
Learn how
to get started!
Big data is both a buzzword and a real catalyst for
growth. The data is out there, ready to be used. Big
and small.
Is your organisation venturing into (big) data, we
can guide you along the way. We have several
years’ experience of data analysis, computation and
consultancy on how to use big data.
In this booklet, we focus on where data comes from
and how to store, visualise, secure and collect it
– and not least how to create new business
oppor-tunities from the data.
Small data sets can
also create entirely
new business areas.
People often overlook what data is. There is a ten-dency to believe that it is only about large amounts of data. But data is many things, and for a business it is the art of finding out what data you have and can get access to - and to get someone to help you create an overview.
Data as a commodity
According to Dina Myrup Raabjerg, Head of Sales at the Alexandra Institute, we currently see several examples where data has become the actual commod-ity. Take the way we book hotel rooms and flights and the way we pay, for example: We process data that we already have, or can access, to create a new service or product.
- In Denmark, Vestas is a good example of a company that has taken data they already have and created a service in collaboration with Creuna. They have highly accurate data on how their wind turbines are being used. Just like your car is called in for service, Vestas has developed extra services that call in the wind tur-bines for repair, she explains.
It is not
necessarily
the size
Small data sets can
be extremely valuable
- both for your
custom-ers and your business.
Who are the obvious buyers of your data?
Vestas has access to highly accurate data on how much the wind blows where their wind turbines are lo-cated. So they asked the question: Who is this relevant to? Here farmers are obvious, and therefore Vestas made a weather service that can accurately predict when it is going to rain on a local farmer’s field. According to Dina Myrup Raabjerg, you have to ask yourself: What can improve my clients’ business, and who are the obvious buyers of the data? Small data sets can also be valuable - both to the customer and to your own business.
Improving city services
Another example brings big data into a helicopter perspective. Here is a video that makes you ask: What created the video?
https://www.youtube.com/watch?v=8J3T3UjHbrE
The short answer is that big data did. The video is pro-duced in collaboration with the Spanish bank BBVA and SENSEable City Lab at MIT and shows the consumption and purchasing patterns throughout Spain over Easter in 2011. The data is collected through BBVA’s banking network and is a visualisation of how 1.4 million cus-tomers and 374,220 businesses have performed more than four million transactions.
- If the consumption pattern is the same year after year, perhaps you can use the digital footprints people leave behind to better understand the city and our consumption patterns and to improve city services, she explains.
Where does data
come from and
how can we use it?
Jesper Nielsen, Senior R&D Engineer at the
Alexan-dra Institute, works with sensor technology,
elec-tronics, hardware and software development.
Here he explains where the large amounts of data
come from and gives us some examples of how to
use them.
Things communicate
We produce and store more data than ever before, and the development continues. This is the result of numerous sensors, a tremendous amount of commu-nication and analysis. Often, big data
uncovers otherwise hidden patterns or behaviours that we are now able to analyse and use by making them communicate.
Jesper Nielsen explains:
- Most of the current developments are actually about communication - that things are interconnected and able to talk to the Internet. That is the foundation of the Internet of Things. The things were there in the past, but they could not talk to each other.
- A major reason for the rapid development in data generation is that things have become connected. In the past, we had a modem or slow connection, and it was expensive to publish things on the web. Now everything has become wireless, and this has had a major impact, he explains.
Companies perform better with big data
To exploit big data, it is essential for a company to be able to handle the huge amounts of data. Often focus is on the technical aspects, and it can be difficult to focus attention on how to use big data to create value for the company and its customers.
- In addition to developing specific IoT software, the Alexandra Institute develops both hardware and soft-ware, Jesper says.
The great potential of using big data can be realised through a complex technology, and in this respect the Alexandra Institute has a very strong expertise. Ac-cording to Jesper, the Alexandra Institute is involved in several projects in which data is collected in different ways.
Companies can use the data to:
• create a better basis for making decisions
• obtain an overview
• optimise internal processes
• enhance business productivity
• focus sales promotion, for example by combining
internal and external data
• provide greater knowledge and understanding of
different customer groups
• predict sales and storage development
• develop new business areas both in existing and in
new companies
• develop smart systems and concepts based on big
data.
Spot anomalies
with efficient
data analysis
Enhanced computing
power has paved the
way for advanced data
processing.
Machine learning, data mining and data analysis have been fundamental concepts in computer science for decades. Now data analysis is becoming increasingly prevalent. In the past, it was not possible to perform data analysis due to the cost of processing power, but now we are able to process data much more cost- effectively.
Jan Neerbek, Senior IT Solutions Architect at the Alex-andra Institute, explains why the widespread use of big data and data analysis create new business opportu-nities.
Massive investments create positive spiral
According to Jan Neerbek, this area is undergoing a rapid development at the moment. A lot of money is being invested in the development of algorithms, data structures and processing platforms.
– In the area of machine learning, there is a lot of activity going on in a subfield called ‘deep learning’. This is a method used to build and train much bigger artificial neural networks, and the reason why we see this now is that deep learning is making huge advances compared to what was possible a few years ago. The old tools did not work in big neural networks. It was simply too difficult to train a neural network to learn anything rational, Jan Neerbek explains.
What deep learning does is to produce a method for splitting up the networks so that we can train them separately. Thus, we avoid the problems of oversized networks.
The computer could not see the ‘yellow cheese’
A keyword in deep learning is structure. You have to find the structure of a problem before you can deal with it. This makes sense in both audio and visual recognition where we can get an answer to questions that used to be too complex. This is useful in for ex-ample face recognition, speech recognition and better translation.
– In the past, the computer was not capable of under-standing that the ‘yellow cheese’ in a Pacman game was interesting because it could not detect all the pixels. The computer was unable to analyse the move-ments of Pacman. Present-day computers can analyse much more data, and that is a major step forward. It is also the reason why Google paid more than 500 million USD for the British company Deep Mind, he explains.
Recognises words in the same way as the brain
It can be hard for machines to recognise words and sentences fast and precisely. The Skype Translator software that runs on Microsoft’s servers is trained to recognise words in the same way as the brain. Ac-cording to Bill Gates, the ultimate computer will learn by itself, and he believes that within the next decade, deep learning will change the way computers work. Deep learning allows the computer to do things that were not possible in the past, and even though the area is still in its infancy, we will soon be using automated processes for processing data and making recommen-dations.
– Microsoft, Google and many others are develop-ing functional virtual assistants. The best example is Google Now that can plan your daily life, without you lifting a finger. It monitors your mobile phone and knows when you leave the office and can tell you if there is roadwork ahead or an accident on the high-way, Jan Neerbek explains.
Help with data analysis
Public and private organisations are required to pro-tect the personal data of citizens and customers. At the moment, we are doing a data analysis for Ud-budsVagten A/S – an organisation that scans public and private contract databases and offers contract services to its customers.
We develop a tool that uses data analysis to detect if private information, such as civil registration num-bers or medical history, is published on a website by mistake. Data analysis can also be used for monitoring urine output in hospitals. Therefore, we are developing an algorithm that automatically figures out whether a warning should be issued in case the urine concentra-tions are too high.
Data analysis can also analyse people’s online shop-ping behaviour. We have helped D60 to optimise and redesign their recommendation algorithm. D60 develops advanced intelligent datamining solutions for online shops, such as Den Blå Avis, Just-Eat and Bil-Basen.
Large amounts of
data require more
computing power
Computation and
visualisation of large
amounts of data.
The Alexandra Institute’s Computer Graphics experts struggle to compute large amounts of data much faster. Among other things, they have found ways to better exploit the potential of modern graphics cards, and their expertise is in demand when large amounts of data need to be computed and visualised. Our Computer Graphics experts develop solutions for the health sector because:
1. their method can compute extremely large amounts of data very fast
2. it provides higher quality
3. it opens up for entirely new ways of using scanning results for e.g. surgical simulation, collaborative solutions and diagnostics as a web service.
Case: Brainreader
When a patient has a CT or MRI scan, massive and complex data sets are generated, which take a long time to compute. In collaboration with the Alexandra Institute, Brainreader has significantly improved their brain scanner for detection of Alzheimer’s because computation time has been reduced from hours to minutes.
Case: QuantumWise
QuantumWise uses molecular visualisations for simu-lating electrical properties of e.g. chips at the nanos-cale. They wanted to be able to simulate on larger and more complex molecules, but real-time visualisation was not possible with existing technologies.
The solution developed by Computer Graphics Lab minimised the amount of data to be used as basis for the rendering and the number of times it had to be moved. This made the speed of the presentation 500 times faster, and it became possible to show signifi-cantly larger molecules.
Case: VES
A third example has been developed in collaboration with a surgeon from Copenhagen University Hospital. The Ear simulator is a surgical simulator that allows ear surgeons to train complicated and risky surgical procedures. The model they practice on is a digital version of a human head based on a large amount of imagery and data. The Capital Region of Denmark has introduced a compulsory simulation course as a tool in medical specialist training.
Case: Ultrasound scanners of the future
The Alexandra Institute is also involved in develop-ing the ultrasound scanner of the future. It must be small, handy and able to be connected wirelessly to the Internet so it can be connected to an iPad or other tablet. The scanner enables faster diagnostics for the benefit of patients.
- The project will radically change the potential of using ultrasound by making improved scanners which are so compact that some of them can fit in a pocket, says Professor A. Jensen from the Technical University of Denmark (DTU). Besides DTU and the Alexandra In-stitute, the Danish companies BK Medical, Meggitt and research groups from DTU and Copenhagen University Hospital participate in the project.
Jesper Mosegaard, lab manager at the Alexandra Insti-tute, explains:
- We work primarily with service-on-demand. More specifically, we use massive acceleration of compu-tations through GPUs in clouds to make advanced computations that provide new and better services to the clinical staff - while at the same time developing an ultrasound scanner that is both small and handy, he says.
Mads Sølvsten Sørensen, Peter Trier & Karsten Noe Steven Andersen & Daniel Sieber
Secure your data
and protect other
people’s data too
Security and privacy are
in focus the more we
use data – and the more
data we use.
According to Gert Læssøe Mikkelsen, security expert in the Alexandra Institute’s Security Lab, the increased focus on big data security is not just a challenge. On the contrary: It may open up new business opportuni-ties.
- EU’s proposed General Data Protection Regulation will impose stricter requirements on the handling and exchange of personal information. This is likely to have a big impact and may prevent the development of certain big data solutions.
- The increased focus on big data security and privacy enables us to act proactively and develop solutions that meet the regulation.
– Several organisations refrain from developing solu-tions for security concerns, but there is huge business potential in state-of-the-art security solutions. The Alexandra Institute’s Security Lab helps companies understand the security issues of specific contexts. We also advise companies on how to design and develop solutions that both meet the needs of businesses and comply with data protection regulation.
Secure data exchange between companies
There are two interesting aspects when we talk about big data and security. One involves citizens who are exposed to advertisements based on all kinds of data sets. The other involves companies who want to ex-change data – for example in connection with Supply Chain Management.
- Secure Multiparty Computation (SMC) is an efficient technology for secure data exchange. In the research project COBE (Confidential Benchmarking), we have taken part in developing an SMC-based solution that facilitates the correlation of certain data, which would otherwise be problematic seen from a security per-spective, says Gert Læssøe Mikkelsen.
SMC allows a number of servers to jointly compute any function without learning the inputs to the function. Using the right cryptographic tools, the servers can work together and compute the result, which will never be compromised.
Secure authentication and privacy protection
Another example is the technology Attribute-Based Credentials (ABC), which supports both secure authen-tication and privacy protection, for example in con-nection with electronic ID cards, which become more and more common. The Alexandra Institute has been involved in the EU research project ABC4Trust that develops privacy solutions for this type of systems.
- The objective was to establish an overall architecture and a common platform for existing ABC systems. The solution reduces the amount of information you have to give about yourself, and you do not reveal any information unless you want to. This provides an extra level of quality and service to the users and reduces the risk of data being compromised, says Gert Læssøe Mikkelsen and adds:
– SMC and ABC are only two examples of technologies that have a potential within security and privacy in a big data context.
Seven questions
about health data
Big data across sectors
in tomorrow’s health
services.
Lab Manager for Pervasive Healthcare Lab, Morten Kyng, explains the scope of big data in the Danish healthcare system. What are the advantages of using data across sectors and what threats should we be aware of among these opportunities?
What is the challenge of the way we collect and use health data today?
The major challenge today is that we access health data across different systems and standards. General practitioners, hospitals and health care workers in mu-nicipalities use different systems that do not commu-nicate. This causes confusion and extra work because the various institutions only have the data that has been actively sent to them. At worst, it may result in serious errors, because you do not have the necessary information. An example is a lung transplant patient who was close to getting inappropriate medication as the doctor was unable to see that she had had a transplant, for which reason she was intolerant to the medication in question.
What is the goal of your project?
The goal of telemed.nu is to look into all aspects of telemedicine. This includes studies of telemedicine users, development of organisational and economic models to manage telemedicine along with a technical infrastructure that supports telemedicine. With regard to technical infrastructure, our goal is to provide se-cure and centralised data storage that can be accessed by everyone in the proper way. We use international standards that have been developed in advance so that people can participate worldwide.
How far is the progress on sharing electronic health data in Denmark?
Denmark is at an advanced stage. But it is based on different national standards. Unfortunately, it is ex-pensive to develop and maintain proprietary stand-ards. In addition, it is more difficult to attract inter-national suppliers, and it is not easy for the domestic suppliers to bring their solutions based on national standards abroad. By using international standards, we can achieve greater flexibility for both suppliers and buyers.
Why are common systems
and international standards so important?
For example, it is important that we all use the same units of measurement. It means that we all have the same starting point, and when dealing with patients and lives even the smallest discrepancies can be crucial.
Can you give an example?
Outside the health sector we had, for example, the Mars Climate Orbitor. It crashed because they used data based on different measurement units, so both sea miles and ordinary miles were at stake. This is a good example of how wrong things can go if we do not speak the same language.
Why is big data and healthcare a good match?
Big data is a buzz word, which is subject to different meanings. I find our work interesting in relation to big data because we create the possibility of having a cen-tral data repository with machine-readable content. It becomes really interesting if you connect it with other data such as metrological or demographic data and use big data algorithms. This might help us detect incipient critical illnesses.
What are the dangers if we get easier access to health data?
It is clear that the citizens’ data must be protected and the necessary security measures must be taken. Afterall, the citizen owns his own data and must give his consent in order for other people to look at it. The data neither is nor should become publicly available, but as long as the security aspect is observed, I see only advantages in creating a centralised healthcare data repository.
The Alexandra Institute is a privately owned,
non-profit company that works with applied IT
research, development and innovation. Our mission
is to create growth in society.
We help public and private organisations to
develop innovative, IT-based products and
services based on cutting-edge IT research.
We turn
research into
societal value
*
The Alexandra Institute is a member of GTS – Advan-ced Technology Group – a network of nine indepen-dent Danish research and technology organisations. Our primary focus is communication technology in products and surroundings.
Contact us
Rasmus Vedel
Business Development Manager +45 30 95 65 35
