The Danish Centre for Big Data Analytics driven Innovation (DABAI) is the name of a new big data research centre that was inaugurated on Friday 27 May at Aarhus University by Dean Niels Chr. Nielsen, Science and Technology. The Department of Computer Science plays a key role in DABAI, where big data will be systematically analysed to solve business-related and societal challenges in areas such as public administration, logistics, the environment, education, food and the agricultural sector.
The number of bytes of data generated every day from the web, social media, apps, production equipment and sensors in cities and buildings amounts to 2.5 quintillion (2.5 followed by 17 zeros). This corresponds to the content of 57.5 billion iPads (32 GB) – daily. However, less than three per cent of the enormous amounts of data are analysed and converted to knowledge and innovation.
Something will now be done about this in a new community partnership called the Danish Centre for Big Data Analytics driven Innovation (DABAI). With a total budget of more than DKK 117 million, researchers and business people at DABAI will over the next four years develop efficient and useful methods and tools to analyse big data. The centre is the first of its kind in Denmark, where large amounts of data will be systematically and efficiently used to find solutions to challenges in areas such as public administration, logistics, the environment, education, food and the agricultural sector.
Large audience at the opening
“The accelerating technological development is changing our daily lives by leaps and bounds. DABAI will help to create spaces and frameworks in which entrepreneurship, collaboration and an international outlook prosper, so that ideas, knowledge and technologies are converted to viable businesses and innovative solutions for the benefit of society,” said Dean Niels Chr. Nielsen, Science and Technology, on Friday 27 May when he opened DABAI in the Peter Bøgh Andersen Lecture Theatre at IT City Katrinebjerg.
The lecture theatre was packed with visitors who had come to hear representatives from universities and companies provide specific examples of previous big data projects, and which projects will be in focus at DABAI. The centre will be under the project management of the Alexandra Institute – a role that Professor Ole Lehrmann Madsen, CEO of the institute, described in advance when he presented the project’s participants on Friday.
Better hospital logistics to ensure shorter waiting times
The Department of Computer Science at Aarhus University plays a key role in DABAI, and will be involved in a number of projects in the centre’s three main business areas: public data, food industry data, and data from IT-based learning.
One of the initiators of the centre is Professor Kaj Grønbæk, Department of Computer Science, who is primarily responsible for the Interactive Visual Analytics area of research. In a previous project called PosLogistics, he developed a system to improve porter-related logistics based on indoor positioning in collaboration with Systematic – an IT company in Aarhus – as well as Aarhus University Hospital and Aalborg University Hospital.
At DABAI, Professor Grønbæk and Systematic will take this work further to analyse large amounts of anonymised patient flow data in order to understand all the detailed patient flow and to improve the hospitalisation process right through the hospital. The aim is to have fewer cancellations of operations, shorter waiting times and better utilisation of resources – and thereby better patient treatment.
Geodata can be used to predict flooding
Another DABAI initiator from the Department of Computer Science is Professor Lars Arge, who has the main responsibility for one of the project’s focus areas – public data. Professor Arge is also director of the Danish National Research Foundation’s Centre for Massive Data Algorithmics (MADALGO) at Aarhus University.
Based on algorithmic research, Professor Arge previously developed in collaboration with SCALGO a unique online tool to predict flooding called SCALGO Live. In the DABAI project, Professor Arge and SCALGO will work together with companies and authorities including Orbicon, the Central Denmark Region, the Danish Meteorological Institute (DMI) and the Agency for Data Supply and Efficiency to develop tools that enable the state, municipalities and utilities to predict flooding and reduce negative after-effects of climate change. The tools make it possible to update and interact with data, and to simulate the impact of rising waters and cloudbursts. This means that decisions can be made on a very safe basis regarding where investments have the greatest effect to safeguard against climate change and flooding.
Facts about DABAI
DABAI stands for DAnish Centre for Big Data Analytics driven Innovation.
The project is led by the Alexandra Institute, and the remaining core players are the computer science departments at the University of Copenhagen, the Technical University of Denmark and Aarhus University, as well as companies including Systematic, Visma and BusinessMinds, and authorities such as the Danish Agency for Digitisation, the Danish Business Authority and the Central Denmark Region. A considerable number of other private and public companies will also be involved in specific case activities at the centre.
The aim of the collaboration is to develop general techniques and methods in the areas of analysis algorithms, machine learning and interactive visual analysis, all of which can be reused cutting across a number of cases in three business areas: public data, food industry data, and data from IT-based learning, where the many companies involved in DABAI have a clear business potential.
DABAI has an initial budget of more than DKK 117 million for a period of four years from March 2016, DKK 45 million of which is financed by a grant from Innovation Fund Denmark. The remaining budget consists of self-financed contributions from the participating partners, including DKK 5 million in direct support from the Central Denmark Region.
Read more about DABAI here.