Advanced and Efficient Big Data Management and Analysis​

The ongoing, sweeping digitalisation of societal and industrial processes represents a development that holds substantial potential for transforming society. Big data is a consequence of this development. Indeed, data has been termed the new oil, and data will play an increasingly important role in society and industry. As a result, it becomes increasingly important to be able to create value from data. This in turn calls for research that addresses challenges caused by big data.

The objectives for this workstream are:

  1. to invent new efficient and effective means of enabling value creation from big data and
  2. to develop software prototypes as a foundation for empirical studies and demonstrations with real-world data in collaboration with users.

The thematic area of Big Data involves the invention, integration, and empirical study of algorithmic techniques, and it involves analytics including machine learning and data mining. As such, Big Data has very substantial interfaces to the thematic areas Artificial Intelligence (in relation to machine learning) and Algorithms and Data Structures. There are also links to the thematic area Cyber Physical Systems and Internet of Things, e.g. in relation to distributed data platforms.

Further, there are links to the thematic area Human Computer Interaction, CSCW and InfoVis, e.g. in relation to the efficient visualisation of massive data. The area Business Innovation, Processes and Model is concerned in part with aspects related to introducing Big Data technologies into organisations. Finally, there are relations to the thematic area Ethics, e.g., in the areas of transparency and privacy.

Workstream related projects

Bridge project

Multimodal Data Processing of Earth Observation Data

The Danish partnership for digitalization has concluded that there is a need to support the digital acceleration of the green transition. This includes strengthening efforts to establish a stronger data foundation for environmental data. Based on observations of the Earth a range of Danish public organizations build and maintain important data foundations. Such foundations are used for decision making, e.g., for executing environmental law or making planning decisions in both private and public organizations in Denmark.

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Workstream manager

Aalborg University
Department of Computer Science

E: csj@cs.aau.dk
T: +45 20 14 52 50​

Contributing researchers

Frank Allan Hansen

Head of DxS Lab

The Alexandra Institute

Katja Hose

Professor

Aalborg University
Department of Computer Science

Ira Assent

Professor

Aarhus University
Department of Computer Science

Copenhagen Business School
Department of Digitalization

Jan Damsgaard

Professor

Copenhagen Business School
Department of Digitalization

Yongluan Zhou

Professor

University of Copenhagen 
Department of Computer Science

Arthur Zimek

Professor

University of Southern Denmark
Department of Mathematics and Computer Science

Hua Lu

Professor

Roskilde University
Department of People and Technology

Tung Kieu

Assistant Professor

Aalborg University
Department of Computer Science