Advanced and Efficient Big Data Management and Analysis

Contributing key researchers: 
Christian S. Jensen (AAU)
Katja Hose (AAU)
Ira Assent (AU)
Jan Damsgaard (CBS)

Christian S. Jensen
Professor


Aalborg University
Department of Computer Science
Selma Lagerlöfsvej 300
9220 Aalborg Ø

E: csj@cs.aau.dk
T: +45 20 14 52 50
WS3

Relevance

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.

Objectives and synergies

The objectives 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.