Smart Data Technologies

While Big Data can be seen as the result of digitalization of former analog data sources and the emergence of digital data sources, we understand Smart Data as an added value to the economic and social realms, given the increasing amounts of data. The infrastructure that analyzes data is diverse, yet not fully able to deal with the soaring amount of data being generated in real-time by multiple sources. Below we give an overview of the current challenges in the area of data source and storage, data analysis, infrastructure, as well as human-machine interactions.


Data Acquisition

Every minute, massive amounts of data are created by billions of devices: i.e. smartphones, wearables, social media or cyber-physical systems. How can these data masses from different sources be combined and made available for analysis?

Data Management

What needs to be done to achieve and maintain certain qualities of data, which are prerequisite for meaningful analysis of large repositories and data streams? Which tools can be used?

Data Analysis

How to convert Big Data into Smart Data: meaningful analysis of large amounts of data. But how can long and comprehensive processes like this be designed fault tolerat and with minimal statistical errors so that the results are reliable?

Data Visualization & User Interaction

Only new forms of visualization and interaction make results of data analysis interesting for large user groups. Which requirements will have to be met by intelligent devices of the future so that they can be used in different use cases and according to human needs?