Abstract: Provided is a method for anonymizing datasets having sensitive information, including the steps of determining a dataset of records to be assigned to aggregation clusters; computing an average record of the dataset on the basis of a predefined repetition counter; finding a most distant first record to the average record using a distance measure; finding a most distant second record from the first record using the distance measure; forming a first aggregation cluster around the first record and a second aggregation cluster around the second record; and generating a new dataset by subtracting the first cluster and the second cluster from the previous dataset.

Abstract: A method and module for detecting dependencies of at least two data streams of sensor measurements is provided, which are recorded on a technical device, in particular in an energy generation device, including: an input interface which is adapted for capturing the streams of sensor data from sensors, a data structure for analysis in form of a sliding window which is incrementally moved over the respective streams of sensor data so that there is an overlap between consecutive windows, and a processor, which is adapted to apply an entropy-based algorithm on the data within the sliding window for calculating data stream dependencies, while incrementally moving the sliding window, wherein only updated data in the sliding window is processed by the entropy based algorithm.

Abstract: Provided is a method for anonymising data stocks, including the steps of determining a combination of generalization stages for quasi-identifiers of a data stock at a central node; transmitting the combination of generalization stages to a plurality of sub-nodes; and a parallel performing of an anonymisation of the data stock on the basis of the combination of generalization stages by the sub-nodes.

Abstract: Provided is a method for anonymising data stocks, including the steps of determining a combination of generalization stages for quasi-identifiers pf of a data stock at a central node; transmitting the combination of generalization stages to a plurality of sub-nodes; and a parallel performing of an anonymisation of the data stock on the basis of the combination of generalization stages by the sub-nodes.

Abstract: Provided is a method for anonymizing datasets having sensitive information, including the steps of determining a dataset of records to be assigned to aggregation clusters; computing an average record of the dataset on the basis of a predefined repetition counter; finding a most distant first record to the average record using a distance measure; finding a most distant second record from the first record using the distance measure; forming a first aggregation cluster around the first record and a second aggregation cluster around the second record; and generating a new dataset by subtracting the first cluster and the second cluster from the previous dataset.

Abstract: A method and module for detecting dependencies of at least two data streams of sensor measurements is provided, which are recorded on a technical device, in particular in an energy generation device, including: an input interface which is adapted for capturing the streams of sensor data from sensors, a data structure for analysis in form of a sliding window which is incrementally moved over the respective streams of sensor data so that there is an overlap between consecutive windows, and a processor, which is adapted to apply an entropy-based algorithm on the data within the sliding window for calculating data stream dependencies, while incrementally moving the sliding window, wherein only updated data in the sliding window is processed by the entropy based algorithm.

Abstract: A device is provided for determining an investment solution. The device includes a global unit being configured to: (1) send an investment indication on an investment amount to a plurality of local units, each local unit being associated with an investment area and being configured to determine a plurality of local investment solutions for the associated investment area based on the investment amount, (2) receive the plurality of local investment solutions from each local unit, and (3) determine a plurality of global solutions based on the received local investment solutions. The device also includes an optimization unit being configured to: (1) display the plurality of global solutions in a diagram together with associated investment effects, (2) receive a user input for adapting the diagram illustrating the plurality of global solutions, and (3) determine an investment solution from the plurality of global solutions based on the adapted diagram.