In almost all areas of business, industry, science, and everybody's life, the amount of available data that contains value and knowledge is immense and fast growing. However, turning data into information, information into knowledge, and knowledge into value is challenging.To extract the knowledge, the data needs to be stored, managed, and analyzed. Thereby, we not only have to cope with increasing amount of data, but also with increasing velocity, i.e., data streamed in high rates, with heterogeneous data sources and also more and more have to take data quality and reliability of data and information into account. These properties referring to the four V's (Volume, Velocity, Variety, and Veracity) are the key properties of "Big Data". Big Data grows faster than our ability to process the data, so we need new architectures, algorithms and approaches for managing, processing, and analyzing Big Data that goes beyond traditional concepts for knowledge discovery and data mining. This course introduces Big Data, challenges associated with Big Data, and basic concepts for Big Data Management and Big Data Analytics which are important components in the new and popular field Data Science.

The seminar on Data Ethics is part of the MSc Data Science program at Ludwig-Maximilians-Universität (LMU) Munich. The course will be lead by Prof. Dr. Dieter Kranzlmüller and Fabio Genz.

Contents: The seminar is one part of the module Data Ethics and Data Security, which covers basic legal and ethical questions and challenges of data security. This course helps the students to prepare lectures on ethical and legal aspects of data ethics. Students are introduced to the technical, legal, and ethical issues of data security, especially when dealing with personal data or when planning experiments in Data Science.

Objective: Students will reflect on standard procedures and problems of data protection and learn technical methods to handle data responsibly.