TY - JOUR A1 - Kampe, Heike A1 - Horn-Conrad, Antje A1 - Zimmermann, Matthias A1 - Scholz, Jana A1 - Görlich, Petra A1 - Eckardt, Barbara A1 - Krafzik, Carolin ED - Engel, Silke ED - Zimmermann, Matthias T1 - Portal Wissen = Data BT - The Research Magazine of the University of Potsdam N2 - Data assimilation? Stop! Don’t be afraid, please, come closer! No tongue twister, no rocket science. Or is it? Let’s see. It is a matter of fact, however, that data assimilation has been around for a long time and (almost) everywhere. But only in the age of supercomputers has it assumed amazing proportions. Everyone knows data. Assimilation, however, is a difficult term for something that happens around us all the time: adaptation. Nature in particular has demonstrated to us for millions of years how evolutionary adaptation works. From unicellular organisms to primates, from algae to sequoias, from dinosaurs ... Anyone who cannot adapt will quickly not fit in anymore. We of course have also learned to adapt in new situations and act accordingly. When we want to cross the street, we have a plan of how to do this: go to the curb, look left and right, and only cross the street if there’s no car (coming). If we do all this and adapt our plan to the traffic we see, we will not just safely cross the street, but we will also have successfully practiced data assimilation. Of course, that sounds different when researchers try to explain how data assimilation helps them. Meteorologists, for example, have been working with data assimilation for years. The German Weather Service writes, “In numerical weather prediction, data assimilation is the approximation of a model run to the actual development of the atmosphere as described by existing observations.” What it means is that a weather forecast is only accurate if the model which is used for its calculation is repeatedly updated, i.e. assimilated, with new measurement data. In 2017 an entire Collaborative Research Center was established at the University of Potsdam, CRC 1294, to deal with the mathematical basics of data assimilation. For Portal Wissen, we asked the mathematicians and speakers of the CRC Prof. Sebastian Reich and Prof. Wilhelm Huisinga how exactly data assimilation works and in which areas of research they can be used profitably in the future. We have looked at two projects at the CRC itself: the analysis of eye movements and the research on space weather. In addition, the current issue is full of research projects that revolve around data in very different ways. Atmospheric physicist Markus Rex throws a glance at the spectacular MOSAiC expedition. Starting in September 2019, the German research icebreaker “Polarstern” will drift through the Arctic Ocean for a year and collect numerous data on ice, ocean, biosphere, and atmosphere. In the project “TraceAge”, nutritionists will use the data from thousands of subjects who participated in a long-term study to find out more about the function of trace elements in our body. Computer scientists have developed a method to filter relevant information from the flood of data on the worldwide web so as to enable visually impaired to surf the Internet more easily. And a geophysicist is working on developing an early warning system for volcanic eruptions from seemingly inconspicuous seismic data. Not least, this issue deals with the fascination of fire and ice, the possibilities that digitization offers for administration, and the question of how to inspire children for sports and exercise. We hope you enjoy reading – and if you send us some of your reading experience, we will assimilate it into our next issue. Promised! T3 - Portal Wissen: The research magazine of the University of Potsdam [Englische Ausgabe] - 02/2019 Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-442574 SN - 2198-9974 IS - 02/2019 ER -