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Ausgewählte Projekte

Die Ideen des Kernprofilbereich werden in zahlreichen Einzelprojekten umgesetzt, wie z.B. in Masterarbeiten, deren Themen interdisziplinär sind und deren Betreuer aus verschiedenen Fachbereichen stammen.

Zudem kann das KPA mit eigenen finanziellen Mittel Projekte unterstützen. Im April 2023 sind die ersten Projekte (KPA 001 - KPA 006) dafür ausgewählt worden.

KPA 001 (started)

Prof. Dr. Andreas Vogelsang - Informatik - Software and System Engineering

Evaluating Software Quality of Research Software

Software becomes more and more important to research. (…) We are interested in inspecting which software development best practices are applied and which relevance code quality has in research software. The results will give insight into current code quality and provide possibilities for improvement of the quality and correctness of the programs used. More specifically, we want to answer the following research questions:

  • RQ1: Which role does code quality currently play in research software?
  • RQ2: How “good” is research software in comparison to other open-source (and commercial) software?#
  • RQ3: How can we improve productivity and code quality in research software? By answering these three research question, we will be able to identify further topics that will investigate further as part of KPA initiatives or offer as training for researchers.


KPA 002 (started)

Prof.'in Dr.'in Christina Bogner – Geographie - Ökosystemforschung

Establishing a modelling framework for agent-based models

with  Marijn van der Meij, Tim Reichenau, Andreas Bolten, Tony Reimann, Georg Bareth, and Karl Schneider

Agent-based models (ABMs) are known as a tool to model interactions between human agents in economics (Farmer and Foley, 2009) or social sciences (Bankes, 2002) or human-environment interactions (An, 2012). It is one of the methods to approach complex systems. Some even call them “a bridge between disciplines”‘ (Axelrod, 2006). ABMs are related to game theory; however, they can encompass more complex behaviour. Given their power to approach complex systems, we feel that ABMs should be part of the KPA’s repertoire of models to help answering pertinent questions relating to human-environment interactions within the Earth System Sciences. Eventually, ABMs could even be a link between the KPAs “Social and Economic Behavior” and “Intelligent Methods for Earth System Sciences”. ABMs require a thorough implementation to run at a reasonable speed. The (relatively) new language for data analysis, Julia (https://julialang.org/), promises such a framework for a successful implementation (https://github.com/juliadynamics/Agents.jl/). Thus, we suggest trying Julia’s capacity to provide a framework to implement ABMs. As a case study, we will use the research questions arising in the project A05 “Future roads” in the CRC 228 related to land-use change and development of a road network.


  • Farmer, J. D. and D. Foley (Aug. 2009). “The Economy Needs Agent-Based Modelling”. In: Nature 460.7256, pp. 685–686. issn: 1476-4687. doi: 10.1038/460685a. (Visited on 04/17/2023).
  • Bankes, S. C. (May 2002). “Agent-Based Modeling: A Revolution?” In: Proceedings of the National Academy of Sciences 99.suppl 3, pp. 7199–7200. doi: 10.1073/pnas.072081299. (Visited on 04/17/2023).
  • An, L. (Mar. 2012). “Modeling Human Decisions in Coupled Human and Natural Systems: Review of Agent-Based Models”. In: Ecological Modelling. Modeling Human Decisions 229, pp. 25–36. issn: 0304-3800. doi: 10.1016/j.ecolmodel.2011.07.010. (Visited on 04/17/2023).
  • Axelrod, R. (Jan. 2006). “Chapter 33 Agent-based Modeling as a Bridge Between Disciplines”. In: Handbook of Computational Economics. Ed. by L. Tesfatsion and K. L. Judd. Vol. 2. Elsevier, pp. 1565–1584. doi: 10.1016/S1574-0021(05)02033-2. (Visited on 04/17/2023).


KPA 003 (started)

Prof.'in Dr.'in Christina Bogner – Geographie - Ökosystemforschung

Establishing and testing a digital lab notebook

with Stephan Opitz

Electronic lab notebooks (ELN) are an important tool to ensure data safety and reproducibility of experimental results in a lab. It is part of a thorough research data management (https://fdm.uni-koeln.de/serviceangebot/servicekatalog-1). At the Faculty of Mathematics and Natural Sciences, we have the opportunity to test the software eLABJOURNAL. In this proposal, we suggest to test eLABJOURNAL in the Laboratory of the Institute of Geography within the working group Ecosystem Research and to report whether this software can be used more broadly within the KPA to e.g., exchange protocols between different working groups and coordinate our technical infrastructure (Großgeräte) more efficiently.


KPA 004 (starting soon)

Prof.'in Dr.'in Christina Bogner – Geographie - Ökosystemforschung

Establishing a framework for development of Shiny Apps for teaching

with Andreas Bolten

Shiny apps written in R (https://shiny.rstudio.com/) are interactive web apps. They can be used to teach e.g., statistics (https://stattlc.com/2021/08/17/ooh-shiny-r-shiny-apps-as-a-teaching-tool/) to beginners or for serious applications like reporting about systematic literature search according to PRISMA (https://estech.shinyapps.io/prisma_flowdiagram/.) We suggest (i) developing shiny apps for teaching within the KPA and (ii) creating teaching material that can serve to teach students to program such apps themselves. In order to deploy Shiny apps, a Shiny server is needed. To setup it, we kindly request the assistance of the KPA and in particular from Dr. Katja Sperveslage.


KPA 005 (started)

Prof.'in Dr.'in  Tatiana von Landesberger – Informatik – Visualisation and Visual Analytics

Dashboard Visualization for Atmospheric Rivers

The visualization of meteorological data requires effective and efficient interaction possibilities. Meteorological data have specific characteristics to be taken into account. Especially multiple aspects of data measurements on arctic atmospheric rivers. The use of visualization for publication purposes – in papers or online – requires a high amount of data accessibility and readability provided through a high number of filters and display options.

Our goal is to develop, implement and evaluate a novel dashboard visualization on meteorological data as well as to improve the given dashboard on atmospheric rivers designed during the “Visual Analysis Lab”. The output of the project can be used by all researchers in KPA.


KPA 006 (started)

Prof. Dr. Tony Reimann - Geographie – Geochronologie und Geomorphologie

Design and implementation of a soil-sediment database system for complex geoscientific and spatial data

Due to progress in experimental technology and computational processing, geoscientific research produces increasingly more and more complex data from an increasing number of various sources and methods.(…) In Geosciences, placing observations in their spatial context is very important. (…) A modular and scalable database system deployed on the organisational level of an institute-wide laboratory rather than a research project, may help overcome the aforementioned challenges. The proposed project seeks to develop an integrated database system for geoscientific research that integrates the data management in the course of the research process from fieldwork documentation to laboratory results. Moreover, collaboration between research groups of the Institute for Geography (mainly AG Bareth, AG Bogner, AG Mansfeldt, AG Schneider, AG Reimann) and participants of the Key Profile Area (KPA) (e.g. AG Dunai, AG Grunert, AG Melles and others) will be explored. The goals of database system development are to:

  • provide long-term storage of research data and metadata beyond the organisational and temporal limits of individual projects,
  • simplify fieldwork and laboratory documentation,
  • allow simple and comprehensive query of data records across different projects, spatial and temporal scales, using programming interfaces,
  • be modular and scalable and
  • fulfil the requirements of the DFG


KPA 007 (started)

Dr. Claudia Acquistapace - Meteorologie - Extreme Wetterphänomene

New ground-based dataset input for developing a new machine learning self-supervised classification approach to identify cloud regimes.

Cloud mesoscale organization is crucial in determining cloud response to climate change, especially in the tropical region. Self-supervised machine learning (MLSV) method applied to satellite data successfully classifies cloud regimes in the trades during the EUREC4A campaign (Chatterjee et al., 2023). However, it still does not exploit the information from different observing geometries, like ship-based profiling observations. Model studies show that the evaporation of precipitation can play a crucial role in cold pool development, altering cloud spatial patterns and organization. We suggest preparing precipitation's evaporation rate (ER) measured from ship-based observations (Acquistapace et al., 2021) as input for MLSV. We will calculate ER by applying the method described by Tridon et al., 2017. First, we will use the mean cloud ER to understand better cloud regimes obtained using only satellite data. Finally, we will test the feasibility of including such data as input for the MLSV algorithm, hopefully revealing a new potential extension of the MLSV method that could benefit various applications and diverse scientific goals in intelligent methods for earth sciences.


KPA 008 (starting in 2024)

Dr. Yannick Bussweiler - GeoMuseum

Digitalisierung der Lehrsammlung des GeoMuseums

Das GeoMuseum des Instituts für Geologie und Mineralogie der Universität zu Köln beheimatet eine große Sammlung an Gesteinen, Mineralen und Fossilien. Einige dieser Stücke sind im Museumsraum ausgestellt und für die Öffentlichkeit zugänglich. Die meisten Stücke befinden sich jedoch in den Lagerräumen des Museums. Darunter befindet sich auch eine umfangreiche Lehrsammlung aus sedimentären, magmatischen und metamorphen Gesteinen, welche in der Vergangenheit intensiv für die Lehre genutzt wurde. Unser Ziel ist es, die Aufmerksamkeit unserer Dozierenden am Institut (und evtl. darüber hinaus) auf die Lehrsammlung zu erhöhen, in dem wir diese digitalisieren. 

Zur Digitalisierung wird derzeit ein Photogrammetrie-Labor in den Räumlichkeiten des GeoMuseums eingerichtet (u.a. mit Geldern des Albertus-Magnus Lehrpreises 2023). Voraussichtlich kann im neuen Jahr mit der Aufnahme der Lehrsammlung (etwa 350 Stücke) begonnen werden. Hierzu sollen die Stücke zuerst gewogen, dann fotografiert (aus mehreren Perspektiven zur Erstellung eines 3D-Modells) und petrographisch beschrieben werden. Die Daten und Informationen werden in einer digitalen Datenbank eingetragen und schließlich mit allen Dozierenden des Instituts geteilt.





Masterarbeit "Graphbasiertes Clustering von Wolkenbildern"

Durch den Einfluss verschiedener Wolkentypen auf das Erdklima und stetig steigendes Datenvolumen ist eine automatisierte Klassifizierung von Satellitenbildern verschiedener Wolkentypen von wachsendem Interesse. Dadurch motiviert wurde in der interdisziplinären Masterarbeit (Informatik und Meteorologie) von Sebastian Zaun (Institut für Informatik, Lehrstuhl Prof. Dr. Sohler) eine neue Methode zum Clustering von Wolkenbildern entwickelt. Unsere Methode unterteilt die Eingabebilder in kleinere quadratische Ausschnitte, um das Auftreten verschiedener Muster in den unterschiedlichen Bildern zu vergleichen. Dabei werden die Eingabebilder sowie die Ausschnitte als gitterartige Graphen interpretiert. Um das Clustering der Bilder durchführen zu können, haben wir eine neues Abstandsmaß für diese Bilder definiert, welches durch die Kombination einer Approximation der Graph Edit Distanz und der Wasserstein Distanz definiert ist. Erstere wird dafür genutzt, den Abstand zwischen Bildausschnitten zu berechnen, während zweitere dafür verwendet wird, das Auftreten einzelner Bildausschnitte in unterschiedlichen Bildern zu vergleichen. Getestet haben wir die Methode auf einem Cloud Optical Depth Bilddatensatz über zentral Europa.



Masterarbeit zu "Visualization and Visual Analytics"

Die interdisziplinäre Masterarbeit (Informatik und Meteorologie) von Daniel Braun (Institut für Informatik, Arbeitsgruppe Visualisierung und Visual Analytics) stellt ein neuartiges Farbschema vor, das sich der Herausforderung der Visualisierung von Datenreihen mit großen Wertebereichen stellt und bei der die Skalentransformation nur begrenzte Unterstützung bietet. Wir konzentrieren uns auf meteorologische Daten, bei denen das Vorhandensein von großen Wertebereichen üblich ist. Wir wenden unseren Ansatz auf meteorologische Streudiagramme an, eines der in diesem Bereich am häufigsten verwendeten Diagramme. Unser Ansatz nutzt die numerische Darstellung von Mantisse und Exponent der Werte, um das Design neuartiger "verschachtelter" Farbschemata zu steuern, die in der Lage sind, Unterschiede zwischen Größenordnungen zu betonen.

Das ganze entsprechende Paper Color Coding of Large Value Ranges Applied to Meteorological Data gibt es hier (Arxiv) und die entwickelte in einer Python-Library implementierte Methode befindet sich hier (github).


Dagstuhl Seminar 

Im Schloss Dagstuhl findet das Seminar Computational Geometry of Earth System Analysis (23342) vom 20. August bis 25. August 2023 statt. Die Organisatoren sind Susanne Crewell (Universität Köln, DE), Anne Driemel (Universität Bonn, DE) und Jeff M. Phillips (University of Utah - Salt Lake City, US). This Dagstuhl Seminar will bring together computational geometers and meteorologists and will provide a forum to discuss the unique computational challenges that meteorologists are dealing with and how the geometry underlying the input data can be exploited to obtain efficient algorithms. Concrete problem areas that could greatly benefit from synergies between the two research areas include (1) data assimilation of weather-related measurements for numerical simulation, (2) tracking and clustering of moving atmospheric features, and (3) the planning and optimization of sensor placements.