Publications

Articles in public domain

Scientific articles

P. Baumann, On the analysis-readiness of spatio-temporal Earth data and suggestions for its enhancement, Environmental Modelling & Software, Volume 176, 2024, 106017, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2024.106017.
Nunez, Coronado-Zamora, et al., Footprints of worldwide adaptation in structured populations of D. melanogaster through the expanded DEST 2.0 genomic resource. BioRxiv preprint doi: https://doi.org/10.1101/2024.11.10.622744
Mohamed-Bachir Belaid, Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, Helge Spieker, Query-driven Qualitative Constraint Acquisition, Journal of Artificial Intelligence Research, vol 79, 2024. DOI: https://doi.org/10.1613/jair.1.14752
M. Kapun, S. Steindl, M. Ricci, M. Loehnertz, F. Strasser, R. Chen, L. Timaeus, N. Szucsich, E. Haring, Ecology and temporal dynamics of urban Drosophila species communities as potential indicators of biodiversity decline. https://doi.org/10.22541/au.175731863.36387636/v1.
I. Gottwald, S. Steindl, F. Strasser, M. Kiesel, H. Rainer, E. Haring, M Kapun. How to catch flies in the city (fast): Citizen Science on Drosophila ecology helps to raise awareness for biodiversity in urban environments. https://doi.org/10.1101/2025.10.10.681315
Kapun, M; Steindl, S, Genome-wide signals of adaptation in Drosophila to natural and anthropogenic factors in rural and urban environments in Europe. In prep.

Contributions in proceedings

P. Baumann, “On Openness in Service Stacks,” 2024 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), Victoria, Seychelles, 2024, pp. 1-7, doi: 10.1109/ACDSA59508.2024.10467764.
D. Mišev, M. Rodionychev and P. Baumann, “Performance of Null Handling in Array Databases,” 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 247-254, doi: 10.1109/BigData59044.2023.10386100.
S. Jetschny, K. Schleidt, FAIRICUBE: Enabling gridded data analysis for all, doi: 10.5281/zenodo.11487039.
Babak Ebrahimi, Mohamed-Bachir Belaid, Daniel Dean Moran and Stefan Jetschny, Estimating Residential Building Energy Demand at City Scale: Heuristic vs. Machine Learning. Submitted.
J. Sharma, S. Jetschny, M. Kapun, M.B. Belaid, Scalable Deep Learning for High-Fidelity Imputation of Large-Scale Genomic Fragments. Submitted.
J. Sharma, S. Jetschny, M. Kapun, M.B. Belaid, Deep Learning-Enhanced Gap Filling in Drosophila melanogaster Genomic Data. Submitted.

Posters

P. Baumann, D. Misev, AI and Datacubes: Towards a Happy Marriage. In Soille, P., Lumnitz, S. and Albani, S., Proceedings of the 2023 conference on Big Data from Space (BiDS’23) – From foresight to impact – 6-9 November 2023, Austrian Center, Vienna, Soille, P.(editor), Lumnitz, S.(editor) and Albani, S.(editor), Publications Office of the European Union, 2023, https://data.europa.eu/doi/10.2760/46796
H. Rainer, S. Ioni, Kryštof Chytrý, Use Case 5: Validation of Phytosociological Methods through Occurrence Cubes, doi: 10.5281/zenodo.16271250
M. Kapun, S. Steindl Use Case 3 Analysis of genetic drift in Drosophila melanogaster, doi: 10.5281/zenodo.16615053.
M. Ricci, M. Löhnertz, A. Peters, M. Cattaneo, Use Case 1: Invasive plant species in cities, Monitoring the spread of invasives with data cubes in urban areas, doi: 10.5281/zenodo.16570537
M. Vittek, R. Knapen, M. Raeissi, G. Hekkert, Use Case 2: Agriculture and Biodiversity Nexus, Quantifying the Impact of Agriculture Activities on Farmland Bird Diversity with Causal Modelling, 10.5281/zenodo.17244954