Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
ObsPy: A Python Toolbox for Seismology
20101.2k citationsMoritz Beyreuther, R. Barsch et al.Seismological Research Lettersprofile →
ObsPy: a bridge for seismology into the scientific Python ecosystem
2015611 citationsLion Krischer, Tobias Megies et al.Ghent University Academic Bibliography (Ghent University)profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of R. Barsch's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by R. Barsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites R. Barsch more than expected).
This network shows the impact of papers produced by R. Barsch. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by R. Barsch. The network helps show where R. Barsch may publish in the future.
Co-authorship network of co-authors of R. Barsch
This figure shows the co-authorship network connecting the top 25 collaborators of R. Barsch.
A scholar is included among the top collaborators of R. Barsch based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with R. Barsch. R. Barsch is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
12 of 12 papers shown
1.
Krischer, Lion, Tobias Megies, Elliott Sales de Andrade, R. Barsch, & J. MacCarthy. (2017). ObsPy: A Python Toolbox for Seismology. EGU General Assembly Conference Abstracts. 17089.
2.
Krischer, Lion, Tobias Megies, R. Barsch, et al.. (2017). ObsPy -- A Python Toolbox for Seismology -- and Applications. 2017.1 indexed citations
3.
Krischer, Lion, Tobias Megies, R. Barsch, et al.. (2015). ObsPy: a bridge for seismology into the scientific Python ecosystem. Ghent University Academic Bibliography (Ghent University). 8(1). 14003–14003.611 indexed citations breakdown →
Megies, Tobias, R. Barsch, Moritz Beyreuther, Lion Krischer, & Joachim Wassermann. (2011). ObsPy: A Python Toolbox for Seismology/Seismological Observatories. AGUFM. 2011.1 indexed citations
Beyreuther, Moritz, R. Barsch, Lion Krischer, et al.. (2010). ObsPy: A Python Toolbox for Seismology. Seismological Research Letters. 81(3). 530–533.1222 indexed citations breakdown →
8.
Beyreuther, Moritz, R. Barsch, Lion Krischer, et al.. (2010). ObsPy: A Python toolbox for Seismology, a Data Center Perspective. EGU General Assembly Conference Abstracts. 4576.1 indexed citations
9.
Wassermann, Joachim, Lion Krischer, Tobias Megies, R. Barsch, & Moritz Beyreuther. (2010). ObsPy: A Python Toolbox for Seismology. AGUFM. 2013.4 indexed citations
Igel, Heiner, et al.. (2005). The EU SPICE Project: a digital library with codes and training material in computational seismology. AGU Fall Meeting Abstracts. 2005.3 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.