nev is a web-based visual tool for querying and inspection of Nemo‘s reasoning traces.
Prototype: Run the Application
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Our tool nev is free and open source. GitHub repository with source code and Dockerfile: https://github.com/imldresden/nev
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We also provide a live version of Nemo and nev, accessible at: https://tools.iccl.inf.tu-dresden.de/nemo/
Video: Tool Walkthrough
Related Publications
@inproceedings{DGHIKMM2026,
author = {Raimund Dachselt and Lukas Gerlach and Philipp Hanisch and Alex Ivliev and Markus Kr\"{o}tzsch and Maximilian Marx and Juli\'{a}n M\'{e}ndez},
title = {Declarative Debugging for Datalog with Aggregation},
booktitle = {Proceedings of the Workshops of the EDBT/ICDT 2026 Joint Conference},
series = {CEUR Workshop Proceedings},
year = {2026},
month = {3},
location = {Tampere, Finland},
numpages = {8},
publisher = {CEUR-WS.org}
}List of additional material
@article{gerlach2024evonnemo,
author = {Lukas Gerlach and Alex Ivliev and Juli\'{a}n M\'{e}ndez and Simon Meusel and Raimund Dachselt and Markus Kr\"{o}tzsch},
title = {EvonNemo - A Symbiosis of Datalog Tracing and Proof Tree Visualization},
booktitle = {The Fifth Workshop on Explainable Logic-Based Knowledge Representation},
year = {2024},
month = {11},
location = {Hanoi, Vietnam}
}List of additional material
Related Student Theses

Interactive Visualization for Datalog Query Tracing
Tobias Wieland April 28th, 2025 until September 15th, 2025
Supervision: Julián Méndez, Raimund Dachselt
Acknowledgements
This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy: EXC-2068, 390729961 – Cluster of Excellence “Physics of Life” and EXC 2050/2, 390696704 – Cluster of Excellence “Centre for Tactile Internet” (CeTI) of TU Dresden, by DFG grant 389792660 as part of TRR 248 – CPEC (see https://cpec.science) and by the Federal Ministry of Research, Technology and Space (BMFTR, SCADS22B) and Saxon State Ministry for Science, Culture and Tourism (SMWK) by funding the competence center for Big Data and AI “ScaDS.AI Dresden/Leipzig”.

