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guide/community-workflow-overview.md

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## Examples
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**See the [CODECHECK register](/register) for a full list of codechecks, including direct links to the reports and register issues with background information.**
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See the [CODECHECK register](/register) for a full list of codechecks, including direct links to the reports and register issues.
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You can check there for more examples from different communities.
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### Neuroscience 🧠
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- Life Sciences 🧬🌿🧠
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- [_ShinyLearner: A containerized benchmarking tool for machine-learning classification of tabular data_](https://doi.org/10.1093/gigascience/giaa026)
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#### [Piccolo, 2020](https://github.com/codecheckers/Piccolo-2020)
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CODECHECK Certificate 2020-001. <https://doi.org/10.5281/zenodo.3674056>
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- [_Report 9: impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. March 16, 2020._](https://doi.org/10.25561/77482)
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Codechecker: [@sje30](https://github.com/sje30)
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CODECHECK certificate 2020-010: <https://doi.org/10.5281/zenodo.3865491>
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- [_Driftage: a multi-agent system for concept drift detection and an application on electromyography_](https://doi.org/10.1093/gigascience/giab030)
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(Uses MyBinder)
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Report: [http://doi.org/10.5281/zenodo.3674056](http://doi.org/10.5281/zenodo.3674056)
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CODECHECK certificate 2020-024: <https://doi.org/10.5281/zenodo.4964880>
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- GIScience/Geography/Geoinformatics 🌏🌎🌍
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- [_Progress in the R ecosystem for representing and handling spatial data_](https://doi.org/10.1007/s10109-020-00336-0)
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Journal: GigaScience, see also [related blog post](http://gigasciencejournal.com/blog/codecheck-certificate/) reporting on this first CODECHECK for the journal.
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CODECHECK certificate 2020-017: <https://doi.org/10.5281/zenodo.4003848>
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- [_Geographically Weighted Regressions in educational planning_](https://www.iiep.unesco.org/en/publication/geographically-weighted-regressions-prioritizing-educational-planning-policies-and-interventions)
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(R and QGIS)
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#### [Hopfield, 1982](https://github.com/codecheckers/Hopfield-1982)
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CODECHECK certificate 2022-001: <https://doi.org/10.5281/zenodo.6040066>
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- [_Is it safe to be attractive? Disentangling the influence of streetscape features on the perceived safety and attractiveness of city streets_](https://doi.org/10.5194/agile-giss-4-8-2023)
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(web app, Jupyter notebook)
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A landmark paper from neuroscience, reproduced by [@sebwyh](https://github.com/sebwyh) with edits by [@nuest](https://github.com/nuest).
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CODECHECk certificate 2023-008: <https://doi.org/10.17605/OSF.IO/AQGXR>
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- [_Urban Sound Mapping for Wayfinding - A theoretical Approach and an empirical Study_](https://doi.org/10.5194/agile-giss-4-9-2023)
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(R and QGIS)
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Codechecker: [@nuest](https://github.com/nuest)
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CODECHECk certificate 2023-001: <https://doi.org/10.17605/OSF.IO/C7VX3>
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- [_Road Network Mapping from Multispectral Satellite Imagery: Leveraging Deep Learning and Spectral Bands_](https://doi.org/10.5194/agile-giss-5-6-2024)
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(Python with Conda, data subset)
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Report: [https://doi.org/10.5281/zenodo.3741797](https://doi.org/10.5281/zenodo.3741797)
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CODECHECk certificate 2024-013: <https://doi.org/10.17605/OSF.IO/TXGZV>
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- [_The Impact of Traffic Lights on Modal Split and Route Choice: A use-case in Vienna_](https://doi.org/10.5194/agile-giss-5-4-2024)
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(Python, with requirements.txt by codechecker)
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#### [Hancock, 1991](https://github.com/codecheckers/Reproduction-Hancock)
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CODECHECk certificate 2024-013: <https://doi.org/10.17605/OSF.IO/W42AD>
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- [_Developing a city-specific walkability index through a participatory approach_](https://doi.org/10.5194/agile-giss-5-2-2024)
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(mixed methods; QGIS and Python)
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A classical neuroscience paper.
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CODECHECk certificate 2024-013: <https://doi.org/10.17605/OSF.IO/CSB7R>
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- [_Knowledge-Based Identification of Urban Green Spaces: Allotments_](https://doi.org/10.5194/agile-giss-5-8-2024)
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(R, proprietary GIS)
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Codechecker: [@sje30](https://github.com/sje30) and [@nuest](https://github.com/nuest)
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CODECHECk certificate 2024-013: <https://doi.org/10.17605/OSF.IO/3NBJW>
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- Archaeology ⛏️🗿
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- [_The application of Local Indicators for Categorical Data (LICD) to explore spatial dependence in archaeological spaces_](https://doi.org/10.1016/j.jas.2020.105306)
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Report: [http://doi.org/10.5281/zenodo.3750741](http://doi.org/10.5281/zenodo.3750741)
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### GIScience/Geography/Geoinformatics 🌏🌎🌍
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#### [Brunsden & Comber, 2020](https://github.com/codecheckers/OpeningPractice)
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Paper on reproducibility in spatial data science.
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Codechecker: [@nuest](https://github.com/nuest)
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Report: [https://doi.org/10.5281/zenodo.3873153](https://doi.org/10.5281/zenodo.3873153)
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### Archaeology ⛏️
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Paper on spatial dependence in archaeological spaces.
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Codechecker: [@nuest](https://github.com/nuest)
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Report: [https://doi.org/10.5281/zenodo.4279275](https://doi.org/10.5281/zenodo.4279275)
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### _Your scientific dispipline here..._
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**[Get involved!](/get-involved)**
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CODECHECK Certificate 2020-025. <https://doi.org/10.5281/zenodo.4279275>
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- _Your scientific dispipline here..._
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- **[Get involved!](/get-involved)**

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