2024-03-28T17:58:35Z
https://zenodo.org/oai2d
oai:zenodo.org:5078256
2022-02-21T08:45:05Z
user-calc
software
user-research-compendium
user-digling
user-eu
Johann-Mattis List
Robert Forkel
Tiago Tresoldi
Simon J Greenhill
Mary Walworth
2021-07-07
<p>This is a bugfix release of our LingPy tutorial, accompanying the paper "Sequence Comparison in Computational Historical Linguistics" (List et al. 2018, Journal of Language Evolution, DOI: <a href="https://doi.org/10.1093/jole/lzy006">https://doi.org/10.1093/jole/lzy006</a>).</p>
https://doi.org/10.5281/zenodo.5078256
oai:zenodo.org:5078256
Zenodo
https://github.com/lingpy/lingpy-tutorial/tree/v1.1
https://zenodo.org/communities/research-compendium
https://zenodo.org/communities/calc
https://zenodo.org/communities/eu
https://zenodo.org/communities/digling
https://doi.org/10.5281/zenodo.1252230
info:eu-repo/semantics/openAccess
Other (Open)
lingpy/lingpy-tutorial: LingPy Tutorial
info:eu-repo/semantics/other
oai:zenodo.org:1252231
2022-02-21T08:45:06Z
user-calc
software
user-research-compendium
user-digling
user-eu
Johann-Mattis List
Mary Walworth
Simon J Greenhill
Tiago Tresoldi
Robert Forkel
2018-05-24
<p>This is the first release of our LingPy tutorial, accompanying the paper "Sequence Comparison in Computational Historical Linguistics" (List et al. 2018, Journal of Language Evolution, DOI: http://dx.doi.org/10.1093/jole/lzy006).</p>
https://doi.org/10.5281/zenodo.1252231
oai:zenodo.org:1252231
eng
Zenodo
https://www.dx.doi.org/10.1093/jole/lzy006
https://zenodo.org/communities/research-compendium
https://zenodo.org/communities/calc
https://zenodo.org/communities/eu
https://zenodo.org/communities/digling
https://doi.org/10.5281/zenodo.1252230
info:eu-repo/semantics/openAccess
GNU General Public License v2.0 only
https://www.gnu.org/licenses/old-licenses/gpl-2.0-standalone.html
Journal of Language Evolution, (2018-05-24)
historical linguistics
sequence comparison
computational linguistics
cognate detection
LingPy Tutorial. Version 1.0
info:eu-repo/semantics/other
oai:zenodo.org:3381641
2021-06-08T18:22:44Z
software
user-research-compendium
Ross Gayler
2019-08-29
<p>This is the R notebook and R project that generates the <a href="http://doi.org/10.5281/zenodo.3381658">presentation</a>, as given at Credit Scoring & Credit Control XVI, Edinburgh, UK, on 2019-08-30.</p>
https://doi.org/10.5281/zenodo.3381641
oai:zenodo.org:3381641
Zenodo
https://doi.org/10.5281/zenodo.3381658
https://github.com/rgayler/scorecal_CSCC_2019/tree/v1.0
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.3381640
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
CSCC XVI, Credit Scoring and Credit Control Conference XVI, Edinburgh, UK, 28-30 August 2019
rgayler/scorecal_CSCC_2019 v1.0
info:eu-repo/semantics/other
oai:zenodo.org:4633893
2021-03-25T00:27:30Z
software
user-research-compendium
Nüst, Daniel
Ostermann, Frank
Granell, Carlos
Hofer, Barbara
Konkol, Markus
2021-03-24
<p>Data and code for research article <em>Reproducible Research and GIScience: an evaluation using GIScience conference papers</em>.</p>
<p>This record is a preservation of the collaborative project at <a href="https://github.com/nuest/reproducible-research-at-giscience/">https://github.com/nuest/reproducible-research-at-giscience/</a>. A preprint is published on EarthArXiv at <a href="https://doi.org/10.31223/X5ZK5V">https://doi.org/10.31223/X5ZK5V</a>.</p>
The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.
All contained code is licensed under the Apache License 2.0.
The data used is licensed under a Open Data Commons Attribution License.
https://doi.org/10.5281/zenodo.4633893
oai:zenodo.org:4633893
eng
Zenodo
https://doi.org/10.31223/X5ZK5V
https://github.com/nuest/reproducible-research-at-giscience/tree/submission.v1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.4032875
info:eu-repo/semantics/openAccess
Other (Open)
reproducible research
GIScience
open science
Reproducibility package for "Reproducible Research and GIScience: an evaluation using GIScience conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:2591710
2020-01-24T19:25:59Z
openaire_data
user-research-compendium
Schratz, Patrick
Muenchow, Jannes
Iturritxa, Eugenia
Richter, Jakob
Brenning, Alexander
2019-03-04
<p>This repository will contain the research compendium of our work on comparing algorithms across different resampling settings.</p>
https://doi.org/10.5281/zenodo.2591710
oai:zenodo.org:2591710
Zenodo
https://arxiv.org/abs/1803.11266
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.2582969
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
machine-learning
ecological modeling
hyperparameter tuning
pathogen
benchmarking
Analyzing the importance of spatial autocorrelation in hyperparameter tuning and performance estimation of machine-learning algorithms for spatial data.
info:eu-repo/semantics/other
oai:zenodo.org:2575062
2020-01-24T19:26:10Z
openaire_data
user-research-compendium
Granell, Carlos
Hofer, Barbara
Konkol, Markus
Ostermann, Frank O.
Sileryte, Rusne
Certutti, Valentina
Nüst, Daniel
2018-04-23
<p>Data and code for analysis and plots used in the manuscript "Reproducible research and GIScience: an evaluation using AGILE conference papers": <a href="https://doi.org/10.7287/peerj.preprints.26561v1">https://doi.org/10.7287/peerj.preprints.26561v1</a></p>
<p>The deposited archived includes a <a href="https://en.wikipedia.org/wiki/Docker_(software)">Dockerfile</a> and an <a href="http://rmarkdown.rstudio.com/">R Markdown</a> document suitable for use with <a href="http://mybinder.org/">Binder</a>: <a href="https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/6">https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/6</a></p>
<p>The version tag of this repository matches the <a href="https://git-scm.com/book/en/v2/Git-Basics-Tagging">git tag</a> on the code repository at <a href="https://github.com/nuest/reproducible-research-and-giscience">https://github.com/nuest/reproducible-research-and-giscience</a>, except version <code>6-fixed</code> which matches the tag <code>6</code>.</p>
<p> </p>
The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.
All contained code is licensed under the Apache License 2.0.
The data used is licensed under a Open Data Commons Attribution License.
https://doi.org/10.5281/zenodo.2575062
oai:zenodo.org:2575062
eng
Zenodo
https://doi.org/10.7287/peerj.preprints.26561v1
https://doi.org/10.7717/peerj.5072
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1227260
info:eu-repo/semantics/openAccess
Other (Open)
GIScience
Reproducibility Package for "Reproducible research and GIScience: an evaluation using AGILE conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:1244292
2020-01-24T19:25:42Z
openaire_data
user-research-compendium
Granell, Carlos
Hofer, Barbara
Konkol, Markus
Ostermann, Frank O.
Sileryte, Rusne
Certutti, Valentina
Nüst, Daniel
2018-04-23
<p>Data and code for analysis and plots used in the manuscript "Reproducible research and GIScience: an evaluation using AGILE conference papers": <a href="https://doi.org/10.7287/peerj.preprints.26561v1">https://doi.org/10.7287/peerj.preprints.26561v1</a></p>
<p>The deposited archived includes a <a href="https://en.wikipedia.org/wiki/Docker_(software)">Dockerfile</a> and an <a href="http://rmarkdown.rstudio.com/">R Markdown</a> document suitable for use with <a href="http://mybinder.org/">Binder</a>: <a href="https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2">https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2</a></p>
<p>The version tag of this repository matches the <a href="https://git-scm.com/book/en/v2/Git-Basics-Tagging">git tag</a> on the code repository at <a href="https://github.com/nuest/reproducible-research-and-giscience">https://github.com/nuest/reproducible-research-and-giscience</a>.</p>
https://doi.org/10.5281/zenodo.1244292
oai:zenodo.org:1244292
eng
Zenodo
https://doi.org/10.7287/peerj.preprints.26561v1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1227260
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
GIScience
Reproducibility Package for "Reproducible research and GIScience: an evaluation using AGILE conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:11837
2020-01-25T07:25:47Z
user-archaeology
software
user-research-compendium
Ben Marwick
2014-09-23
<p>The files in this repository are a part of a supplement to:</p>
<p>Marwick, B., Hiscock, P., Sullivan, M., & Hughes, P. 2017 Landform boundary effects on Holocene forager landscape use in arid South Australia. Journal of Archaeological Science: Reports. <a href="http://doi.org/10.1016/j.jasrep.2017.07.004">http://doi.org/10.1016/j.jasrep.2017.07.004</a></p>
https://doi.org/10.5281/zenodo.11837
oai:zenodo.org:11837
Zenodo
https://github.com/benmarwick/olympic-dam-mobile-gis/tree/v0.2
https://doi.org/10.1016/j.jasrep.2017.07.004
https://zenodo.org/communities/research-compendium
https://zenodo.org/communities/archaeology
https://doi.org/10.5281/zenodo.592365
info:eu-repo/semantics/openAccess
Other (Open)
olympic-dam-mobile-gis
info:eu-repo/semantics/other
oai:zenodo.org:159527
2020-01-25T07:22:51Z
user-kwb
software
user-research-compendium
user-eu
Rustler, Michael
2016-10-07
<p>The code and data allows you to reproduce the quantitative microbiological risk assessment (QMRA) for the wastewater treatment plant Old Ford, which was performed in the EU project DEMOWARE (<a href="http://demoware.eu/en">http://demoware.eu/en</a>) and is documentated in the <a href="http://demoware.eu/en/results/deliverables/deliverable-d3-2-show-case-of-the-environmental-benefits-and-risk-assessment-of-reuse-schemes.pdf#page=137">DEMOWARE Deliverable 3.2 (p. 119-130).</a></p>
<p> </p>
<p><strong>The following licences apply:</strong></p>
<p>Code: <a href="https://choosealicense.com/licenses/mit/">MIT License</a></p>
<p>Data: <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International (CC BY 4.0) </a></p>
<p>Text: <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International (CC BY 4.0) </a></p>
<p> </p>
<p><strong>How to reproduce the risk calculation?</strong></p>
<p> </p>
<p><strong>Requirements</strong></p>
<p>For performing the risk calculation you need to make sure to have R (>= 3.3.1, www.r-project.org) installed on your computer and at least 16GB of RAM (required to perform the risk calculation for the “toilet flushing scenario”). An integrated development environment (IDE) like RStudio is helpful but is not required. However, the workflow described below assumes that you are using RStudio.</p>
<p><strong>Workflow</strong></p>
<p>To perform the risk calculation for the Old Ford case study you need to:</p>
<ol>
<li>
<p>Open the R script <strong><em>run_risk_calculation.R</em></strong> in RStudio,</p>
</li>
<li>
<p>Run the whole script by clicking on the <strong>Source</strong> button in RStudío</p>
</li>
<li>
<p>Wait until risk calculation & plotting is completed for all 3 scenarios</p>
</li>
</ol>
<p><strong>Important note:</strong></p>
<p>In case the R script crashes because of insufficient RAM memory for the 3rd scenario you are still able to reproduce the results and plots for the first two. If this occurs just close RStudio, reopen the R script <strong><em>run_risk_calculation.R</em></strong> and just perform the lines 32 until 132. That’s all!</p>
<p> </p>
<p><strong><em>Happy reproducing!</em></strong></p>
For performing the quantitative microbial risk assessment the R package kwb.qmra, v.0.1.1 (https://doi.org/10.5281/zenodo.154111) is used.
Both, documents and data in this repository are licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. All contained code is licensed under the MIT Licence (MIT).
https://doi.org/10.5281/zenodo.159527
oai:zenodo.org:159527
eng
Zenodo
https://zenodo.org/communities/research-compendium
https://zenodo.org/communities/kwb
https://zenodo.org/communities/eu
https://doi.org/
info:eu-repo/semantics/openAccess
Other (Open)
quantitative microbiological risk assessment
R package
R script
Research Compendium
Quantitative microbiological risk assessment for different wastewater reuse options in Old Ford (v.1.0)
info:eu-repo/semantics/other
oai:zenodo.org:1135140
2019-04-09T13:25:31Z
user-research-compendium
Nüst, Daniel
2018-01-08
<p><em>A reproducible analysis of environmental data - from hardware to interactive map!</em></p>
<p>This repository contains the workspace, data, and code for analysing particulates measured by senseBoxes at New Year's Eve 2017/18 in Münster, Germany. It is a showcase for the transparency and potential of Open Hardware, Open Data, Free and Open Source Software, and Open Science.</p>
<p>The analysis is written in R Markdown and can be easily explored thanks to Jupyter Notebook+RStudio embedded in a Docker image - see file README.md for full instructions.</p>
https://doi.org/10.5281/zenodo.1135140
oai:zenodo.org:1135140
eng
Zenodo
https://github.com/nuest/sensebox-binder
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1135139
info:eu-repo/semantics/openAccess
Other (Open)
reproducible research
rstats
reproducibility
particulates
air quality
open science
Docker
BinderHub
Open environmental data analysis with senseBox, openSenseMap, Jupyter Notebook, RStudio, and BinderHub
info:eu-repo/semantics/other
oai:zenodo.org:13187
2020-01-25T07:21:04Z
software
user-research-compendium
Marwick, Ben
2014-12-10
<p>This repository contains code and data used to accompany my open review of Tong et al. "Vlog to Death: Project Eliseg’s Video-Blogging", published in <em>Internet Archaeology </em>as:</p>
<p>Marwick, B. (2015) Peer Comment: Films, digs and death: a review of the Project Eliseg videos, Internet Archaeology 39. <a href="http://dx.doi.org/10.11141/ia.39.3.com3">http://dx.doi.org/10.11141/ia.39.3.com3</a></p>
https://doi.org/10.5281/zenodo.13187
oai:zenodo.org:13187
Zenodo
https://github.com/benmarwick/vlog_to_death_review
https://zenodo.org/communities/research-compendium
https://doi.org/
info:eu-repo/semantics/openAccess
MIT License
https://opensource.org/licenses/MIT
Internet Archaeology, (2014-12-10)
Supplementary Materials for an Open Review for Internet Archaeology
info:eu-repo/semantics/other
oai:zenodo.org:3402938
2021-06-08T18:22:44Z
software
user-research-compendium
Ross Gayler
2019-09-09
<p>This is the R notebook and R project that generates the <a href="http://doi.org/10.5281/zenodo.3381658">presentation</a>, as given at Credit Scoring & Credit Control XVI, Edinburgh, UK, on 2019-08-30.</p>
<p>A docker image has been generated from this release of the project. It can be executed in Rstudio running on a free cloud instance provided by <a href="http://mybinder.org">mybinder.org</a>. All the user interaction is via a web browser, so that the user can experiment with the code without needing to install any software locally.</p>
<p>The project notebook can be executed by following all the instructions below or opening the "launch binder" link in a new browser tab then following steps 2 and 3 of the instructions.</p>
<p><a href="http://mybinder.org/v2/zenodo/10.5281/zenodo.3402938?urlpath=rstudio/"><strong>[LAUNCH BINDER]</strong></a></p>
<p>INSTRUCTIONS</p>
<ol>
<li>Open <a href="https://mybinder.org/v2/zenodo/10.5281/zenodo.3402938?urlpath=rstudio/">https://mybinder.org/v2/zenodo/10.5281/zenodo.3402938?urlpath=rstudio/</a> in a web browser (or click the "launch binder" link instead).</li>
<li>Once the Rstudio instance is running open the file scorecal_CSCC_2019.Rmd by clicking on the filename in the Files tab of the bottom-right pane.</li>
<li>Click the Knit button at the top of the scorecal_CSCC_2019.Rmd tab of code editor (top-left) pane. This will execute the notebook and generate the presentation slides.</li>
</ol>
https://doi.org/10.5281/zenodo.3402938
oai:zenodo.org:3402938
Zenodo
https://doi.org/10.5281/zenodo.3381658
https://doi.org/10.5281/zenodo.3381658
https://doi.org/10.5281/zenodo.3381658
https://github.com/rgayler/scorecal_CSCC_2019/tree/v1.2
https://mybinder.org/v2/zenodo/10.5281/zenodo.3402938?urlpath=rstudio/
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.3381640
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
CSCC XVI, Credit Scoring & Credit Control Conference XVI, Edinburgh, UK, 28-30 August 2019
rgayler/scorecal_CSCC_2019: v1.2 (with live execution of the notebook)
info:eu-repo/semantics/other
oai:zenodo.org:4049787
2021-03-24T18:22:21Z
user-research-compendium
Nüst, Daniel
Ostermann, Frank
Granell, Carlos
Hofer, Barbara
Konkol, Markus
2020-09-25
<p>Data and code for research article <em>Reproducible Research and GIScience: an evaluation using GIScience conference papers</em>.</p>
<p>This record is a preservation of the collaborative project at <a href="https://github.com/nuest/reproducible-research-at-giscience/">https://github.com/nuest/reproducible-research-at-giscience/</a>. A preprint is publised on EarthArXiv at <a href="https://doi.org/10.31223/X5ZK5V">https://doi.org/10.31223/X5ZK5V</a>.</p>
The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.
All contained code is licensed under the Apache License 2.0.
The data used is licensed under a Open Data Commons Attribution License.
https://doi.org/10.5281/zenodo.4049787
oai:zenodo.org:4049787
eng
Zenodo
https://github.com/nuest/reproducible-research-at-giscience/tree/preprint.v1
https://doi.org/10.31223/X5ZK5V
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.4032875
info:eu-repo/semantics/openAccess
Other (Open)
reproducible research
GIScience
open science
Reproducibility package for "Reproducible Research and GIScience: an evaluation using GIScience conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:168370
2022-08-25T14:15:54Z
user-gis
user-mdpi
user-remote-sensing
software
user-research-compendium
Nüst, Daniel
Knoth, Christian
2017-03-18
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p>Data and software to reproduce the scientific article Knoth, C., Nüst, D., 2017. Reproducibility and Practical Adoption of GEOBIA with Open-Source Software in Docker Containers. Remote Sensing 9, 290. doi:10.3390/rs9030290</p>
<p><strong>See file README.md for instructions.</strong></p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
<p> </p>
https://doi.org/10.5281/zenodo.168370
oai:zenodo.org:168370
Zenodo
https://doi.org/10.3390/rs9030290
https://zenodo.org/communities/research-compendium
https://zenodo.org/communities/mdpi
https://zenodo.org/communities/remote-sensing
https://zenodo.org/communities/gis
https://doi.org/
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Remote Sensing, 9(3), 290, (2017-03-18)
GEOBIA 2016, 6th Geographic Object-Based Image Analysis Conference, Enschede, The Netherlands, 14-16 September 2016
reproducibility
reproducible research
OBIA
GEOBIA
Docker
QGIS
InterIMAGE
conflict damage assessment
Reproducibility package for: Reproducibility and Practical Adoption of GEOBIA with Open-Source Software in Docker Containers
info:eu-repo/semantics/other
oai:zenodo.org:2633102
2020-01-24T19:25:59Z
openaire_data
user-research-compendium
Schratz, Patrick
Muenchow, Jannes
Iturritxa, Eugenia
Richter, Jakob
Brenning, Alexander
2019-04-08
<p>This is a research compendium (RC) for the publication "Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data".</p>
<p>The code (including figures, appendices and the manuscript) is packed in <strong>pathogen-modeling-3.zip </strong>or can be found directly in the <a href="https://github.com/pat-s/pathogen-modeling">Github repository</a>.</p>
<ul>
<li><strong>Publication figures</strong>: analysis/paper/submission/3/latex-source-files/</li>
<li><strong>Appendices</strong>: analysis/paper/submission/3/</li>
</ul>
<p>This RC represents a static snapshot at the time of submission. The Github repository will receive changes after the publication was published.</p>
<p><strong>Data sources</strong></p>
<ul>
<li>Atlas Climatico: <a href="http://opengis.uab.es/wms/iberia/index.htm">http://opengis.uab.es/wms/iberia/index.htm</a></li>
<li>DEM: ftp://ftp.geo.euskadi.eus/lidar/MDE_LIDAR_2016_ETRS89/</li>
<li>Lithology: <a href="http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home">http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home</a></li>
<li>pH: <a href="https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0">https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0</a></li>
<li>soil: <a href="https://www.isric.org/explore/soilgrids">https://www.isric.org/explore/soilgrids</a></li>
</ul>
<p><strong>Licenses</strong></p>
<p>All files are shared via the given license with the exception of "soil.tif" which is shared via the <strong>ODbL </strong>license<strong>.</strong></p>
https://doi.org/10.5281/zenodo.2633102
oai:zenodo.org:2633102
Zenodo
https://arxiv.org/abs/1803.11266
https://doi.org/10.1016/j.ecolmodel.2019.06.002
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.2582969
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Ecological Modelling, 406, 109-120, (2019-04-08)
spatial modeling
machine-learning
spatial autocorrelation
hyperparameter tuning
spatial cross-validation
Hyperparameter tuning and performance assessment of statistical and machine-learning models using spatial data.
info:eu-repo/semantics/other
oai:zenodo.org:1248839
2020-01-24T19:25:41Z
openaire_data
user-research-compendium
Granell, Carlos
Hofer, Barbara
Konkol, Markus
Ostermann, Frank O.
Sileryte, Rusne
Certutti, Valentina
Nüst, Daniel
2018-04-23
<p>Data and code for analysis and plots used in the manuscript "Reproducible research and GIScience: an evaluation using AGILE conference papers": <a href="https://doi.org/10.7287/peerj.preprints.26561v1">https://doi.org/10.7287/peerj.preprints.26561v1</a></p>
<p>The deposited archived includes a <a href="https://en.wikipedia.org/wiki/Docker_(software)">Dockerfile</a> and an <a href="http://rmarkdown.rstudio.com/">R Markdown</a> document suitable for use with <a href="http://mybinder.org/">Binder</a>: <a href="https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2">https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2</a></p>
<p>The version tag of this repository matches the <a href="https://git-scm.com/book/en/v2/Git-Basics-Tagging">git tag</a> on the code repository at <a href="https://github.com/nuest/reproducible-research-and-giscience">https://github.com/nuest/reproducible-research-and-giscience</a>.</p>
The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.
All contained code is licensed under the Apache License 2.0.
The data used is licensed under a Open Data Commons Attribution License.
https://doi.org/10.5281/zenodo.1248839
oai:zenodo.org:1248839
eng
Zenodo
https://doi.org/10.7287/peerj.preprints.26561v1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1227260
info:eu-repo/semantics/openAccess
Other (Open)
GIScience
Reproducibility Package for "Reproducible research and GIScience: an evaluation using AGILE conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:1227261
2020-01-24T19:26:16Z
openaire_data
user-research-compendium
Granell, Carlos
Hofer, Barbara
Konkol, Markus
Ostermann, Frank O.
Sileryte, Rusne
Certutti, Valentina
Nüst, Daniel
2018-04-23
<p>Data and code for analysis and plots used in the manuscript "Reproducible research and GIScience: an evaluation using AGILE conference papers": <a href="https://doi.org/10.7287/peerj.preprints.26561v1">https://doi.org/10.7287/peerj.preprints.26561v1</a></p>
<p>The deposited archived includes a <a href="https://en.wikipedia.org/wiki/Docker_(software)">Dockerfile</a> and an <a href="http://rmarkdown.rstudio.com/">R Markdown</a> document suitable for use with <a href="http://mybinder.org/">Binder</a>: <a href="https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/1">https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/1</a></p>
https://doi.org/10.5281/zenodo.1227261
oai:zenodo.org:1227261
eng
Zenodo
https://doi.org/10.7287/peerj.preprints.26561v1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1227260
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
GIScience
Reproducibility Package for "Reproducible research and GIScience: an evaluation using AGILE conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:1325107
2021-02-10T16:03:41Z
user-research-compendium
Rodriguez-Sanchez, Francisco
Luque-Oliva, Virginia
Jurado, Vicente
2018-08-01
<p>Research compendium (data, code and manuscript) for the following publication:</p>
<p>Rodríguez-Sánchez F, Luque-Oliva V & Jurado V. (2018) Impactos de la herbivoría por ungulados en las comunidades de plantas leñosas del Parque Natural Los Alcornocales. <em>Almoraima (</em>ISSN 1133-5319), 49: 251-263. https://doi.org/10.5281/zenodo.4529818.</p>
<p>Compendium URL: https://doi.org/10.5281/zenodo.1325107</p>
<p>Data license: CC-BY-4.0 (https://creativecommons.org/licenses/by/4.0/)</p>
<p>Text license: CC-BY-4.0 (https://creativecommons.org/licenses/by/4.0/)</p>
<p>Code license: MIT</p>
<p> </p>
https://doi.org/10.5281/zenodo.1325107
oai:zenodo.org:1325107
spa
Zenodo
https://github.com/Pakillo/exclosures-Almoraima/tree/1.0.0
https://doi.org/10.5281/zenodo.4529818
https://doi.org/10.5281/zenodo.4529818
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1325106
info:eu-repo/semantics/openAccess
MIT License
https://opensource.org/licenses/MIT
research compendium
ecology
R
R package
Rmarkdown
Research compendium for "Impactos de la herbivoría por ungulados en las comunidades de plantas leñosas del Parque Natural Los Alcornocales"
info:eu-repo/semantics/article
oai:zenodo.org:11833
2020-01-25T07:25:26Z
user-archaeology
software
user-research-compendium
Ben Marwick
2014-09-22
No description provided.
https://doi.org/10.5281/zenodo.11833
oai:zenodo.org:11833
Zenodo
https://github.com/benmarwick/olympic-dam-mobile-gis/tree/v0.1
https://zenodo.org/communities/research-compendium
https://zenodo.org/communities/archaeology
https://doi.org/10.5281/zenodo.592365
info:eu-repo/semantics/openAccess
Other (Open)
olympic-dam-mobile-gis v0.1
info:eu-repo/semantics/other
oai:zenodo.org:3381648
2021-06-08T18:22:44Z
software
user-research-compendium
Ross Gayler
2019-08-29
<p>This R notebook and R project that generates the <a href="http://doi.org/10.5281/zenodo.3381658">presentation</a>, as given at Credit Scoring & Credit Control XVI, Edinburgh, UK, on 2019-08-30.</p>
https://doi.org/10.5281/zenodo.3381648
oai:zenodo.org:3381648
Zenodo
https://doi.org/10.5281/zenodo.3381658
https://github.com/rgayler/scorecal_CSCC_2019/tree/v1.1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.3381640
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
CSCC XVI, Credit Scoring and Credit Control Conference XVI, Edinburgh, UK, 28-30 August 2019
rgayler/scorecal_CSCC_2019: v1.1 with corrected Zenodo DOI
info:eu-repo/semantics/other
oai:zenodo.org:1139929
2019-04-09T13:25:31Z
user-research-compendium
Nüst, Daniel
2018-01-08
<p><em>A reproducible analysis of environmental data - from hardware to interactive map!</em></p>
<p>This repository contains the workspace, data, and code for analysing particulates measured by senseBoxes at New Year's Eve 2017/18 in Münster, Germany. It is a showcase for the transparency and potential of Open Hardware, Open Data, Free and Open Source Software, and Open Science.</p>
<p>The analysis is written in R Markdown and can be easily explored thanks to Jupyter Notebook+RStudio embedded in a Docker image - see file README.md for full instructions.</p>
Data license: Public Domain Dedication and License 1.0; Contributed code license: Apache License 2.0, see respective used software licenses for included libraries and tools; Text and documentation license: Creative Commons Attribution 4.0 International (CC BY 4.0)
https://doi.org/10.5281/zenodo.1139929
oai:zenodo.org:1139929
eng
Zenodo
https://github.com/nuest/sensebox-binder
https://doi.org/10.5281/zenodo.1217911
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1135139
info:eu-repo/semantics/openAccess
Other (Attribution)
reproducible research
rstats
reproducibility
particulates
air quality
open science
Docker
BinderHub
Open environmental data analysis with senseBox, openSenseMap, Jupyter Notebook, RStudio, and BinderHub
info:eu-repo/semantics/other
oai:zenodo.org:4051231
2020-09-26T12:49:25Z
user-research-compendium
Nüst, Daniel
Graupner, Anika
2020-06-25
<p>Workflow code, computing environment, and visualisation app for preprint <strong>"Serverless GEO Labels for the Semantic Sensor Web"</strong>.</p>
<p>Sources: <a href="https://gitlab.com/nuest/geolabel-ssno-paper">https://gitlab.com/nuest/geolabel-ssno-paper</a></p>
<p><strong>Article: <a href="https://doi.org/10.4230/LIPIcs.GIScience.2021.I.4">https://doi.org/10.4230/LIPIcs.GIScience.2021.I.4</a></strong></p>
https://doi.org/10.5281/zenodo.4051231
oai:zenodo.org:4051231
eng
Zenodo
https://doi.org/10.20944/preprints202002.0326.v2
https://gitlab.com/nuest/geolabel-ssno-paper
https://doi.org/10.4230/LIPIcs.GIScience.2021.I.4
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.3908398
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
GEO label
SSNO
Semantic Web
serverless computing
Serverless GEO Labels for the Semantic Sensor Web
info:eu-repo/semantics/other
oai:zenodo.org:3908399
2020-09-26T12:49:23Z
user-research-compendium
Nüst, Daniel
Graupner, Anika
2020-06-25
<p>Workflow code, computing environment, and visualisation app for preprint "Serverless GEO Labels for the Semantic Sensor Web".</p>
<p>Sources: <a href="https://gitlab.com/nuest/geolabel-ssno-paper">https://gitlab.com/nuest/geolabel-ssno-paper</a></p>
<p>Preprint: <a href="https://doi.org/10.20944/preprints202002.0326.v1">https://doi.org/10.20944/preprints202002.0326.v1</a></p>
https://doi.org/10.5281/zenodo.3908399
oai:zenodo.org:3908399
eng
Zenodo
https://doi.org/10.20944/preprints202002.0326.v2
https://gitlab.com/nuest/geolabel-ssno-paper
https://doi.org/10.4230/LIPIcs.GIScience.2021.I.4
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.3908398
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
GEO label
SSNO
Semantic Web
serverless computing
Serverless GEO Labels for the Semantic Sensor Web
info:eu-repo/semantics/other
oai:zenodo.org:4032876
2021-03-24T18:22:21Z
user-research-compendium
Nüst, Daniel
Ostermann, Frank
Granell, Carlos
Hofer, Barbara
Konkol, Markus
2020-09-16
<p>Data and code for research article <em>Reproducible Research and GIScience: an evaluation using GIScience conference papers</em>.</p>
<p>This record is a preservation of the collaborative project at <a href="https://github.com/nuest/reproducible-research-at-giscience/">https://github.com/nuest/reproducible-research-at-giscience/</a>.</p>
The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.
All contained code is licensed under the Apache License 2.0.
The data used is licensed under a Open Data Commons Attribution License.
https://doi.org/10.5281/zenodo.4032876
oai:zenodo.org:4032876
eng
Zenodo
https://github.com/nuest/reproducible-research-at-giscience/tree/v0.1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.4032875
info:eu-repo/semantics/openAccess
Other (Open)
reproducible research
GIScience
open science
Reproducibility package for "Reproducible Research and GIScience: an evaluation using GIScience conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:1219780
2020-01-25T19:21:34Z
software
user-research-compendium
Carl Boettiger
2018-04-17
<p>Research compendium containing code for reproducing all figures and analyses included in this manuscript.</p>
https://doi.org/10.5281/zenodo.1219780
oai:zenodo.org:1219780
Zenodo
https://github.com/cboettig/noise-phenomena/tree/revision-2
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1219779
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cboettig/noise-phenomena: Supplement to: "From noise to knowledge: how randomness generates novel phenomena and reveals information"
info:eu-repo/semantics/other
oai:zenodo.org:2600266
2020-01-24T19:25:58Z
openaire_data
user-research-compendium
Schratz, Patrick
Muenchow, Jannes
Iturritxa, Eugenia
Richter, Jakob
Brenning, Alexander
2019-03-04
<p>This is a research compendium (RC) for the publication "Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data".</p>
<p>The code (including figures, appendices and the manuscript) is packed in <strong>pathogen-modeling-master.zip</strong> or can be found directly in the <a href="https://github.com/pat-s/pathogen-modeling">Github repository</a>.</p>
<p><strong>Publication figures</strong>: analysis/paper/submission/3/latex-source-files/</p>
<p><strong>Appendices</strong>: analysis/paper/submission/3/</p>
<p>This RC represents a static snapshot of the publication mentioned above. The Github repo will receive changes after the publication was published.</p>
https://doi.org/10.5281/zenodo.2600266
oai:zenodo.org:2600266
Zenodo
https://arxiv.org/abs/1803.11266
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.2582969
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
spatial modeling
machine-learning
spatial autocorrelation
hyperparameter tuning
spatial cross-validation
Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
info:eu-repo/semantics/other
oai:zenodo.org:1227761
2020-01-24T19:25:43Z
openaire_data
user-research-compendium
Granell, Carlos
Hofer, Barbara
Konkol, Markus
Ostermann, Frank O.
Sileryte, Rusne
Certutti, Valentina
Nüst, Daniel
2018-04-23
<p>Data and code for analysis and plots used in the manuscript "Reproducible research and GIScience: an evaluation using AGILE conference papers": <a href="https://doi.org/10.7287/peerj.preprints.26561v1">https://doi.org/10.7287/peerj.preprints.26561v1</a></p>
<p>The deposited archived includes a <a href="https://en.wikipedia.org/wiki/Docker_(software)">Dockerfile</a> and an <a href="http://rmarkdown.rstudio.com/">R Markdown</a> document suitable for use with <a href="http://mybinder.org/">Binder</a>: <a href="https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2">https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2</a></p>
https://doi.org/10.5281/zenodo.1227761
oai:zenodo.org:1227761
eng
Zenodo
https://doi.org/10.7287/peerj.preprints.26561v1
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1227260
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
GIScience
Reproducibility Package for "Reproducible research and GIScience: an evaluation using AGILE conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:1297419
2020-01-24T19:25:46Z
openaire_data
user-research-compendium
Granell, Carlos
Hofer, Barbara
Konkol, Markus
Ostermann, Frank O.
Sileryte, Rusne
Certutti, Valentina
Nüst, Daniel
2018-04-23
<p>Data and code for analysis and plots used in the manuscript "Reproducible research and GIScience: an evaluation using AGILE conference papers": <a href="https://doi.org/10.7287/peerj.preprints.26561v1">https://doi.org/10.7287/peerj.preprints.26561v1</a></p>
<p>The deposited archived includes a <a href="https://en.wikipedia.org/wiki/Docker_(software)">Dockerfile</a> and an <a href="http://rmarkdown.rstudio.com/">R Markdown</a> document suitable for use with <a href="http://mybinder.org/">Binder</a>: <a href="https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2">https://mybinder.org/v2/gh/nuest/reproducible-research-and-giscience/2</a></p>
<p>The version tag of this repository matches the <a href="https://git-scm.com/book/en/v2/Git-Basics-Tagging">git tag</a> on the code repository at <a href="https://github.com/nuest/reproducible-research-and-giscience">https://github.com/nuest/reproducible-research-and-giscience</a>.</p>
The documents in this repository are licensed under a Creative Commons Attribution 4.0 International License.
All contained code is licensed under the Apache License 2.0.
The data used is licensed under a Open Data Commons Attribution License.
https://doi.org/10.5281/zenodo.1297419
oai:zenodo.org:1297419
eng
Zenodo
https://doi.org/10.7287/peerj.preprints.26561v1
https://doi.org/10.7717/peerj.5072
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.1227260
info:eu-repo/semantics/openAccess
Other (Open)
GIScience
Reproducibility Package for "Reproducible research and GIScience: an evaluation using AGILE conference papers"
info:eu-repo/semantics/other
oai:zenodo.org:2621996
2020-01-24T19:25:58Z
openaire_data
user-research-compendium
Schratz, Patrick
Muenchow, Jannes
Iturritxa, Eugenia
Richter, Jakob
Brenning, Alexander
2019-04-08
<p>This is a research compendium (RC) for the publication "Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data".</p>
<p>The code (including figures, appendices and the manuscript) is packed in <strong>pathogen-modeling-master.zip </strong>or can be found directly in the <a href="https://github.com/pat-s/pathogen-modeling">Github repository</a>.</p>
<ul>
<li><strong>Publication figures</strong>: analysis/paper/submission/3/latex-source-files/</li>
<li><strong>Appendices</strong>: analysis/paper/submission/3/</li>
</ul>
<p>This RC represents a static snapshot at the time of submission. The Github repository will receive changes after the publication was published.</p>
<p><strong>Data sources</strong></p>
<ul>
<li>Atlas Climatico: <a href="http://opengis.uab.es/wms/iberia/index.htm">http://opengis.uab.es/wms/iberia/index.htm</a></li>
<li>DEM: ftp://ftp.geo.euskadi.eus/lidar/MDE_LIDAR_2016_ETRS89/</li>
<li>Lithology: <a href="http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home">http://www.geo.euskadi.eus/geonetwork/srv/spa/main.home</a></li>
<li>pH: <a href="https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0">https://esdac.jrc.ec.europa.eu/content/soil-ph-europe#tabs-0-description=0</a></li>
<li>soil: <a href="https://www.isric.org/explore/soilgrids">https://www.isric.org/explore/soilgrids</a></li>
</ul>
<p><strong>Licenses</strong></p>
<p>All files are shared via the given license with the exception of "soil.tif" which is shared via the <strong>ODbL </strong>license<strong>.</strong></p>
https://doi.org/10.5281/zenodo.2621996
oai:zenodo.org:2621996
Zenodo
https://arxiv.org/abs/1803.11266
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.2582969
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
spatial modeling
machine-learning
spatial autocorrelation
hyperparameter tuning
spatial cross-validation
Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
info:eu-repo/semantics/other
oai:zenodo.org:2582970
2020-01-24T19:25:16Z
openaire_data
user-research-compendium
Schratz, Patrick
Muenchow, Jannes
Iturritxa, Eugenia
Richter, Jakob
Brenning, Alexander
2019-03-04
<p>This repository will contain the research compendium of our work on comparing algorithms across different resampling settings.</p>
https://doi.org/10.5281/zenodo.2582970
oai:zenodo.org:2582970
Zenodo
https://arxiv.org/abs/1803.11266
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.2582969
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
machine-learning
ecological modeling
hyperparameter tuning
pathogen
benchmarking
Analyzing the importance of spatial autocorrelation in hyperparameter tuning and performance estimation of machine-learning algorithms for spatial data.
info:eu-repo/semantics/other
oai:zenodo.org:2591746
2020-01-24T19:26:01Z
openaire_data
user-research-compendium
Schratz, Patrick
Muenchow, Jannes
Iturritxa, Eugenia
Richter, Jakob
Brenning, Alexander
2019-03-04
<p>This repository will contain the research compendium of our work on comparing algorithms across different resampling settings.</p>
https://doi.org/10.5281/zenodo.2591746
oai:zenodo.org:2591746
Zenodo
https://arxiv.org/abs/1803.11266
https://zenodo.org/communities/research-compendium
https://doi.org/10.5281/zenodo.2582969
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
machine-learning
ecological modeling
hyperparameter tuning
pathogen
benchmarking
Analyzing the importance of spatial autocorrelation in hyperparameter tuning and performance estimation of machine-learning algorithms for spatial data.
info:eu-repo/semantics/other