cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.1403204
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: PEPIC wheat

description: This is model output from PEPIC for wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403208
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: PEPIC rice

description: This is model output from PEPIC for rice as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1403210
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: PEPIC maize

description: This is model output from PEPIC for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1410541
title: High Resolution Retinal Blood Vessels Datasets Of Diabetic Retinopathy Patients

description: This dataset contains 89 high resolution image files of blood vessels extracted from publicly available retina images available in DIARETDB1
DOI: 10.5281/zenodo.1410542
title: High Resolution Retinal Blood Vessels Datasets Of Diabetic Retinopathy Patients

description: This dataset contains 89 high resolution image files of blood vessels extracted from publicly available retina images available in DIARETDB1
DOI: 10.5281/zenodo.1410647
title: Identifier Refinery Conversion Matrixes

description: <strong>identifier-refinery</strong>

Tools and assets for easy and reproducable gene identifier conversion.

<strong>Methods</strong>

This repository is used to build matricies which can convert between different gene identifiers.

These conversion matricies are built by:


	Randomly choosing raw CEL files from NCBI GEO for a given platform accession code (in <code>/cels</code>)
	Reading the CEL header and joining Brainarray (e.g., <code>hgu133plus2hsensgprobe</code>) and Bioconductor (e.g., <code>hgu133plus2.db</code>) (x, y) coordinates
	Finding intersecting probe identifiers
	Extracting supported identifiers and probe IDs from the Bioconductor package
	Filtering on probe IDs and Ensembl Gene IDs in Brainarray
	Writing the output to a conversion TSV file
	Check that all output conversion TSV files have a shared SHA1


<strong>Repository Contents</strong>

<strong>Source Files</strong>

The <code>cels</code> directory contains raw CEL files taken from GEO. The list of supported platforms is in <code>supported_microarray_platforms.csv</code>. Source files can be acquired by running the <code>acquire_cels.py</code> script.

<strong>Docker Image</strong>

The conversion scripts are run on custom Docker images.

Two Dockerfiles are provided in this repository - <code>base</code> Docker image, which is used to install the quire R dependancies, and the <code>pd</code> image, which is used to build the required databases for a given platform.

<strong>Conversion Scripts</strong>

A <code>build_and_convert.py</code> script is provided, which build a unique Docker image for each package, mount the downloaded CEL files as a volume, and then run the gene conversion script <code>R/gene_convert.R</code> inside the image and output the master conversion matrix. Output TSV files live in <code>cels/out/</code>.

<strong>Reproducing</strong>

The entire process can be reproduced by running the following command script from a fresh checkout of this repository. It will take some time:

<pre><code>$ ./generate_matricies_from_scratch.sh
</code></pre>

You can also choose to only build a specific platform, ex.,:

<pre><code>$ ./generate_matricies_from_scratch.sh celegans
</code></pre>

<strong>Identifiers</strong>

Released assets in this repository are availble under the DOI, <code>xyz:1.2.3.4</code>, which can be seen on Zenodo here.

<strong>Related Projects</strong>


	AlexsLemonade/refinebio


<strong>Copyright</strong>

<code>identifier-refinery</code> output assets are released under a CC0 1.0 Universal license. All code is released under the BSD 3-clause license. Input assets are property of the original providers to NCBI GEO, but may be freely downloaded and redistributed unless otherwise noted.

 

https://github.com/AlexsLemonade/identifier-refinery
DOI: 10.5517/ccdc.csd.cc1z8lmg
title: CCDC 1825516: Experimental Crystal Structure Determination

description: Related Article: Fei-Long Hu, Yan Mi, Chen Zhu, Brendan F. Abrahams, Pierre Braunstein, and Jian-Ping Lang|2018|Angew.Chem.,Int.Ed.|57|12696|doi:10.1002/anie.201806076
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1zr080
title: CCDC 1839362: Experimental Crystal Structure Determination

description: Related Article: Hanbyul Kim, Su Yeon Choi, Seunghoon Shin|2018|Angew.Chem.,Int.Ed.|57|13130|doi:10.1002/anie.201807514
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1ztggq
title: CCDC 1841724: Experimental Crystal Structure Determination

description: Related Article: Fei-Long Hu, Yan Mi, Chen Zhu, Brendan F. Abrahams, Pierre Braunstein, and Jian-Ping Lang|2018|Angew.Chem.,Int.Ed.|57|12696|doi:10.1002/anie.201806076
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc1ztghr
title: CCDC 1841725: Experimental Crystal Structure Determination

description: Related Article: Fei-Long Hu, Yan Mi, Chen Zhu, Brendan F. Abrahams, Pierre Braunstein, and Jian-Ping Lang|2018|Angew.Chem.,Int.Ed.|57|12696|doi:10.1002/anie.201806076
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5281/zenodo.1404760
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-Boku wheat

description: This is model output from EPIC-Boku for wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1404761
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-Boku wheat

description: This is model output from EPIC-Boku for wheat as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1404762
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-Boku soy

description: This is model output from EPIC-Boku for soy as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1404763
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-Boku soy

description: This is model output from EPIC-Boku for soy as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1404765
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-Boku rice

description: This is model output from EPIC-Boku for rice as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1404767
title: AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set: EPIC-Boku maize

description: This is model output from EPIC-Boku for maize as part of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 output data set.

The data have been generated following the modeling protocol of Elliott et al. (2015) and has been used to evaluate the models (Müller et al., 2017). A data description paper has been published in Scientific Data (Müller et al. 2019).

References:

Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, and Sheffield J. 2015, The Global Gridded Crop Model intercomparison: data and modeling protocols for Phase 1 (v1.0). Geosci. Model Dev. 8, 261-277, doi:10.5194/gmd-8-261-2015

Müller C, Elliott J, Chryssanthacopoulos J, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Glotter M, Hoek S, Iizumi T, Izaurralde RC, Jones C, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Ray DK, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Song CX, Wang X, de Wit A, and Yang H. 2017, Global gridded crop model evaluation: benchmarking, skills, deficiencies and implications, Geosci. Model Dev., 10, 1403-1422, doi: 10.5194/gmd-10-1403-2017

Müller C, Elliott J, Kelly D, Arneth A, Balkovic J, Ciais P, Deryng D, Folberth C, Hoek S, Izaurralde RC, Jones CD, Khabarov N, Lawrence P, Liu W, Olin S, Pugh TAM, Reddy A, Rosenzweig C, Ruane AC, Sakurai G, Schmid E, Skalsky R, Wang X, de Wit A, and Yang H. 2019, The Global Gridded Crop Model Intercomparison phase 1 simulation dataset, Scientific Data, 6, 50, doi: 10.1038/s41597-019-0023-8
DOI: 10.5281/zenodo.1409951
title: The Landscape Of Open Access In Africa

description: This project is a continuation from this previous project stored here (https://zenodo.org/record/817600#.W5DGy359hyU). It was based on the following keywords:

"Open Access" OR "Institutional Repository" OR "Self-archiving" OR "Green OA" OR "Gold OA" AND Africa

We used Web of Science database provided by The University of Sydney in Sep 6 2018. There were 3986 docs, but it decreased to 3976, presumably due to bad records when we imported it to Jabref Ref Manager. We export the dataset in to CSV and RIS for easy use.
DOI: 10.5281/zenodo.1409952
title: The Landscape Of Open Access In Africa

description: This project is a continuation from this previous project stored here (https://zenodo.org/record/817600#.W5DGy359hyU). It was based on the following keywords:

"Open Access" OR "Institutional Repository" OR "Self-archiving" OR "Green OA" OR "Gold OA" AND Africa

We used Web of Science database provided by The University of Sydney in Sep 6 2018. There were 3986 docs, but it decreased to 3976, presumably due to bad records when we imported it to Jabref Ref Manager. We export the dataset in to CSV and RIS for easy use.
DOI: 10.5281/zenodo.1169588
title: Bibliographic References Extracted From Theses And Dissertations In The Electronic Theses And Dissertations Library Of The Federal University Of Paraná, Brazil

description: Bibliographic references obtained from a subset of PDF files in the Electronic Theses and Dissertations Library of the Federal University of Paraná, Brazil, extracted through ParsCit.
DOI: 10.5281/zenodo.1169589
title: Bibliographic References Extracted From Theses And Dissertations In The Electronic Theses And Dissertations Library Of The Federal University Of Paraná, Brazil

description: Bibliographic references obtained from a subset of PDF files in the Electronic Theses and Dissertations Library of the Federal University of Paraná, Brazil, extracted through ParsCit.