cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive130503.20201210.5
title: Massilia sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130504.20201210.5
title: Telluria mixta (Bowman et al. 1989) Bowman et al. 1993

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130505.20201210.5
title: Undibacterium seohonense Kim et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130506.20201210.5
title: Undibacterium macrobrachii Sheu et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130507.20201210.5
title: Glaciimonas singularis Chung et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5887008
title: Potential and realized distribution at 30m for Holm oak (Quercus ilex) in Europe for 2000 - 2020

description: Probability and uncertainty maps showing the potential and realized distribution for the holm oak (<em>Quercus ilex L.</em>) for Europe from the dataset prepared by Bonannella et al. (2022) and predicted using Ensemble Machine Learning (EML). Potential distribution map cover the period 2018 - 2020; realized distribution cover the period 2000 - 2020, split in the following time periods: 2000 - 2002, 2002 - 2006, 2006 - 2010, 2010 - 2014, 2014 - 2018, 2018 - 2020. Files are named according to the following naming convention, e.g: veg_quercus.ilex_anv.eml_md_30m_0..0cm_2000..2002_eumap_epsg3035_v0.2 with the following fields: theme: e.g. <strong>veg</strong>, species code: e.g. <strong>quercus.ilex</strong>, species distribution type: e.g. <strong>anv</strong> (= actual natural vegetation), species estimation method: e.g. <strong>eml</strong>, species estimation type: e.g. <strong>md</strong> ( = model deviation), resolution in meters e.g. <strong>30m</strong>, reference depths (vertical dimension): e.g. <strong>0..0cm</strong>, reference period begin end: e.g. <strong>2000..2002</strong>, reference area: e.g. <strong>eumap</strong>, coordinate system: e.g. <strong>epsg3035</strong>, data set version: e.g. <strong>v0.2</strong>. For each species is then easy to identify probability and uncertainty distribution maps: veg_quercus.ilex_<strong>anv</strong>.eml_<strong>md</strong>: model uncertainty for realized distribution veg_quercus.ilex_<strong>anv</strong>.eml_<strong>p</strong>: probability for realized distribution veg_quercus.ilex_<strong>pnv</strong>.eml_<strong>md</strong>: model uncertainty for potential distribution veg_quercus.ilex_<strong>pnv</strong>.eml_<strong>p</strong>: probability for potential distribution Files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in both <em>SLD</em> and <em>QML</em> format. If you would like to know more about the creation of the maps and the modeling: <strong>watch</strong> the talk at Open Data Science Workshop 2021 (TIB AV-PORTAL) <strong>access </strong>the repository with our R/Python scripts and follow the instructions (GitLab) <strong>access </strong>the repository with the training dataset (Zenodo) A publication describing, in detail, all processing steps, accuracy assessment and general analysis of species distribution maps is under preparation. You can access the preprint on ResearchSquare. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.13145/bacdive130508.20201210.5
title: Glaciimonas alpina Frasson et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130509.20201210.5
title: Cohnella nanjingensis Huang et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130510.20201210.5
title: Paenibacillus glucanolyticus (Alexander and Priest 1989) Shida et al. 1997

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130511.20201210.5
title: Paenibacillus senegalensis Mishra et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5887416
title: Potential and realized distribution at 30m for pedunculate oak (Quercus robur) in Europe for 2000 - 2020

description: Probability and uncertainty maps showing the potential and realized distribution for the pedunculate oak (<em>Quercus robur, L.</em>) for Europe from the dataset prepared by Bonannella et al. (2022) and predicted using Ensemble Machine Learning (EML). Potential distribution map cover the period 2018 - 2020; realized distribution cover the period 2000 - 2020, split in the following time periods: 2000 - 2002, 2002 - 2006, 2006 - 2010, 2010 - 2014, 2014 - 2018, 2018 - 2020. Files are named according to the following naming convention, e.g: veg_quercus.robur_anv.eml_md_30m_0..0cm_2000..2002_eumap_epsg3035_v0.2 with the following fields: theme: e.g. <strong>veg</strong>, species code: e.g. <strong>quercus.robur</strong>, species distribution type: e.g. <strong>anv</strong> (= actual natural vegetation), species estimation method: e.g. <strong>eml</strong>, species estimation type: e.g. <strong>md</strong> ( = model deviation), resolution in meters e.g. <strong>30m</strong>, reference depths (vertical dimension): e.g. <strong>0..0cm</strong>, reference period begin end: e.g. <strong>2000..2002</strong>, reference area: e.g. <strong>eumap</strong>, coordinate system: e.g. <strong>epsg3035</strong>, data set version: e.g. <strong>v0.2</strong>. For each species is then easy to identify probability and uncertainty distribution maps: veg_quercus.robur_<strong>anv</strong>.eml_<strong>md</strong>: model uncertainty for realized distribution veg_quercus.robur_<strong>anv</strong>.eml_<strong>p</strong>: probability for realized distribution veg_quercus.robur_<strong>pnv</strong>.eml_<strong>md</strong>: model uncertainty for potential distribution veg_quercus.robur_<strong>pnv</strong>.eml_<strong>p</strong>: probability for potential distribution Files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in both <em>SLD</em> and <em>QML</em> format. If you would like to know more about the creation of the maps and the modeling: <strong>watch</strong> the talk at Open Data Science Workshop 2021 (TIB AV-PORTAL) <strong>access </strong>the repository with our R/Python scripts and follow the instructions (GitLab) <strong>access </strong>the repository with the training dataset (Zenodo) A publication describing, in detail, all processing steps, accuracy assessment and general analysis of species distribution maps is under preparation. You can access the preprint on ResearchSquare. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.13145/bacdive130512.20201210.5
title: Paenibacillus sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130513.20201210.5
title: Paenibacillus sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130514.20201210.5
title: Paenibacillus gorillae Keita et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5896621
title: Potential and realized distribution at 30m for Cork oak (Quercus suber) in Europe for 2000 - 2020

description: Probability and uncertainty maps showing the potential and realized distribution for the cork oak (<em>Quercus suber, L.</em>) for Europe from the dataset prepared by Bonannella et al. (2022) and predicted using Ensemble Machine Learning (EML). Potential distribution map cover the period 2018 - 2020; realized distribution cover the period 2000 - 2020, split in the following time periods: 2000 - 2002, 2002 - 2006, 2006 - 2010, 2010 - 2014, 2014 - 2018, 2018 - 2020. Files are named according to the following naming convention, e.g: veg_quercus.suber_anv.eml_md_30m_0..0cm_2000..2002_eumap_epsg3035_v0.2 with the following fields: theme: e.g. <strong>veg</strong>, species code: e.g. <strong>quercus.suber</strong>, species distribution type: e.g. <strong>anv</strong> (= actual natural vegetation), species estimation method: e.g. <strong>eml</strong>, species estimation type: e.g. <strong>md</strong> ( = model deviation), resolution in meters e.g. <strong>30m</strong>, reference depths (vertical dimension): e.g. <strong>0..0cm</strong>, reference period begin end: e.g. <strong>2000..2002</strong>, reference area: e.g. <strong>eumap</strong>, coordinate system: e.g. <strong>epsg3035</strong>, data set version: e.g. <strong>v0.2</strong>. For each species is then easy to identify probability and uncertainty distribution maps: veg_quercus.suber_<strong>anv</strong>.eml_<strong>md</strong>: model uncertainty for realized distribution veg_quercus.suber_<strong>anv</strong>.eml_<strong>p</strong>: probability for realized distribution veg_quercus.suber_<strong>pnv</strong>.eml_<strong>md</strong>: model uncertainty for potential distribution veg_quercus.suber_<strong>pnv</strong>.eml_<strong>p</strong>: probability for potential distribution Files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in both <em>SLD</em> and <em>QML</em> format. If you would like to know more about the creation of the maps and the modeling: <strong>watch</strong> the talk at Open Data Science Workshop 2021 (TIB AV-PORTAL) <strong>access </strong>the repository with our R/Python scripts and follow the instructions (GitLab) <strong>access </strong>the repository with the training dataset (Zenodo) A publication describing, in detail, all processing steps, accuracy assessment and general analysis of species distribution maps is under preparation. You can access the preprint on ResearchSquare. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.13145/bacdive130515.20201210.5
title: Paenibacillus abyssi Huang et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130516.20201210.5
title: Paenibacillus nicotianae Li et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.48370/ofd/tbnk4r
title: Nectria cinnabarina (Tode) Fries, 3041

description: Fungarium Makromycetes
DOI: 10.13145/bacdive130517.20201210.5
title: Paenibacillus tibetensis Han et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130518.20201210.5
title: Gorillibacterium massiliense Keita et al. 2017 emend. Hwang et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130519.20201210.5
title: Frederiksenia canicola Korczak et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5896666
title: Potential and realized distribution at 30m for Goat willow (Salix caprea) in Europe for 2000 - 2020

description: Probability and uncertainty maps showing the potential and realized distribution for the goat willow (<em>Salix caprea, L.</em>) for Europe from the dataset prepared by Bonannella et al. (2022) and predicted using Ensemble Machine Learning (EML). Potential distribution map cover the period 2018 - 2020; realized distribution cover the period 2000 - 2020, split in the following time periods: 2000 - 2002, 2002 - 2006, 2006 - 2010, 2010 - 2014, 2014 - 2018, 2018 - 2020. Files are named according to the following naming convention, e.g: veg_salix.caprea_anv.eml_md_30m_0..0cm_2000..2002_eumap_epsg3035_v0.2 with the following fields: theme: e.g. <strong>veg</strong>, species code: e.g. <strong>salix.caprea</strong>, species distribution type: e.g. <strong>anv</strong> (= actual natural vegetation), species estimation method: e.g. <strong>eml</strong>, species estimation type: e.g. <strong>md</strong> ( = model deviation), resolution in meters e.g. <strong>30m</strong>, reference depths (vertical dimension): e.g. <strong>0..0cm</strong>, reference period begin end: e.g. <strong>2000..2002</strong>, reference area: e.g. <strong>eumap</strong>, coordinate system: e.g. <strong>epsg3035</strong>, data set version: e.g. <strong>v0.2</strong>. For each species is then easy to identify probability and uncertainty distribution maps: veg_salix.caprea_<strong>anv</strong>.eml_<strong>md</strong>: model uncertainty for realized distribution veg_salix.caprea_<strong>anv</strong>.eml_<strong>p</strong>: probability for realized distribution veg_salix.caprea_<strong>pnv</strong>.eml_<strong>md</strong>: model uncertainty for potential distribution veg_salix.caprea_<strong>pnv</strong>.eml_<strong>p</strong>: probability for potential distribution Files are provided as Cloud Optimized GeoTIFFs and projected in the Coordinate Reference System ETRS89 / LAEA Europe (= EPSG code 3035). Styling files are provided in both <em>SLD</em> and <em>QML</em> format. If you would like to know more about the creation of the maps and the modeling: <strong>watch</strong> the talk at Open Data Science Workshop 2021 (TIB AV-PORTAL) <strong>access </strong>the repository with our R/Python scripts and follow the instructions (GitLab) <strong>access </strong>the repository with the training dataset (Zenodo) A publication describing, in detail, all processing steps, accuracy assessment and general analysis of species distribution maps is under preparation. You can access the preprint on ResearchSquare. To suggest any improvement/fix use https://gitlab.com/geoharmonizer_inea/spatial-layers/-/issues.
description: This work is co-financed under Grant Agreement Connecting Europe Facility (CEF) Telecom project 2018-EU-IA-0095 by the European Union (https://ec.europa.eu/inea/en/connecting-europe-facility/cef-telecom/2018-eu-ia-0095).
DOI: 10.13145/bacdive130520.20201210.5
title: Vespertiliibacter pulmonis Mühldorfer et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130521.20201210.5
title: Mesocricetibacter intestinalis Christensen et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130522.20201210.5
title: Cricetibacter osteomyelitidis Christensen et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5897197
title: Preoperative Anemia Correction in Cardiac Surgery: A Propensity-Matched Study

description: Dataset from Ranucci M, Pavesi M, Pistuddi V, Baryshnikova E. Preoperative Anemia Correction in Cardiac Surgery: A Propensity-Matched Study. J Cardiothorac Vasc Anesth. 2021 Mar;35(3):874-881. doi: 10.1053/j.jvca.2020.07.015. Epub 2020 Jul 7. PMID: 32741609.
DOI: 10.5281/zenodo.5897196
title: Preoperative Anemia Correction in Cardiac Surgery: A Propensity-Matched Study

description: Dataset from Ranucci M, Pavesi M, Pistuddi V, Baryshnikova E. Preoperative Anemia Correction in Cardiac Surgery: A Propensity-Matched Study. J Cardiothorac Vasc Anesth. 2021 Mar;35(3):874-881. doi: 10.1053/j.jvca.2020.07.015. Epub 2020 Jul 7. PMID: 32741609.
DOI: 10.13145/bacdive130523.20201210.5
title: Desulfosporosinus acididurans Sánchez-Andrea et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130524.20201210.5
title: Desulfohalotomaculum tongense (Cha et al. 2014) Watanabe et al. 2018

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130525.20201210.5
title: Aquamicrobium terrae Wu et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130526.20201210.5
title: Pseudaminobacter sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130527.20201210.5
title: Mesorhizobium robiniae Zhou et al. 2010

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130528.20201210.5
title: Mesorhizobium camelthorni Chen et al. 2011

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130529.20201210.5
title: Mesorhizobium silamurunense Zhao et al. 2012

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130530.20201210.5
title: Mesorhizobium muleiense Zhang et al. 2012

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130531.20201210.5
title: Mesorhizobium hawassense Degefu et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130532.20201210.5
title: Mesorhizobium qingshengii Zheng et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130533.20201210.5
title: Mesorhizobium sangaii Zhou et al. 2013

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130534.20201210.5
title: Rhodopirellula rosea Roh et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130535.20201210.5
title: Rhodopirellula lusitana Bondoso et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5897468
title: Dataset for XBeach model calibration and simulation of sample storms in an intermediate-to-dissipative, microtidal coast (Sabaudia, Italy)

description: The archive contains XBeach input data and datasets used for the calibration of the hydrodynamic model XBeach and subsequent simulation of six sample storms at different tidal levels at the intermediate-to-dissipative, microtidal coast of Sabaudia (Tyrrhenian Sea, Italy). VERSION v2 (January 24, 2022): uploaded a new version of the dataset to support the revised version of the manuscript.
DOI: 10.13145/bacdive130536.20201210.5
title: Rhodopirellula rubra Bondoso et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.5281/zenodo.5470253
title: Dataset for XBeach model calibration and simulation of sample storms in an intermediate-to-dissipative, microtidal coast (Sabaudia, Italy)

description: The archive contains XBeach input data and datasets used for the calibration of the hydrodynamic model XBeach and subsequent simulation of six sample storms at different tidal levels at the intermediate-to-dissipative, microtidal coast of Sabaudia (Tyrrhenian Sea, Italy). VERSION v2 (January 24, 2022): uploaded a new version of the dataset to support the revised version of the manuscript.
DOI: 10.13145/bacdive130537.20201210.5
title: Kurthia senegalensis Roux et al. 2016

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130538.20201210.5
title: Kurthia senegalensis Roux et al. 2016

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130539.20201210.5
title: Planomicrobium sp.

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130540.20201210.5
title: Sporosarcina siberiensis Zhang et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130541.20201210.5
title: Dysgonomonas macrotermitis Yang et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130542.20201210.5
title: Microbacter margulisiae Sánchez-Andrea et al. 2014

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130543.20201210.5
title: Myceligenerans cantabricum Sarmiento-Vizcaíno et al. 2015

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive130544.20201210.5
title: Acidipropionibacterium olivae (Lucena-Padrós et al. 2014) Scholz and Kilian 2016

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.