cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5526/erdr-00000216
title: Cattle grazing observations

description: Cattle (n = three individuals) were equipped with GPS sensors via coloured collars and continuously observed at a distance for a mean of two hours per day (ranging from 30 minutes to three hours per day). Each of the three collared individuals were all observed during each observation period, except on 16/10/2023 where data were collected from cattle ID 294364 only. Individuals were recorded as either grazing or not grazing, with the observer primarily focussing on a focal individual. An individual was considered to be grazing when observed with their head lowered, actively consuming vegetation and not ruminating.
DOI: 10.5526/erdr-00000215
title: Cattle GPS locations, activity and temperature

description: Commercial Global Positioning System (GPS) sensors were deployed on three outdoor cattle to track their location and activity. The sensors recorded locations every 15 minutes when the animals were active and the update rate was reduced when the animals were not active to conserve battery. Activity index was measured by a dynamometer embedded in the cow-equipped sensors, where each movement along the heave axis over a half-hour period incremented the count by one. Additionally, the sensors recorded temperature every half an hour.
description: The original data were obtained from Nofence® sensors.
DOI: 10.15468/dl.sxze4k
title: Occurrence Download

description: A dataset containing 83100 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lapsana communis subsp. communis)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 83100 records from 374 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035607-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5526/erdr-00000212
title: The Making of a Nation: Who Voted for Australian Federation?

description: Database developed to analyse votes by polling booth in the 1898 and 1899 referendums on federation in New South Wales, Australia
description: Votes registered by polling booth in 1898 and 1899 digitised and geocoded
County level variables from the 1901 census of New south Wales also geocoded
description: Geolocated polling booths have been linked to geographical boundaries of the counties of New South Wales as described in Appendix 1 of the paper.
DOI: 10.15468/dl.cwb2uv
title: Occurrence Download

description: A dataset containing 2842 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lapsana communis subsp. intermedia (M.Bieb.) Hayek)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 2842 records from 101 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035608-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10927336
title: EXE1: dataset 1 collected within the framework of the Civil Protection Exercise "EXE.Lomb.Est 2023"

description: Raw images dataset collected using multi-rotor UASs within the first assignment EXE 1 of the medium-scale technical civil protection exercise “EXE.Lomb.Est 2023”, carried out in October 2023 during Italian Civil Protection Week. 

The assignment is related to the post-event rapid mapping of a medium-size area for fast assessment.

The technical group is a network of Italian Civil Protection Centre of Competence with internal UAS units.

 
description: Part of the dataset collection has been carried out under the financial support of the Italian Civil Protection (within the framework of the Executive Project 2022–2023 with the EUCENTRE Foundation) and of the Lombardy Region (within the convention 2022-2024 with the EUCENTRE Foundation: L.R. 27/2021- art. 8; L.R: 33/2015 e DGR 5935/2022).
description: In addition to the contributors, the following participants actively supported the dataset collection: Ilaria Enrica Senaldi, Emanuele Brunesi, Stefano Bracchi and Igor Lanese (EUCENTRE Foundation); Andrea Giorgi and Luca Stefanoli (ARPA Valle d'Aosta); Gianluca Negra (CIMA Foundation); Salvatore Arcuri (ARPA Calabria); Dario Bellingeri (ARPA Lombardia); Daniele Trippanera, Martina Forzese, Alessandro Fornaciai and Andrea Bevilacqua (INGV); Andrea Berton, Angelo Ballaera, Roberto De Franco and Grazia Caielli (CNR); Gabriele Scaduto (Università di Firenze).
DOI: 10.5281/zenodo.10927337
title: EXE1: dataset 1 collected within the framework of the Civil Protection Exercise "EXE.Lomb.Est 2023"

description: Raw images dataset collected using multi-rotor UASs within the first assignment EXE 1 of the medium-scale technical civil protection exercise “EXE.Lomb.Est 2023”, carried out in October 2023 during Italian Civil Protection Week. 

The assignment is related to the post-event rapid mapping of a medium-size area for fast assessment.

The technical group is a network of Italian Civil Protection Centre of Competence with internal UAS units.

 
description: Part of the dataset collection has been carried out under the financial support of the Italian Civil Protection (within the framework of the Executive Project 2022–2023 with the EUCENTRE Foundation) and of the Lombardy Region (within the convention 2022-2024 with the EUCENTRE Foundation: L.R. 27/2021- art. 8; L.R: 33/2015 e DGR 5935/2022).
description: In addition to the contributors, the following participants actively supported the dataset collection: Ilaria Enrica Senaldi, Emanuele Brunesi, Stefano Bracchi and Igor Lanese (EUCENTRE Foundation); Andrea Giorgi and Luca Stefanoli (ARPA Valle d'Aosta); Gianluca Negra (CIMA Foundation); Salvatore Arcuri (ARPA Calabria); Dario Bellingeri (ARPA Lombardia); Daniele Trippanera, Martina Forzese, Alessandro Fornaciai and Andrea Bevilacqua (INGV); Andrea Berton, Angelo Ballaera, Roberto De Franco and Grazia Caielli (CNR); Gabriele Scaduto (Università di Firenze).
DOI: 10.15468/dl.bz6pgk
title: Occurrence Download

description: A dataset containing 321 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Lardizabala funaria (Molina) Looser)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 321 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035609-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cw3c3f
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (BOLD:ACJ2316)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 15 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035611-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.26370274
title: Supplementary Figure S2 - sdhA Gammaproteobacteria

description: Data files for the sdhA phylogeny in Supplementary Figure S2 of "Genetic potential for aerobic respiration and denitrification in globally distributed respiratory endosymbionts".<br><br>Files for a sdhA gene phylogeny of representatives of 305 gammaproteobacterial families included in Supplementary Figure S1. The genomes/mags included were obtained from the Genome Taxonomy Database (GTDB) and the genomic catalog of earth's microbiomes (GEM).<br><br>references:<br>GTDB:<br>https://academic.oup.com/nar/article/50/D1/D785/6370255 & https://gtdb.ecogenomic.org/<br>GEM:<br>https://www.nature.com/articles/s41587-020-0718-6 & https://genome.jgi.doe.gov/portal/GEMs/GEMs.home.html
DOI: 10.6084/m9.figshare.26370274.v1
title: Supplementary Figure S2 - sdhA Gammaproteobacteria

description: Data files for the sdhA phylogeny in Supplementary Figure S2 of "Genetic potential for aerobic respiration and denitrification in globally distributed respiratory endosymbionts".<br><br>Files for a sdhA gene phylogeny of representatives of 305 gammaproteobacterial families included in Supplementary Figure S1. The genomes/mags included were obtained from the Genome Taxonomy Database (GTDB) and the genomic catalog of earth's microbiomes (GEM).<br><br>references:<br>GTDB:<br>https://academic.oup.com/nar/article/50/D1/D785/6370255 & https://gtdb.ecogenomic.org/<br>GEM:<br>https://www.nature.com/articles/s41587-020-0718-6 & https://genome.jgi.doe.gov/portal/GEMs/GEMs.home.html
DOI: 10.15468/dl.pa28cm
title: Occurrence Download

description: A dataset containing 18 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Fraxinus retusifoliolata K.M.Feng ex P.Y.Pai"
 ]
}

 The dataset includes 18 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035612-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5255/ukda-sn-857144
title: Processes of Hybridisation in Peace and Conflict Processes in Madagascar, Hybricon 1575-2019

description: Madagascar's historical interactions with external actors have significantly influenced its socio-political and economic dynamics. Despite recent advancements in understanding hybridisation—the blending of international (liberal and illiberal) and local (non-liberal) institutions, practices, and values—very little is understood about how these processes affect local conflict trajectories. 
The motivation for this research stems from the need to understand the complex mechanisms behind the formation of hybrid institutions in Madagascar. 
What are the dynamics underlying the hybridisation of international (liberal/illiberal) and local (non-liberal) institutions, practices, and values in Madagascar? 
How do these dynamics influence local conflict trajectories, particularly in terms of escalation, de-escalation, and the protraction of conflicts? 
This research argues that local variations in hybridisation processes result in diverse conflict outcomes, thereby shaping distinct local conflict trajectories. To understand the characteristics of hybridisation and its impact on conflict, the study investigates the interactions between the "international" and the "local" in both central and peripheral regions of Madagascar. The focus is on Antananarivo (the centre) and peripheral areas including Antsiranana (Diego), Fenoarivo Atsinanana (Fenerive Est), Toamasina (Tamatave), Mahajanga (Majunga), and Marovoay. The analysis spans three distinct historical periods, each influenced by different international contexts: the post-1945 French colonial rule (1945-1960), the post-colonial period (1960-1991), and the post-Cold War era (since 1991). 
The data covers a range of topics across scales, including the identities and interests of the actors involved, their repertoires of action, accommodation policies or initiatives aimed at conflict resolution, the roles and influence of international/external institutions and actors, and local institutions (both formal and informal). Furthermore, it examines the cultural, political, and economic dimensions of conflicts. Through this comprehensive analysis, the study aims to enhance our understanding of how hybridisation processes influence conflict trajectories in Madagascar, providing valuable insights for future policy development and conflict resolution strategies.
DOI: 10.15468/dl.9ubt68
title: Occurrence Download

description: A dataset containing 15505 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Larix decidua var. decidua)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 15505 records from 86 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035613-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12819136
title: Smart Energy Systems: A Survey on Explainability

description: The dataset contains the responses from a survey titled "Smart Energy Systems: A Survey on Explainability," which was conducted among members of Austrian Energy Communities, specifically targeting the Renewable Energy Communities. The primary objective of the survey was to gather insights into user interactions with smart energy systems, focusing on their expectations, requirements, and the importance of explainability in these systems. Notably, the dataset is presented in German.
DOI: 10.5281/zenodo.12819137
title: Smart Energy Systems: A Survey on Explainability

description: The dataset contains the responses from a survey titled "Smart Energy Systems: A Survey on Explainability," which was conducted among members of Austrian Energy Communities, specifically targeting the Renewable Energy Communities. The primary objective of the survey was to gather insights into user interactions with smart energy systems, focusing on their expectations, requirements, and the importance of explainability in these systems. Notably, the dataset is presented in German.
DOI: 10.15468/dl.523n9u
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Larix decidua x kaempferi)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 61 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035614-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jja63d
title: Occurrence Download

description: A dataset containing 651 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Larra bicolor Fabricius, 1804)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 651 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035615-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rpu5f7
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Larra polita luzonensis Rohwer, 1919)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035617-240626123714530/datasets/export for details.
DOI: 10.15468/dl.jtx4fr
title: Occurrence Download

description: A dataset containing 1776 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Bats of Bukit Barisan Selatan Landscape, Sumatra, Indonesia"
 ]
}

 The dataset includes 1776 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035616-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.12819183
title: MS data linked to manuscript: https://doi.org/10.1038/s41598-023-43300-w
DOI: 10.5281/zenodo.12819184
title: MS data linked to manuscript: https://doi.org/10.1038/s41598-023-43300-w
DOI: 10.15468/dl.df38u8
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Laser archangelica (Wulfen) Spalik & Wojew.)",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "HasGeospatialIssue is false",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Specimen)"
 ]
 }
 }
 ]
}

 The dataset includes 13 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035618-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.r7vsg3
title: Occurrence Download

description: A dataset containing 208 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Fairy moths of the genus Nemophora Hoffmannsegg, 1798 (Lepidoptera: Adelidae) of India and Sri Lanka"
 ]
}

 The dataset includes 208 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0035619-240626123714530/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.10884503
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-11-01/2022-12-31): Spectral indices

description: Data information
        
This dataset includes widely used indices for 2022-11-01/2022-12-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!
DOI: 10.5281/zenodo.10884504
title: Landsat-based Spectral Indices for pan-EU 2000-2022 - Bimonthly predictor (2022-11-01/2022-12-31): Spectral indices

description: Data information
        
This dataset includes widely used indices for 2022-11-01/2022-12-31. It covers key aspects such as vegetation, crops, soil, and water, available bimonthly (i.e. one value per two months).
        

            
Normalized Difference Vegetation Index (NDVI) is used to evaluate vegetation health and biomass. It is calculated as (nir - red) / (nir + red) (Tucker, 1979).
            
Normalized Difference Tillage Index (NDTI), also known as Normalized Burn Ratio 2 (NBR2), used in tillage detection, post-fire recovery studies, and soil sealing identification. It is calculated as (swir1 - swir2) / (swir1 + swir2) (Van Deventer et al., 1997).
            
Soil Adjusted Vegetation Index (SAVI) is more effective in areas with sparse vegetation by minimizing the impact of soil brightness on vegetation sensing. It is calculated as ((nir - red) / (nir + red + 0.5)) * 1.5 (Huete, 1988).
            
Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) provides a more direct measurement of plant productivity. It is calculated as ((ndvi - 0.03) * (0.95 - 0.001)) / (0.96 - 0.03) + 0.001 (Robinson et al., 2018).
            
Normalized Difference Water Index (NDWI) provides insights into water dynamics and climatic characteristics. It is calculated as (nir - swir1) / (nir + swir1) (Gao, 1996).
            
Normalized Difference Snow Index (NDSI) helps identify snowy areas. It is calculated as (green - swir1) / (green + swir1) (Salomonson and Appel, 2006).
        
        
As a part of a Data Cube
        
This data represents a subset of the Time-series of Landsat-based Spectral Indices (EU, 30m) data cube. For a comprehensive overview and full dataset information, please visit the landing page of this data cube using the provided link.
        

            
To cite this dataset, refer to the DOI available on the landing page.
            
To access other data layers in the data cube, use the navigation catalog on the landing page as well.
        
        
Support
        
If you discover a bug, artifact, or inconsistency, or if you have a question, please raise a Github Issue!