cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.bbifd8
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048759-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y5f6yp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is Données Faune Base SIRFF - FNE Centre-Val de Loire - Système d’Information Régional sur la Faune et la Flore - FNE Centre-Val de Loire - Données 2016",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219966-230224095556074/datasets/export for details.
DOI: 10.15468/dl.v9f6tw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is Macro-invertebrates of the Desna river basin",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219972-230224095556074/datasets/export for details.
DOI: 10.15468/dl.q3spub
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is Amphipoda of Desna river basin",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219974-230224095556074/datasets/export for details.
DOI: 10.15468/dl.eyrdyq
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 32 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003315-180824113759888/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5xp6cr
title: Occurrence Download

description: A dataset containing 658 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is Estonian Naturalists’ Society",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 658 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219971-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lqjvor
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006998-160803222355964/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jhpnwb
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Bryozoa",
 "DatasetKey is Weser und Weseraue bei Höxter, Godelheim und Boffzen",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Geometry POLYGON ((-25.03991 31.75, 41.65954 31.75, 41.65954 71.53037, -25.03991 71.53037, -25.03991 31.75))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0219976-230224095556074/datasets/export for details.
DOI: 10.15468/dl.ubmz7u
title: Occurrence Download

description: A dataset containing 8 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is (Table 1) Proportion of Toxoplasma gondii seropositive arctic foxes (Alopex lagopus) by age group and geographic area"
 ]
}

 The dataset includes 8 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016866-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rxo7oh
title: Occurrence Download

description: A dataset containing 921526716 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 921526716 records from 17585 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0047117-180508205500799/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15159/phytop.148
title: Reservoirs for Tallinn water supply

description: Phytoplankton biomass, diversity and abundance in samples collected from reservoirs for Tallinn water supply during the period 1956-1995.
DOI: 10.15468/dl.zqjjv4
title: Occurrence Download

description: A dataset containing 58832 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cajanus cajan (L.) Huth"
 ]
}

 The dataset includes 58832 records from 507 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016005-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/rnmij0
title: Replication Materials for Mixed Signals

description: This dataset contains all the variables necessary to replicate the analyses in our article, "Mixed Signals? Rethinking How Ideology and Institutional Motivations Shape the Solicitor General’s Positions," which is forthcoming from Political Research Quarterly
DOI: 10.5281/zenodo.15497764
title: Long-lasting cardiovascular responses to gestation at high-altitude: Lessons from a sheep model - Supplementary Data

description: Data from Figures 1–5 and Table 1 in Long-lasting cardiovascular responses to gestation at high-altitude: Lessons from a sheep model. 

 

Figure 1: Femoral blood flow (FBF), carotid blood flow (CBF), heart rate (HR), and mean systemic artery pressure (mSAP) in low-altitude (LA) and high-altitude (HA) gestated lamb fetuses during hypoxia and recovery.

Figure 2: Heart rate (HR), pulmonary artery pressure (PAP), pulmonary artery PO₂ (PO₂ Apulm), and aortic PO₂ (PO₂ AAorta) in LA and HA newborn lambs.

Figure 3: Mean pulmonary arterial pressure (mPAP) in newborn lambs treated with either vehicle or sildenafil and exposed to hypoxia and recovery.

Figure 4: Heart rate (HR), mean pulmonary arterial pressure (mPAP), and mean systemic artery pressure (mSAP) in adult sheep gestated at LA and HA during hypoxia and recovery.

Figure 5: Heart rate (HR), mean pulmonary arterial pressure (mPAP), and mean systemic artery pressure (mSAP) in fetal, newborn, and adult lambs exposed to LA and HA conditions.

Table 1: Weights of body, brain, heart, liver, adrenals, and placenta+uterus in fetal lambs exposed to LA and HA gestation.
DOI: 10.5281/zenodo.15497765
title: Long-lasting cardiovascular responses to gestation at high-altitude: Lessons from a sheep model - Supplementary Data

description: Data from Figures 1–5 and Table 1 in Long-lasting cardiovascular responses to gestation at high-altitude: Lessons from a sheep model. 

 

Figure 1: Femoral blood flow (FBF), carotid blood flow (CBF), heart rate (HR), and mean systemic artery pressure (mSAP) in low-altitude (LA) and high-altitude (HA) gestated lamb fetuses during hypoxia and recovery.

Figure 2: Heart rate (HR), pulmonary artery pressure (PAP), pulmonary artery PO₂ (PO₂ Apulm), and aortic PO₂ (PO₂ AAorta) in LA and HA newborn lambs.

Figure 3: Mean pulmonary arterial pressure (mPAP) in newborn lambs treated with either vehicle or sildenafil and exposed to hypoxia and recovery.

Figure 4: Heart rate (HR), mean pulmonary arterial pressure (mPAP), and mean systemic artery pressure (mSAP) in adult sheep gestated at LA and HA during hypoxia and recovery.

Figure 5: Heart rate (HR), mean pulmonary arterial pressure (mPAP), and mean systemic artery pressure (mSAP) in fetal, newborn, and adult lambs exposed to LA and HA conditions.

Table 1: Weights of body, brain, heart, liver, adrenals, and placenta+uterus in fetal lambs exposed to LA and HA gestation.
DOI: 10.34740/kaggle/dsv/11925760
title: Brazilian and the quest for UNSC reform - data
DOI: 10.5281/zenodo.15499056
title: TABLE 1 in Madagascar, the real Treasure Island! Malagasy uncharted diversity of a rare ancient lineage of armored harvestmen (Opiliones, Laniatores, Buemarinoidae)

description: TABLE 1. — Measurement in mm of appendages of Flavonuncia Lawrence, 1959 species: HT, holotype; BL, body length; CL, carapace max length; SL, scutum max length; CW, carapace max width; SW, scutum max width; Tr, trochanter; Fe, femur; Pa, patella; Ti, tibia; Ta, tarsus; Ca, claw.
BodyPedipalpLeg ILeg IILeg IIILeg IVSspeciesSexVoucherBLCLSLCWSWTrFePaTiTaCaTrFePaTiTaCaSexVoucherTrFePaTiTaCaTrFePaTiTaCaTrFePaTiTaCaF. mahaka n. sp.♂ HT2165020.491.40.851.100.260.670.510.640.600.160.210.680.270.400.530.35♂ HT216500.210.900.300.670.640.610.200.630.260.540.640.380.200.860.310.600.870.35F. mahaka n. sp.♀90720501.530.490.870.761.000.150.500.300.330.390.190.140.560.250.350.420.34♀90720500.150.690.310.600.590.610.160.540.230.450.540.370.210.700.300.640.780.47F. ubicki n. sp.♂ HT216492.840.691.841.211.420.241.010.660.900.800.300.220.970.380.660.850.50♂ HT216490.291.360.501.111.360.950.251.050.350.861.080.560.291.220.501.101.460.79F. ubicki n. sp.♀90720452.320.71.391.061.320.210.750.470.560.640.250.220.880.350.700.880.57♀90720450.241.030.450.941.070.770.240.840.340.740.930.540.281.120.400.871.220.54F. vazimba n. sp.♂ HT216512.180.511.060.791.040.160.630.410.520.500.200.170.700.280.450.500.39♂ HT216510.180.730.340.640.640.560.190.680.310.570.640.390.200.830.360.700.960.41F. vazimba n. sp.♀90721471.780.430.930.690.960.130.500.280.410.380.110.140.550.210.560.530.46♀90721470.150.570.240.460.610.630.130.630.320.550.470.330.150.760.270.600.780.39F. zanahary n. sp.♂ HT216521.350.390.830.60.750.100.360.260.300.350.120.100.410.180.320.290.29♂ HT216520.120.580.220.430.400.490.130.420.170.350.420.320.140.550.220.460.550.40F. zanahary n. sp.♀90721521.40.440.70.610.800.130.390.240.290.300.100.100.450.210.300.290.29♀90721520.140.530.260.430.380.510.140.450.180.380.380.340.160.540.180.440.560.37F. pupilla♂90720472.450.551.160.931.160.180.640.440.530.470.260.200.640.270.410.510.41♂90720470.200.800.390.630.690.570.190.590.310.520.590.410.200.740.360.610.770.50F. pupilla♀90720472.380.560.940.821.120.180.620.280.430.480.170.150.640.250.400.470.39♀90720470.200.790.340.610.660.640.190.660.290.470.610.430.240.820.320.630.870.49
description: Published as part of Abel, Willians Porto & Pérez-González, Abel, 2025, Madagascar, the real Treasure Island! Malagasy uncharted diversity of a rare ancient lineage of armored harvestmen (Opiliones, Laniatores, Buemarinoidae), pp. 207 in Zoosystema 47 (14) on page 207, DOI: 10.5252/zoosystema2025v47a14, http://zenodo.org/record/15430562
DOI: 10.5281/zenodo.15494205
title: Data set on information quality for 'Mapping the quality  of German language health information on the treatment of knee osteoarthritis - a cross-sectional analysis'

description: This dataset is part of the publication ‘Mapping the quality of German language health information on the treatment of knee osteoarthritis - a cross-sectional analysis’ and contains the information quality ratings, assessed using the MAPPinfo checklist.
DOI: 10.5281/zenodo.15498820
title: AF2_fragments
DOI: 10.5281/zenodo.15498821
title: AF2_fragments
DOI: 10.5281/zenodo.15499071
title: Sapag et al - Whale sightings data
DOI: 10.5281/zenodo.15499072
title: Sapag et al - Whale sightings data
DOI: 10.5281/zenodo.15497558
title: Replication package for stress multimodal study

description: This is the replication package for a stress monitoring multimodal study. It contains only quantitative data. Interview data is not included due to sensitive information and to protect our participants information.
DOI: 10.5281/zenodo.15497559
title: Replication package for stress multimodal study

description: This is the replication package for a stress monitoring multimodal study. It contains only quantitative data. Interview data is not included due to sensitive information and to protect our participants information.
DOI: 10.6084/m9.figshare.28832102.v1
title: Technical and deployable rooftop solar potential across China

description: Data and code for "Shi et.al From technical to deployable: unveiling high-resolution deployable rooftop solar potential across cities in China"
DOI: 10.6084/m9.figshare.28832102
title: Technical and deployable rooftop solar potential across China

description: Data and code for "Shi et.al From technical to deployable: unveiling high-resolution deployable rooftop solar potential across cities in China"
DOI: 10.5281/zenodo.14020182
title: Data for "Breaking the Paywall: The role of Open Journal System as key Open Science infrastructure"

description: Context

This research was conducted within the NSF-SEEKCommons Project, a research initiative dedicated to supporting Open Science and Open Access in disciplinary research. The project has a special interest in understanding the role that critical infrastructure has in supporting open initiatives. The Open Journal System (OJS) serves as a long-standing fundamental piece for Open Access throughout the globe. Hence, it provides valuable information about experiences developing, deploying, and maintaining open technologies. 

Methods



We used mixed methods for our research, triangulating repository data, installation data, interviews, and documentary analysis. We collected repository data using a report generator (Kopp [2018] 2024) that uses repository metadata to present general statistics about a Git project. The resulting information was manually curated, disambiguated, and annotated to have a homogeneous set of developers with information about their institutional affiliation and country. 

 

Names are normalized based on the information in qualitative interviews and by browsing the full-extent commits in the GitHub repository. Other sources for this were the institutional materials (available in current and archived versions of the PKP website), meeting minutes, the user forum, and further project documentation available online. GitHub handles are homologated to their most comprehensive version. For institutional and country affiliation, we resorted to GitHub profiles, PKP documentation and forums, institutional domains available in emails, and researchers' ORCID IDs. 


Available files



Information about the codebase (number of files, lines of code, and timestamp) organized by month, quarter, and semester. See file: OJS_GitStats_04-24.csv

Information about the historical evolution of the codebase (number of files, lines of code, and timestamp), including a description of the top committers for each month. Commiters are described by including their institutional affiliation and country of origin. See file: OJS_DevStats_Institution-Country_1.tsv

Information about the historical evolution of the codebase focusing on top committers, along with their institution and country. This file is formatted to map the co-occurrence of developers and attributes by month between 2004-2024.See file: OJS_DevStats_Institution-Country_2.tsv

Selected fields to describe working and regularly maintained plugins for OJS as of October 2024. Includes name of the plugin, homepage, description, maintainer, and institutional affiliation. See file: OJS_Plugins_2024_Processed.tsv

Details of the aggregated information included in Table 5 of the article.See file: OJS_Plugins_2024_Table5.tsv

Snapshot to XML information of the plugin gallery of OJS (October 21) retrieved from PKP website (Smecher 2024)See file: OJS_Plugins_2024.csv


Funding

The SEEKCommons Project is funded by the U.S. National Science Foundation (NSF), grant #2226425
DOI: 10.5281/zenodo.14020183
title: Data for "Breaking the Paywall: The role of Open Journal System as key Open Science infrastructure"

description: Context

This research was conducted within the NSF-SEEKCommons Project, a research initiative dedicated to supporting Open Science and Open Access in disciplinary research. The project has a special interest in understanding the role that critical infrastructure has in supporting open initiatives. The Open Journal System (OJS) serves as a long-standing fundamental piece for Open Access throughout the globe. Hence, it provides valuable information about experiences developing, deploying, and maintaining open technologies. 

Methods



We used mixed methods for our research, triangulating repository data, installation data, interviews, and documentary analysis. We collected repository data using a report generator (Kopp [2018] 2024) that uses repository metadata to present general statistics about a Git project. The resulting information was manually curated, disambiguated, and annotated to have a homogeneous set of developers with information about their institutional affiliation and country. 

 

Names are normalized based on the information in qualitative interviews and by browsing the full-extent commits in the GitHub repository. Other sources for this were the institutional materials (available in current and archived versions of the PKP website), meeting minutes, the user forum, and further project documentation available online. GitHub handles are homologated to their most comprehensive version. For institutional and country affiliation, we resorted to GitHub profiles, PKP documentation and forums, institutional domains available in emails, and researchers' ORCID IDs. 


Available files



Information about the codebase (number of files, lines of code, and timestamp) organized by month, quarter, and semester. See file: OJS_GitStats_04-24.csv

Information about the historical evolution of the codebase (number of files, lines of code, and timestamp), including a description of the top committers for each month. Commiters are described by including their institutional affiliation and country of origin. See file: OJS_DevStats_Institution-Country_1.tsv

Information about the historical evolution of the codebase focusing on top committers, along with their institution and country. This file is formatted to map the co-occurrence of developers and attributes by month between 2004-2024.See file: OJS_DevStats_Institution-Country_2.tsv

Selected fields to describe working and regularly maintained plugins for OJS as of October 2024. Includes name of the plugin, homepage, description, maintainer, and institutional affiliation. See file: OJS_Plugins_2024_Processed.tsv

Details of the aggregated information included in Table 5 of the article.See file: OJS_Plugins_2024_Table5.tsv

Snapshot to XML information of the plugin gallery of OJS (October 21) retrieved from PKP website (Smecher 2024)See file: OJS_Plugins_2024.csv


Funding

The SEEKCommons Project is funded by the U.S. National Science Foundation (NSF), grant #2226425
DOI: 10.15468/dl.xsuqyr
title: Occurrence Download

description: A dataset containing 1515 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Fossil",
 "OccurrenceStatus is Present",
 "TaxonKey is Gopherus Rafinesque, 1832"
 ]
}

 The dataset includes 1515 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016010-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mc9nwp
title: Occurrence Download

description: A dataset containing 14508 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is Premna L."
 ]
}

 The dataset includes 14508 records from 247 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016009-250515123054153/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.29139464
title: Contiguous U.S. Daily PM<sub>2.5</sub> Measurements (2021) – Benchmark Dataset for Location‑Encoder Evaluation

description: Deep learning models have demonstrated success in geospatial applications, yet quantifying the role of geolocation information in enhancing model performance and geographic generalizability remains underexplored. A new generation of location encoders have emerged with the goal of capturing attributes present at any given location for downstream use in predictive modeling. Being a nascent area of research, their evaluation has remained largely limited to static tasks such as species distributions or average temperature mapping. In this paper, we discuss and quantify the impact of incorporating geolocation into deep learning for a real-world application domain that is characteristically dynamic (with fast temporal change) and spatially heterogeneous at high resolutions: estimating surface-level daily PM<sub>2.5</sub> levels using remotely sensed and ground-level data. We build on a recently published deep learning-based PM<sub>2.5</sub> estimation model that achieves state-of-the-art performance on data observed in the contiguous United States. We examine three approaches for incorporating geolocation: excluding geolocation as a baseline, using raw geographic coordinates, and leveraging pretrained location encoders. We evaluate each approach under within-region (WR) and out-of-region (OoR) evaluation scenarios. Aggregate performance metrics indicate that while naïve incorporation of raw geographic coordinates improves within-region performance by retaining the interpolative value of geographic location, it can hinder generalizability across regions. In contrast, pretrained location encoders like GeoCLIP enhance predictive performance and geographic generalizability for both WR and OoR scenarios. However, our qualitative analysis reveals artifact patterns caused by high-degree basis functions and sparse upstream samples in certain areas, and our ablation results indicate varying performance among location encoders such as SatCLIP vs. GeoCLIP. To the best of our knowledge, this is a first integration and systematic evaluation of location encoders in a complex, temporally dynamic estimation scenario. In addition to guiding better model development for air pollution estimation and location encoders, this study provides insights for effective incorporation of location into deep learning for geospatial predictive tasks.