cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.5qkcvk
title: Occurrence Download

description: A dataset containing 23350 species occurrences available in GBIF matching the query:
{
 "and" : [
 "EstablishmentMeans is INTRODUCED",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Actinopterygii"
 ]
}

 The dataset includes 23350 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0227262-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6mg5mi
title: Occurrence Download

description: A dataset containing 1215 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Year 2000-2018",
 "HasCoordinate is true",
 "TaxonKey is Bombus distinguendus Morawitz, 1869",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 1215 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010624-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fe7zbb
title: Occurrence Download

description: A dataset containing 1195 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rosa ×nitidula Besser",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1195 records from 30 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0300087-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cscxz9
title: Occurrence Download

description: A dataset containing 5192 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Setophaga petechia (Linnaeus, 1766)",
 "Year 2011-2018"
 ]
}

 The dataset includes 5192 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0242007-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25582/data.2023-05.2816975/2367861
title: Data for EMSL Project 51287 from May 2023
DOI: 10.25582/data.2023-05.2816714/2367862
title: Data for EMSL Project 51287 from May 2023
DOI: 10.15468/dl.kpzy3h
title: Occurrence Download

description: A dataset containing 1834 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON ((6.875 53.175,6.925 53.175,6.925 53.225,6.875 53.225,6.875 53.175))",
 "DatasetKey is Observation.org, Nature data from around the World",
 "TaxonKey is Animalia"
 ]
}

 The dataset includes 1834 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0307941-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.y9t895
title: Occurrence Download

description: A dataset containing 22120 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sceloporus grammicus Wiegmann, 1828"
 ]
}

 The dataset includes 22120 records from 97 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0265075-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.89cuqq
title: Occurrence Download

description: A dataset containing 1707 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Streptanthus glandulosus Hook."
 ]
}

 The dataset includes 1707 records from 53 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0233563-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kgelea
title: Occurrence Download

description: A dataset containing 3115 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Abelmoschus esculentus (L.) Moench",
 "HasCoordinate is TRUE"
 ]
}

 The dataset includes 3115 records from 107 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0010624-180412121330197/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rceqzg
title: Occurrence Download

description: A dataset containing 638735 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Bromeliaceae"
 ]
}

 The dataset includes 638735 records from 1201 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0050772-240506114902167/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nzazbe
title: Occurrence Download

description: A dataset containing 880447616 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 880447616 records from 15918 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002277-180131172636756/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.p7qchy
title: Occurrence Download

description: A dataset containing 25412 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lasioglossum leucozonium (Schrank, 1781)",
 "HasCoordinate is true"
 ]
}

 The dataset includes 25412 records from 271 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005911-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.58d2nh
title: Occurrence Download

description: A dataset containing 87840 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Aulacorhynchus prasinus (Gould, 1833)"
 ]
}

 The dataset includes 87840 records from 194 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005897-250402121839773/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34810/data2237
title: Exposure of industrial chemicals

description: Exposure data of different falimies of industrial chemical contaminants including: organophosphate esters, benzothiazoles,benzosulfonamides, phthalate esters and benzotriazoles. One file for family of contaminants. The exposure data is also organised by type of population.
description: Exposure values to calculate the risk derived from consumption of fish species contaminated with the family of contaminants: 


- organophosphate esters

- benzothiazoles

- benzosulfonamides

- phthalate esters

- benzotriazoles
DOI: 10.15468/dl.xy76uc
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OrderKey is Aves",
 "OccurrenceStatus is Present",
 "HasCoordinate is true",
 "Country is Italy",
 "Year is greater than or equal to 2000"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008158-251025141854904/datasets/export for details.
DOI: 10.7910/dvn/1b5kf1
title: Replication data for: A Cold Shower for the Hot Hand Fallacy: Robust Evidence from Controlled Settings

description: Miller, Joshua B., and Sanjurjo, Adam, (2024) “A Cold Shower for the Hot Hand Fallacy: Robust Evidence from Controlled Settings.” Review of Economics and Statistics 106:6, 1607–1619.
description: Volume XX, Issue X
DOI: 10.5281/zenodo.18435282
title: Replication Data: Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud

description: Replication data for the paper titled Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud presented at the 8th International Workshop on Recent Advances for Multi-Clouds and Mobile Edge Computing (M2EC 2026) held in conjunction with the 40th International Conference on Advanced Information Networking and Applications (AINA 2026). April 8-10, 2026 in Wellington, New Zealand. 

Table 2: P99 Tail Latency by Cloud Region and Client Location

Note: The measurement at (9388, Fjordgård) was conducted over an optical fiber connection rather than 5G.




Location
Metric
SE-Central
NO-East
NO-West
Edge / MEC




9131, Kårvik
Number of measurements
71972
72411
72172
-


Overall P99 (ms)
677.35
662.59
672.25
-


Mean hourly P99 (ms)
664.14
650.38
657.49
-


Max hourly P99 (ms)
1082.88
994.31
1006.69
-


P99 volatility (CV)
0.215
0.192
0.203
-


9019, Tromsø
Number of measurements
80342
81290
81287
-


Overall P99 (ms)
111.45
83.98
84.52
-


Mean hourly P99 (ms)
101.54
76.34
77.04
-


Max hourly P99 (ms)
121.23
91.69
92.37
-


P99 volatility (CV)
0.132
0.099
0.089
-


0366, Oslo
Number of measurements
82233
82885
82882
-


Overall P99 (ms)
85.64
58.45
58.55
-


Mean hourly P99 (ms)
75.26
56.48
55.52
-


Max hourly P99 (ms)
97.49
65.34
62.57
-


P99 volatility (CV)
0.201
0.056
0.055
-


1360, Fornebu
Number of measurements
81292
81789
82046
82078


Overall P99 (ms)
78.49
47.69
48.80
44.62


Mean hourly P99 (ms)
75.36
47.74
47.93
44.83


Max hourly P99 (ms)
83.07
50.66
55.46
46.41


P99 volatility (CV)
0.088
0.028
0.075
0.021


9388, Fjordgård
Number of measurements
82829
83430
82922
-


Overall P99 (ms)
47.75
36.71
43.94
-


Mean hourly P99 (ms)
47.75
36.72
43.85
-


Max hourly P99 (ms)
65.19
39.03
47.11
-


P99 volatility (CV)
0.082
0.018
0.027
-
DOI: 10.5281/zenodo.18435283
title: Replication Data: Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud

description: Replication data for the paper titled Evaluating 5G-connected IoT for Power Line Temperature Prediction: Real-World Latency and Cost Trade-offs Between MEC and Cloud presented at the 8th International Workshop on Recent Advances for Multi-Clouds and Mobile Edge Computing (M2EC 2026) held in conjunction with the 40th International Conference on Advanced Information Networking and Applications (AINA 2026). April 8-10, 2026 in Wellington, New Zealand. 

Table 2: P99 Tail Latency by Cloud Region and Client Location

Note: The measurement at (9388, Fjordgård) was conducted over an optical fiber connection rather than 5G.




Location
Metric
SE-Central
NO-East
NO-West
Edge / MEC




9131, Kårvik
Number of measurements
71972
72411
72172
-


Overall P99 (ms)
677.35
662.59
672.25
-


Mean hourly P99 (ms)
664.14
650.38
657.49
-


Max hourly P99 (ms)
1082.88
994.31
1006.69
-


P99 volatility (CV)
0.215
0.192
0.203
-


9019, Tromsø
Number of measurements
80342
81290
81287
-


Overall P99 (ms)
111.45
83.98
84.52
-


Mean hourly P99 (ms)
101.54
76.34
77.04
-


Max hourly P99 (ms)
121.23
91.69
92.37
-


P99 volatility (CV)
0.132
0.099
0.089
-


0366, Oslo
Number of measurements
82233
82885
82882
-


Overall P99 (ms)
85.64
58.45
58.55
-


Mean hourly P99 (ms)
75.26
56.48
55.52
-


Max hourly P99 (ms)
97.49
65.34
62.57
-


P99 volatility (CV)
0.201
0.056
0.055
-


1360, Fornebu
Number of measurements
81292
81789
82046
82078


Overall P99 (ms)
78.49
47.69
48.80
44.62


Mean hourly P99 (ms)
75.36
47.74
47.93
44.83


Max hourly P99 (ms)
83.07
50.66
55.46
46.41


P99 volatility (CV)
0.088
0.028
0.075
0.021


9388, Fjordgård
Number of measurements
82829
83430
82922
-


Overall P99 (ms)
47.75
36.71
43.94
-


Mean hourly P99 (ms)
47.75
36.72
43.85
-


Max hourly P99 (ms)
65.19
39.03
47.11
-


P99 volatility (CV)
0.082
0.018
0.027
-
DOI: 10.6084/m9.figshare.31159464
title: Volatile gas exposure correlates with self-reported liver condition: insights from NHANES 2009–2018 and Mendelian randomization studies

description: Volatile gas exposure and self-reported liver conditions share pathophysiologic risk factors, but their exact association remains unclear. We used a weighted multivariable-adjusted logistic regression model, using data from the National Health and Nutrition Examination Survey (NHANES) 2009–2018. Integrative analyses of Non-alcoholic fatty liver disease (NAFLD), liver fibrosis, liver cirrhosis GWAS summaries and blood expression quantitative trait loci (eQTLs) were conducted via summary data-based MR (SMR) and colocalization analysis to prioritize putative blood smoking-related genes and their associations with each liver condition risk. Finally, we further verified these gene-disease causal links through MR and colocalization analysis. 12,099 NHANES participants were included. Male sex, 46–75 years, and smoke exposure correlated positively with LC; age and smoke exposure remained positively associated with LC incidence after adjustment, while non-Hispanic Black was a LC protective factor. SMR identified three blood-derived candidate genes: RGPD8 (Beta = −0.207), COX6B2 (Beta = −0.567), DNAJC27 (Beta = 0.859). MR and colocalization confirmed their associations with cirrhosis, fibrosis, and NAFLD, respectively. This study confirms a causal link between smoke exposure and increased LC risk, identifies novel gene-disease associations, and provides cross-disciplinary insights for targeted LC prevention and personalized research. This study confirms smoke exposure as a causal risk for self-reported liver conditions (LC). It reinforces smoking cessation as a critical clinical strategy for liver health, while the candidate genes offer potential targets for high-risk screening and personalized interventions, aiding clinical prevention and management of liver diseases.
DOI: 10.6084/m9.figshare.31159464.v1
title: Volatile gas exposure correlates with self-reported liver condition: Insights from NHANES 2009-2018 and Mendelian Randomization studies

description: Volatile gas exposure (VGE) and self-reported liver conditions (LC) share pathophysiologic risk factors, but their exact association remains unclear. We used a weighted multivariable-adjusted logistic regression model, using data from the National Health and Nutrition Examination Survey (NHANES) 2009-2018. Integrative analyses of Non-alcoholic fatty liver disease (NAFLD), liver fibrosis, liver cirrhosis GWAS summaries and blood expression quantitative trait loci (eQTLs) were conducted via summary data-based MR (SMR) and colocalization analysis to prioritize putative blood smoking-related genes and their associations with each liver conditions risk. Finally, we further verified these gene-disease causal links through MR and colocalization analysis. 12,099 NHANES participants were included. Male sex, 46-75 years, and smoke exposure correlated positively with LC; age and smoke exposure remained positively associated with LC incidence after adjustment, while non-Hispanic Black was a LC protective factor. SMR identified three blood-derived candidate genes: RGPD8 (Beta=-0.207), COX6B2 (Beta=-0.567), DNAJC27 (Beta = 0.859). MR and colocalization confirmed their associations with cirrhosis, fibrosis, and NAFLD, respectively. This study confirms a causal link between smoke exposure and increased LC risk, identifies novel gene-disease associations, and provides cross-disciplinary insights for targeted LC prevention and personalized research. This study confirms smoke exposure as a causal risk for self-reported liver conditions (LC). It reinforces smoking cessation as a critical clinical strategy for liver health, while the candidate genes offer potential targets for high-risk screening and personalized interventions, aiding clinical prevention and management of liver diseases.
DOI: 10.6084/m9.figshare.31159464.v2
title: Volatile gas exposure correlates with self-reported liver condition: insights from NHANES 2009–2018 and Mendelian randomization studies

description: Volatile gas exposure and self-reported liver conditions share pathophysiologic risk factors, but their exact association remains unclear. We used a weighted multivariable-adjusted logistic regression model, using data from the National Health and Nutrition Examination Survey (NHANES) 2009–2018. Integrative analyses of Non-alcoholic fatty liver disease (NAFLD), liver fibrosis, liver cirrhosis GWAS summaries and blood expression quantitative trait loci (eQTLs) were conducted via summary data-based MR (SMR) and colocalization analysis to prioritize putative blood smoking-related genes and their associations with each liver condition risk. Finally, we further verified these gene-disease causal links through MR and colocalization analysis. 12,099 NHANES participants were included. Male sex, 46–75 years, and smoke exposure correlated positively with LC; age and smoke exposure remained positively associated with LC incidence after adjustment, while non-Hispanic Black was a LC protective factor. SMR identified three blood-derived candidate genes: RGPD8 (Beta = −0.207), COX6B2 (Beta = −0.567), DNAJC27 (Beta = 0.859). MR and colocalization confirmed their associations with cirrhosis, fibrosis, and NAFLD, respectively. This study confirms a causal link between smoke exposure and increased LC risk, identifies novel gene-disease associations, and provides cross-disciplinary insights for targeted LC prevention and personalized research. This study confirms smoke exposure as a causal risk for self-reported liver conditions (LC). It reinforces smoking cessation as a critical clinical strategy for liver health, while the candidate genes offer potential targets for high-risk screening and personalized interventions, aiding clinical prevention and management of liver diseases.
DOI: 10.6084/m9.figshare.29799967
title: Facilitating public scrutiny of EIA reports with open data and artificial intelligence: insights from a Mexican case study

description: Public scrutiny is a cornerstone of Environmental Impact Assessment (EIA), yet their technical complexity methods often limits the ability of stakeholders to meaningfully review EIA reports. This paper introduces a practical approach that integrates Open Data (OD), Artificial Intelligence (AI), and comparative analysis of impact significance assessment to evaluate whether key sources of uncertainty are adequately addressed in EIA reports. We apply this approach to the case of the, focusing on a technical-scientific review of an EIA report of Tren Maya, commissioned by Mexican environmental authorities. We demonstrate how our approach can be employed to assess epistemic and ontological uncertainty in biodiversity impact assessments. This approach can identify weaknesses in expert judgments, data quality, and adherence to core EIA principles. Results indicate that the EIA report underestimated biodiversity impacts and exhibited methodological inconsistencies in indicator scoring and aggregation. In general, OD-AI tools supports evidence-based scrutiny under procedural constraints, while comparative analysis highlights the risks of biased or inconsistent judgments in conventional EIA practice. The approach is transparent, operationally accessible, and adaptable to other EIA domains and contexts. OD-AI supports public scrutiny of EIA reports.OD enables efficient appraisal of biodiversity baseline data.AI enables traceable, literature-backed assessments of impact significance.Comparative analysis evaluates compliance of expert judgment with core EIA principles. OD-AI supports public scrutiny of EIA reports. OD enables efficient appraisal of biodiversity baseline data. AI enables traceable, literature-backed assessments of impact significance. Comparative analysis evaluates compliance of expert judgment with core EIA principles.
DOI: 10.6084/m9.figshare.29799967.v1
title: Facilitating public scrutiny of EIA reports with open data and artificial intelligence: insights from a Mexican case study

description: Public scrutiny is a cornerstone of Environmental Impact Assessment (EIA), yet their technical complexity methods often limits the ability of stakeholders to meaningfully review EIA reports. This paper introduces a practical approach that integrates Open Data (OD), Artificial Intelligence (AI), and comparative analysis of impact significance assessment to evaluate whether key sources of uncertainty are adequately addressed in EIA reports. We apply this approach to the case of the, focusing on a technical-scientific review of an EIA report of Tren Maya, commissioned by Mexican environmental authorities. We demonstrate how our approach can be employed to assess epistemic and ontological uncertainty in biodiversity impact assessments. This approach can identify weaknesses in expert judgments, data quality, and adherence to core EIA principles. Results indicate that the EIA report underestimated biodiversity impacts and exhibited methodological inconsistencies in indicator scoring and aggregation. In general, OD-AI tools supports evidence-based scrutiny under procedural constraints, while comparative analysis highlights the risks of biased or inconsistent judgments in conventional EIA practice. The approach is transparent, operationally accessible, and adaptable to other EIA domains and contexts. OD-AI supports public scrutiny of EIA reports.OD enables efficient appraisal of biodiversity baseline data.AI enables traceable, literature-backed assessments of impact significance.Comparative analysis evaluates compliance of expert judgment with core EIA principles. OD-AI supports public scrutiny of EIA reports. OD enables efficient appraisal of biodiversity baseline data. AI enables traceable, literature-backed assessments of impact significance. Comparative analysis evaluates compliance of expert judgment with core EIA principles.
DOI: 10.57710/alba-es-20250370185
title: BAG proposal CIB Margarita Salas

description: The current BAG proposal comprises FOUR research teams based at Centro de Investigaciones Biológicas Margarita Salas of the National Scientific Research Council (CSIC): the Structural Biology of Host-Pathogen Interactions (SBHPI) directed by Dr. Cristina Vega; the Structure of Macromolecular Assemblies (SMA) directed by Dr. Carlos Fernández Tornero; the Cell Signaling and Adhesion (CSA) directed by Dr. Daniel Lietha and; the Physiological and Pharmacological Tubulin Modulation (PPTM) directed by Dr. Marian Oliva.
DOI: 10.7910/dvn/jozdgw
title: Replication Data for: International Development Index (IDX)

description: This dataset contains the 12 indicators that make up the International Development Index (IDX), covering 178 countries from 1998 onwards.
DOI: 10.5281/zenodo.18479011
title: A large-scale geophysics preference dataset for direct preference optimization and reusable scientific explanations
DOI: 10.7910/dvn/jlir4y
title: Replication Package for "How Financial Markets Create Superstars"

description: The replication package contains the code used to generate Figure 2 in the paper.
DOI: 10.5281/zenodo.18479010
title: A large-scale geophysics preference dataset for direct preference optimization and reusable scientific explanations
DOI: 10.3535/r1q-4p0-7nh
title: Mauritia L.f.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/060-y58-pbe
title: Mauritia flexuosa L.f.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/8l1-j7p-r4l
title: Aiphanes horrida (Jacq.) Burret

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.
DOI: 10.3535/zmm-phs-n7h
title: Metroxylon salomonense (Warb.) Becc.

description: Digital Specimen for the physical specimen hosted at Botanic Garden and Botanical Museum Berlin.