cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.baj3tk
title: Occurrence Download

description: A dataset containing 9360169 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is iNaturalist Research-grade Observations",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonId is not null",
 "GbifId is not null",
 "Country is one of (Canada, Mexico, United States of America)",
 "EventDate is greater than or equal to 2022-03-01",
 "EventDate is less than or equal to 2023-03-01",
 {
 "not" : {
 "Issue" : [
 "is one of (Basis of record invalid, Coordinate reprojection failed, Coordinate reprojection suspicious, Coordinate precision invalid, Coordinate uncertainty meters invalid, Country mismatch, Country invalid, Geodetic datum invalid, Presumed swapped coordinate, Presumed negated longitude, Presumed negated latitude, Country coordinate mismatch)"
 ]
 }
 },
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 }
 ]
}

 The dataset includes 9360169 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002028-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18036716
title: Financiamiento de la salud en Chile. 1981–2024

description: VARABLES ORIGINALES  

1 Gasto Público (MM$ corrientes). Dirección de Presupuestos. DIPRES. Ministerio de Hacienda; Fondo Nacional de Salud (FONASA)

2 Gasto Obligatorio Isapres  (MM$ corrientes). Superintendencia de Salud

3 Gasto Privado Isapres  (MM$ corrientes). Superintendencia de Salud

4 Gasto del PIB Ref. 2018 (millones encadenados). Banco Central de Chile

5 Var. PIB real (%). Banco Central de Chile 6 IPC Banco Central de Chile
DOI: 10.5281/zenodo.18036717
title: Financiamiento de la salud en Chile. 1981–2024

description: VARABLES ORIGINALES  

1 Gasto Público (MM$ corrientes). Dirección de Presupuestos. DIPRES. Ministerio de Hacienda; Fondo Nacional de Salud (FONASA)

2 Gasto Obligatorio Isapres  (MM$ corrientes). Superintendencia de Salud

3 Gasto Privado Isapres  (MM$ corrientes). Superintendencia de Salud

4 Gasto del PIB Ref. 2018 (millones encadenados). Banco Central de Chile

5 Var. PIB real (%). Banco Central de Chile 6 IPC Banco Central de Chile
DOI: 10.15468/dl.dydezt
title: Occurrence Download

description: A dataset containing 0 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)"
 ]
 }
 },
 "DistanceFromCentroidInMeters is greater than or equal to 2000",
 "Geometry POLYGON ((105.610544 14.999999, 179.999961 14.999999, 179.999961 65.08290100000001, 105.610544 65.08290100000001, 105.610544 14.999999))",
 "TaxonKey is Lamprologus mocquardi"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002060-260226173443078/datasets/export for details.
DOI: 10.6084/m9.figshare.31430443
title: Mappings of DMP templates to TAPS Responsibility Matrix

description: The proliferation of digital data across various fields has contributed to an increase in data management practices. Data Management Plans (DMPs), as an important policy mechanism for responsible and ethical handling of data, are often structured as a set of questions that are intended to guide researchers in describing their data management practices. As data science evolves, several DMP templates and and frameworks have emerged to address the new complexities of data handling. However, there are still two main limitations with current DMP templates: 1) Lack of standardization: Several initiatives have improved alignment through shared core requirements and evaluation rubrics, but templates still vary in how they elicit responsibility and how clearly questions map to distinct responsibility components.We examined three widely-used DMP templates from the European Union (EU), the Data Curation Center (DCC), and the Dutch Research Council (NWO) using the TAPS (Transparency, Accountability, Privacy / Confidentiality, Societal values) Responsibility Matrix, a framework designed to address components of responsibility for data science. TAPS distinguishes between four main dimensions of responsibility (transparency, accountability, privacy and confidentiality, and social values) and their application to four main scopes ( actors, objects, processes and impacts). We mapped questions from the three DMP templates to the TAPS matrix to understand which aspects of responsibility are covered by the DMP templates.
DOI: 10.6084/m9.figshare.31430443.v1
title: Mappings of DMP templates to TAPS Responsibility Matrix

description: The proliferation of digital data across various fields has contributed to an increase in data management practices. Data Management Plans (DMPs), as an important policy mechanism for responsible and ethical handling of data, are often structured as a set of questions that are intended to guide researchers in describing their data management practices. As data science evolves, several DMP templates and and frameworks have emerged to address the new complexities of data handling. However, there are still two main limitations with current DMP templates: 1) Lack of standardization: Several initiatives have improved alignment through shared core requirements and evaluation rubrics, but templates still vary in how they elicit responsibility and how clearly questions map to distinct responsibility components.We examined three widely-used DMP templates from the European Union (EU), the Data Curation Center (DCC), and the Dutch Research Council (NWO) using the TAPS (Transparency, Accountability, Privacy / Confidentiality, Societal values) Responsibility Matrix, a framework designed to address components of responsibility for data science. TAPS distinguishes between four main dimensions of responsibility (transparency, accountability, privacy and confidentiality, and social values) and their application to four main scopes ( actors, objects, processes and impacts). We mapped questions from the three DMP templates to the TAPS matrix to understand which aspects of responsibility are covered by the DMP templates.
DOI: 10.4121/1c86e644-4ffd-4ab1-a28b-6b33a4c01c4f
title: Data derived sand wave characteristics and migration rates and modelled hydrodynamics across the Dutch Continental Shelf, underlying the publication: "Estimating sand wave migration rates from local hydrodynamics and sediment mobility"

description: This dataset contains an extensive compilation of sand wave and environmental data of over 600,000 datapoints across sand wave fields on the Dutch Continental Shelf (North Sea). It combines observed and model-derived information to quantify sand wave characteristics, migration behaviour, and associated hydrodynamic and sediment transport conditions.<br>The dataset includes:<br>- Sand wave characteristics derived from bathymetric observations- Sand wave migration rates derived from bathymetric observations- Hydrodynamic and sediment transport indicators derived from Dutch Continental Shelf Model simulations- Sediment grain size data - Water depth data<br>This dataset underlies the manuscript:<br>Overes et al. (submitted). Estimating sand wave migration from local hydrodynamics and sediment mobility<br>The dataset includes all data, even data points not used in the above study.The applied filtering based on survey amount/quality and sand wave migration rate verification can be carried out using the included data.
DOI: 10.4121/1c86e644-4ffd-4ab1-a28b-6b33a4c01c4f.v1
title: Data derived sand wave characteristics and migration rates and modelled hydrodynamics across the Dutch Continental Shelf, underlying the publication: "Estimating sand wave migration rates from local hydrodynamics and sediment mobility"

description: This dataset contains an extensive compilation of sand wave and environmental data of over 600,000 datapoints across sand wave fields on the Dutch Continental Shelf (North Sea). It combines observed and model-derived information to quantify sand wave characteristics, migration behaviour, and associated hydrodynamic and sediment transport conditions.<br>The dataset includes:<br>- Sand wave characteristics derived from bathymetric observations- Sand wave migration rates derived from bathymetric observations- Hydrodynamic and sediment transport indicators derived from Dutch Continental Shelf Model simulations- Sediment grain size data - Water depth data<br>This dataset underlies the manuscript:<br>Overes et al. (submitted). Estimating sand wave migration from local hydrodynamics and sediment mobility<br>The dataset includes all data, even data points not used in the above study.The applied filtering based on survey amount/quality and sand wave migration rate verification can be carried out using the included data.
DOI: 10.15468/dl.crcx9c
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is one of (Observation, Human Observation)",
 "Country is one of (Peru, Ecuador)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Anadenanthera colubrina"
 ]
}

 The dataset includes 6 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002063-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.11588/duerer.online.69a191fc12fb1
title: Maria mit Kind, drei Heiligen und musizierenden Engeln, https://d-nb.info/gnd/1197754083
DOI: 10.15468/dl.ggu5ht
title: Occurrence Download

description: A dataset containing 287 records in GBIF matching the query:

SELECT
 GBIF_ISEA3HCode(
 8, 
 decimalLatitude,
 decimalLongitude,
 COALESCE(coordinateUncertaintyInMeters, 1000)
 ) AS geogrid_id,
 CASE 
 WHEN classKey IN ('359') THEN 'Mammals'
 WHEN classKey IN ('212') THEN 'Birds'
 WHEN familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879') THEN 'Bony Fish'
 WHEN classKey IN ('131') THEN 'Amphibians'
 WHEN classKey IN ('216') THEN 'Insects'
 WHEN classKey IN ('11418114', '11569602', '11592253', '11493978') THEN 'Reptiles'
 WHEN phylumKey IN ('52') THEN 'Molluscs'
 WHEN classKey IN ('367') THEN 'Arachnids'
 WHEN classKey IN ('220', '196') THEN 'Flowering Plants'
 WHEN classKey IN ('194', '244', '228', '282') THEN 'Gymnosperms'
 WHEN orderKey IN ('392') THEN 'Ferns'
 WHEN phylumKey IN ('35') THEN 'Mosses'
 WHEN phylumKey IN ('95') THEN 'Sac Fungi'
 WHEN phylumKey IN ('34') THEN 'Basidiomycota'
 END AS taxonomic_group,
 COUNT(DISTINCT speciesKey) AS species_count
FROM occurrence
WHERE countryCode = 'HR'
 AND hasCoordinate = TRUE
 AND hasGeospatialIssues = FALSE
 AND coordinateUncertaintyInMeters &lt;= 2000
 AND occurrenceStatus = 'PRESENT'
 AND speciesKey IS NOT NULL
 AND basisOfRecord != 'FOSSIL_SPECIMEN'
 AND taxonRank = 'SPECIES'
 AND (
 classKey IN ('359', '212', '131', '216', '11418114', '11569602', '11592253', '11493978', '367', '220', '196', '194', '244', '228', '282')
 OR familyKey IN ('1103', '1104', '494', '495', '1105', '496', '497', '1106', '498', '499', '1107', '537', '538', '1153', '547', '1162', '548', '549', '550', '1163', '1164', '1165', '1166', '1167', '1305', '1067', '1306', '1307', '1308', '1068', '1069', '587', '1310', '588', '589', '1311', '1312', '1313', '590', '708', '890', '774', '889', '773', '772', '888', '765', '879')
 OR phylumKey IN ('52', '35', '95', '34')
 OR orderKey IN ('392')
 )
GROUP BY geogrid_id, taxonomic_group;


 The dataset's 287 records were derived from 150 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002048-260226173443078/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25326/591
title: PM Aerosol Mineral Analysis, Katibougou, Mali

description: Weekly integrated aerosol samples are collected using two automatic aerosol samplers specifically designed and developed for the INDAAF program (http://indaaf.obs-mip.fr). Each sampler is equipped with two independent air inlets connected with KNF pumps (N89 KNE-K 220V) operating at a flow rate of 9 L/min, Cole palmer ball flow meters with a micrometric valve (flow range adjustable from 0 to 10 L/min and NILU online filter holders. Each air inlet is surmounted with an aerosol cutting head corresponding to aerodynamic particles diameter. Two mini Partisol low air inlets PM2.5 and PM10 (Rupprecht and Patashnick) operates at a flow rate of 5 L/min and the air volume sample is measured with a GALLUS type G4 gas meter (accuracy ±0.01 m-3) (Ouafo-Luembe et al., 2017; Djoussou et al, 2018). Aerosol samples were collected on 47mm diameter filters on a weekly basis. PTFE or teflon filters were used for to determine mineral compounds. PTFE filters are weighed before and after sampling using a SARTORIUS MCS21 microbalance (1 µg resolution for a maximum range of 21 g - Measuring accuracy of ± 5 µg). For each filter batch preparation, field blanks are included with the samplers sent into the field. Before and after collection, samples and blanks filters are conditioned in petri slides boxes and stored at 4°C. From 2005, we performed PM2.5 or PM10 weekly filter samples analysis at the Laboratoire d’Aérologie (Laero) to determine mineral composition (soluble major ions) using Ion Chromatography (IC). Before this date, weekly bulk aerosol sampling on teflon filters was performed (1998-2005).
DOI: 10.25326/587
title: PM10 Aerosol EC/OC, Mineral and Trace Metals Analysis, Djougou, Benin

description: Weekly integrated aerosol samples are collected using two automatic aerosol samplers specifically designed and developed for the INDAAF program (http://indaaf.obs-mip.fr). Each sampler is equipped with two independent air inlets connected with KNF pumps (N89 KNE-K 220V) operating at a flow rate of 9 L/min, Cole palmer ball flow meters with a micrometric valve (flow range adjustable from 0 to 10 L/min and NILU online filter holders. Each air inlet is surmounted with an aerosol cutting head corresponding to aerodynamic particles diameter. Two mini Partisol low air inlets PM2.5 and PM10 (Rupprecht and Patashnick) operates at a flow rate of 5 L/min and the air volume sample is measured with a GALLUS type G4 gas meter (accuracy ±0.01 m-3) (Ouafo-Luembe et al., 2017; Djoussou et al, 2018). Aerosol samples were collected on 47mm diameter filters on a weekly basis. For each filter batch preparation, field blanks are included with the samplers sent into the field. Before and after collection, samples and blanks filters are conditioned in petri slides boxes and stored at 4°C.

Quartz fiber filters were used for carbonaceous analysis and the determination of Elemental Carbon (EC), Organic Carbon (OC) and Total Carbon (TC). Quartz fiber filters were cleaned by burning at 450°C for 48h before exposition. Weekly filter samples are analyzed at the Laboratoire d’Aérologie (LAERO) of Toulouse using thermo-optical methods. From 2005 to 2018, analysis were performed using the Desert Research Institute (DRI) instrument and the IMPROVE analytical protocol. Since 2018, analysis are performed using the Sunset instrument and the European EUSAAR2 protocol. All analytical results are converted to concentrations (in microgram per cubic meter).

PTFE or teflon filters were used for to determine mineral compounds. PTFE filters are weighed before and after sampling using a SARTORIUS MCS21 microbalance (1 µg resolution for a maximum range of 21 g - Measuring accuracy of ± 5 µg). From 2005, we performed PM2.5 or PM10 weekly filter samples analysis at the Laboratoire d’Aérologie (Laero) to determine mineral composition (soluble major ions) using Ion Chromatography (IC). Before this date, weekly bulk aerosol sampling on teflon filters was performed (1998-2005).

Half Teflon filters samples (PM2.5 and PM10) were analyzed by ICP-MS (7500 ce Agilent technologies) using In and Re as internal standards. Filters are previously mineralized according the method described in Ouafo and Luembe, 2017. 13 trace metals are considered: Al, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Ba, La, Th, Pb and Cd. The detection limit is less than 10 ppt.
DOI: 10.25326/597
title: PM10 EC/OC Analysis, Bambey, Senegal

description: Weekly integrated aerosol samples are collected using two automatic aerosol samplers specifically designed and developed for the INDAAF program (http://indaaf.obs-mip.fr). Each sampler is equipped with two independent air inlets connected with KNF pumps (N89 KNE-K 220V) operating at a flow rate of 9 L/min, Cole palmer ball flow meters with a micrometric valve (flow range adjustable from 0 to 10 L/min and NILU online filter holders. Each air inlet is surmounted with an aerosol cutting head corresponding to aerodynamic particles diameter. Two mini Partisol low air inlets PM2.5 and PM10 (Rupprecht and Patashnick) operates at a flow rate of 5 L/min and the air volume sample is measured with a GALLUS type G4 gas meter (accuracy ±0.01 m-3) (Ouafo-Luembe et al., 2017; Djoussou et al, 2018). Aerosol samples were collected on 47mm diameter filters on a weekly basis. Quartz fiber filters were used for carbonaceous analysis and the determination of Elemental Carbon (EC), Organic Carbon (OC) and Total Carbon (TC). Quartz fiber filters were cleaned by burning at 450°C for 48h before exposition. For each filter batch preparation, field blanks are included with the samplers sent into the field. Before and after collection, samples and blanks filters are conditioned in petri slides boxes and stored at 4°C. Weekly filter samples are analyzed at the Laboratoire d’Aérologie (LAERO) of Toulouse using thermo-optical methods. From 2005 to 2018, analysis were performed using the Desert Research Institute (DRI) instrument and the IMPROVE analytical protocol. Since 2018, analysis are performed using the Sunset instrument and the European EUSAAR2 protocol. All analytical results are converted to concentrations (in microgram per cubic meter).
DOI: 10.3886/e246399v1
title: Igbinedion University Teaching Hospital School of Nursing 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052

description: Igbinedion University Teaching Hospital School of Nursing 
 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052
DOI: 10.25326/595
title: PM10 EC/OC Analysis, Banizoumbou, Niger

description: Weekly integrated aerosol samples are collected using two automatic aerosol samplers specifically designed and developed for the INDAAF program (http://indaaf.obs-mip.fr). Each sampler is equipped with two independent air inlets connected with KNF pumps (N89 KNE-K 12V) operating at a flow rate of 9 L/min, Cole palmer ball flow meters with a micrometric valve (flow range adjustable from 0 to 10 L/min and NILU online filter holders. Each air inlet is surmounted with an aerosol cutting head corresponding to aerodynamic particles diameter. Two mini Partisol low air inlets PM2.5 and PM10 (Rupprecht and Patashnick) operates at a flow rate of 5 L/min and the air volume sample is measured with a GALLUS type G4 gas meter (accuracy ±0.01 m-3) (Ouafo-Luembe et al., 2017; Djoussou et al, 2018). Aerosol samples were collected on 47mm diameter filters on a weekly basis. Quartz fiber filters were used for carbonaceous analysis and the determination of Elemental Carbon (EC), Organic Carbon (OC) and Total Carbon (TC). Quartz fiber filters were cleaned by burning at 450°C for 48h before exposition. For each filter batch preparation, field blanks are included with the samplers sent into the field. Before and after collection, samples and blanks filters are conditioned in petri slides boxes and stored at 4°C. Weekly filter samples are analyzed at the Laboratoire d’Aérologie (LAERO) of Toulouse using thermo-optical methods. From 2005 to 2018, analysis were performed using the Desert Research Institute (DRI) instrument and the IMPROVE analytical protocol. Since 2018, analysis are performed using the Sunset instrument and the European EUSAAR2 protocol. All analytical results are converted to concentrations (in microgram per cubic meter).
DOI: 10.3886/e246400v1
title: Kano State School of School of Nursing 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052

description: Kano State School of School of Nursing 
 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052
DOI: 10.3886/e246402v2
title: Delta State School of Nursing 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052

description: Delta State School of Nursing
 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052
DOI: 10.3886/e246402v1
title: Delta State School of Nursing 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052

description: Delta State School of Nursing
 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052
DOI: 10.3886/e246401v1
title: Enugu State School of Nursing 2026/2027 Admission Form Is On Sale.Call 09017730052 To Apply and further admission assistance. Call Admin +2349017730052

description: Enugu State School of Nursing
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DOI: 10.25326/599
title: PM10 EC/OC Analysis, Lamto, Côte d'Ivoire

description: Weekly integrated aerosol samples are collected using two automatic aerosol samplers specifically designed and developed for the INDAAF program (http://indaaf.obs-mip.fr). Each sampler is equipped with two independent air inlets connected with KNF pumps (N89 KNE-K 220V) operating at a flow rate of 9 L/min, Cole palmer ball flow meters with a micrometric valve (flow range adjustable from 0 to 10 L/min and NILU online filter holders. Each air inlet is surmounted with an aerosol cutting head corresponding to aerodynamic particles diameter. Two mini Partisol low air inlets PM2.5 and PM10 (Rupprecht and Patashnick) operates at a flow rate of 5 L/min and the air volume sample is measured with a GALLUS type G4 gas meter (accuracy ±0.01 m-3) (Ouafo-Luembe et al., 2017; Djoussou et al, 2018). Aerosol samples were collected on 47mm diameter filters on a weekly basis. Quartz fiber filters were used for carbonaceous analysis and the determination of Elemental Carbon (EC), Organic Carbon (OC) and Total Carbon (TC). Quartz fiber filters were cleaned by burning at 450°C for 48h before exposition. For each filter batch preparation, field blanks are included with the samplers sent into the field. Before and after collection, samples and blanks filters are conditioned in petri slides boxes and stored at 4°C. Weekly filter samples are analyzed at the Laboratoire d’Aérologie (LAERO) of Toulouse using thermo-optical methods. From 2005 to 2018, analysis were performed using the Desert Research Institute (DRI) instrument and the IMPROVE analytical protocol. Since 2018, analysis are performed using the Sunset instrument and the European EUSAAR2 protocol. All analytical results are converted to concentrations (in microgram per cubic meter).