cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25346/s6lqjm3j/l4gju8
title: msXL_222v_MMSI+RTI+W365G58_031_F.tif
DOI: 10.25346/s6lqjm3j/bwio96
title: msXL_222v_MMSI+RTI+W365B47_035_F.tif
DOI: 10.25346/s6lqjm3j/fqf9fl
title: msXL_334v_MMSI+RTI+W365R25_027_F.tif
DOI: 10.25346/s6lqjm3j/jechnb
title: msXL_334v_MMSI+RTI+W365G58_031_F.tif
DOI: 10.25346/s6lqjm3j/kwqprc
title: msXL_334v_MMSI+RTI+W365B47_035_F.tif
DOI: 10.15468/dl.2kwunk
title: Occurrence Download

description: A dataset listing the 1 species recorded in GBIF matching the query:
{
 "TaxonKey" : [
 "is Tupaia chrysogaster"
 ]
}

 The dataset's 1 records were derived from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032038-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/7azwzj
title: msXL_334v_MMSI+RTI+TX940IR_025_F.tif
DOI: 10.25346/s6lqjm3j/wul0ak
title: msXL_334v_MMSI+RTI+TX735IR_024_F.tif
DOI: 10.25346/s6lqjm3j/dejlb3
title: msXL_334v_MMSI+RTI+TX615RO_023_F.tif
DOI: 10.25346/s6lqjm3j/mb1z8h
title: msXL_334v_MMSI+RTI+TX615IR_023_F.tif
DOI: 10.25346/s6lqjm3j/aznqia
title: msXL_334v_MMSI+RTI+TX1050R_026_F.tif
DOI: 10.25346/s6lqjm3j/wdqwja
title: msXL_334v_MMSI+RTI+TX1050R_022_F.tif
DOI: 10.25346/s6lqjm3j/hgq4pi
title: msXL_334v_MMSI+RTI+M1050IR_021_F.tif
DOI: 10.25346/s6lqjm3j/6qyich
title: msXL_334v_MMSI+RTI+M1050IR_020_F.tif
DOI: 10.25346/s6lqjm3j/xrmmwj
title: msXL_334v_MMSI+RTI+M1050IR_019_F.tif
DOI: 10.25346/s6lqjm3j/crjesy
title: msXL_334v_MMSI+RTI+M0940IR_018_F.tif
DOI: 10.25346/s6lqjm3j/yvhel7
title: msXL_334v_MMSI+RTI+M0850IR_017_F.tif
DOI: 10.25346/s6lqjm3j/lgqvna
title: msXL_334v_MMSI+RTI+M0780IR_016_F.tif
DOI: 10.25346/s6lqjm3j/0uqmdm
title: msXL_334v_MMSI+RTI+M0735IR_015_F.tif
DOI: 10.25346/s6lqjm3j/cogac2
title: msXL_334v_MMSI+RTI+M0700IR_014_F.tif
DOI: 10.25346/s6lqjm3j/qwh5tq
title: msXL_334v_MMSI+RTI+M0655DR_013_F.tif
DOI: 10.25346/s6lqjm3j/xj2igu
title: msXL_334v_MMSI+RTI+M0630RD_012_F.tif
DOI: 10.25346/s6lqjm3j/hxgp7i
title: msXL_334v_MMSI+RTI+M0615RO_011_F.tif
DOI: 10.25346/s6lqjm3j/ucffir
title: msXL_334v_MMSI+RTI+M0590AM_010_F.tif
DOI: 10.25346/s6lqjm3j/ualqfh
title: msXL_334v_MMSI+RTI+M0560LI_009_F.tif
DOI: 10.25346/s6lqjm3j/okanso
title: msXL_334v_MMSI+RTI+M0530GN_008_F.tif
DOI: 10.25346/s6lqjm3j/u4hroh
title: msXL_334v_MMSI+RTI+M0505CN_007_F.tif
DOI: 10.15468/dl.649fnw
title: Occurrence Download

description: A dataset containing 80229 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Rangifer"
 ]
}

 The dataset includes 80229 records from 202 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032005-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/hyoqa1
title: msXL_334v_MMSI+RTI+M0470LB_006_F.tif
DOI: 10.25346/s6lqjm3j/jyfi64
title: msXL_334v_MMSI+RTI+M0450RB_005_F.tif
DOI: 10.25346/s6lqjm3j/ve11qk
title: msXL_334v_MMSI+RTI+M0420VI_004_F.tif
DOI: 10.25346/s6lqjm3j/chum6b
title: msXL_334v_MMSI+RTI+M0400UV_003_F.tif
DOI: 10.25346/s6lqjm3j/xcd0q4
title: msXL_334v_MMSI+RTI+M0385UV_002_F.tif
DOI: 10.25346/s6lqjm3j/homfgu
title: msXL_334v_MMSI+RTI+M0365UV_001_F.tif
DOI: 10.6084/m9.figshare.30615341.v1
title: Genomic Epidemiology of SARS-CoV-2 in Peru from 2020 to 2024

description: This dataset compiles all code, scripts, supporting files, and figure outputs used for the analyses presented in Sobkowiak et al., Genomic Epidemiology of SARS-CoV-2 in Peru, 2020–2024 (Communications Medicine, 2025). <b>Contents:</b><b>1. Analysis Code</b>Core Python scripts used to curate metadata, process genomic data, perform lineage assignments, compute summary statistics, and prepare inputs for downstream phylogenetic and phylogeographic analyses. All primary analysis code was written by Ben Sobkowiak, Amy Langdon, Diego Villa-Almeida, and Renato Cava-Miller.<b>2. Figure-Specific Pipelines and Outputs</b><b>Figure 1: Epidemic overview of SARS-CoV-2 in Peru (2020–2024)</b>Scripts for generating national epidemic curves, cumulative incidence maps, and weekly incidence heatmaps.(a) Weekly COVID-19 positive cases and deaths.(b) Cumulative incidence and mortality rate at the province level.(c) Weekly incidence by department.<b>Figure 2: Phylogenetic analysis of 49,724 high-quality SARS-CoV-2 genomes</b>Pipelines for variant stratification, weekly lineage summaries, and timed phylogeny generation.(a) Weekly variant counts and proportions classified as VOC/VOI.(b) Time-calibrated phylogeny colored by Pango lineage assignment.Lineages are labeled “Other” if not classified as VOC/VOI, and “Unassigned” when Pango calling was inconclusive.<b>Figure 3: Inferred movements of SARS-CoV-2 within Peru</b>Python scripts for constructing subnational phylogeographic maps using Cartopy, GeoPandas, Matplotlib, Basemap, and Shapely.The map is projected in Plate Carrée at a scale of 200 km.Circles represent departments, scaled to the number of inferred outgoing movements.Arrows depict origin–destination transitions, with width proportional to event count.A population-density background is based on MINSA open data and INEI administrative boundaries.<b>Figure 4: International spread of Peruvian-origin SARS-CoV-2 sub-lineages</b>Scripts for generating global phylogeographic maps of international transitions.Visualizations represent inferred movements of Lambda C.37, Gamma P.1.12, Omicron XBB.2.6, and Omicron DJ.1.Arcs show cross-country transitions projected in Plate Carrée at 1,000 km scale.Arrow width corresponds to the number of inferred transitions; color denotes lineage identity.Basemaps were generated from Natural Earth Data, and geodesic arcs were computed using standard geospatial libraries.<b>Links to the source GitHub repositories:</b>https://github.com/healthinnovation/covid19trends/https://github.com/bensobkowiak/Peru_SARS-CoV-2/https://github.com/renatocava/inferred_dates_animation/Uploaded by Pablo Tsukayama on November 13, 2025.
DOI: 10.25346/s6lqjm3j/fbzeso
title: msXL_334v_MMSI+RTI+Arc_G15_096_F.tif
DOI: 10.6084/m9.figshare.30615341
title: Genomic Epidemiology of SARS-CoV-2 in Peru from 2020 to 2024

description: This dataset compiles all code, scripts, supporting files, and figure outputs used for the analyses presented in Sobkowiak et al., Genomic Epidemiology of SARS-CoV-2 in Peru, 2020–2024 (Communications Medicine, 2025). <b>Contents:</b><b>1. Analysis Code</b>Core Python scripts used to curate metadata, process genomic data, perform lineage assignments, compute summary statistics, and prepare inputs for downstream phylogenetic and phylogeographic analyses. All primary analysis code was written by Ben Sobkowiak, Amy Langdon, Diego Villa-Almeida, and Renato Cava-Miller.<b>2. Figure-Specific Pipelines and Outputs</b><b>Figure 1: Epidemic overview of SARS-CoV-2 in Peru (2020–2024)</b>Scripts for generating national epidemic curves, cumulative incidence maps, and weekly incidence heatmaps.(a) Weekly COVID-19 positive cases and deaths.(b) Cumulative incidence and mortality rate at the province level.(c) Weekly incidence by department.<b>Figure 2: Phylogenetic analysis of 49,724 high-quality SARS-CoV-2 genomes</b>Pipelines for variant stratification, weekly lineage summaries, and timed phylogeny generation.(a) Weekly variant counts and proportions classified as VOC/VOI.(b) Time-calibrated phylogeny colored by Pango lineage assignment.Lineages are labeled “Other” if not classified as VOC/VOI, and “Unassigned” when Pango calling was inconclusive.<b>Figure 3: Inferred movements of SARS-CoV-2 within Peru</b>Python scripts for constructing subnational phylogeographic maps using Cartopy, GeoPandas, Matplotlib, Basemap, and Shapely.The map is projected in Plate Carrée at a scale of 200 km.Circles represent departments, scaled to the number of inferred outgoing movements.Arrows depict origin–destination transitions, with width proportional to event count.A population-density background is based on MINSA open data and INEI administrative boundaries.<b>Figure 4: International spread of Peruvian-origin SARS-CoV-2 sub-lineages</b>Scripts for generating global phylogeographic maps of international transitions.Visualizations represent inferred movements of Lambda C.37, Gamma P.1.12, Omicron XBB.2.6, and Omicron DJ.1.Arcs show cross-country transitions projected in Plate Carrée at 1,000 km scale.Arrow width corresponds to the number of inferred transitions; color denotes lineage identity.Basemaps were generated from Natural Earth Data, and geodesic arcs were computed using standard geospatial libraries.<b>Links to the source GitHub repositories:</b>https://github.com/healthinnovation/covid19trends/https://github.com/bensobkowiak/Peru_SARS-CoV-2/https://github.com/renatocava/inferred_dates_animation/Uploaded by Pablo Tsukayama on November 13, 2025.
DOI: 10.25346/s6lqjm3j/tqh3mm
title: msXL_334v_MMSI+RTI+Arc_G13_095_F.tif
DOI: 10.25346/s6lqjm3j/5voby1
title: msXL_334v_MMSI+RTI+Arc_G11_094_F.tif
DOI: 10.25346/s6lqjm3j/z1leqt
title: msXL_334v_MMSI+RTI+Arc_G09_093_F.tif
DOI: 10.25346/s6lqjm3j/jfjgh1
title: msXL_334v_MMSI+RTI+Arc_G07_092_F.tif
DOI: 10.25346/s6lqjm3j/dtwmwr
title: msXL_334v_MMSI+RTI+Arc_G05_091_F.tif
DOI: 10.25346/s6lqjm3j/obzj31
title: msXL_334v_MMSI+RTI+Arc_G03_090_F.tif
DOI: 10.25346/s6lqjm3j/m5ec6p
title: msXL_334v_MMSI+RTI+Arc_G01_089_F.tif
DOI: 10.25346/s6lqjm3j/pkyek4
title: msXL_334v_MMSI+RTI+Arc_F16_088_F.tif
DOI: 10.25346/s6lqjm3j/dqofol
title: msXL_334v_MMSI+RTI+Arc_F14_087_F.tif
DOI: 10.25346/s6lqjm3j/cq1gnc
title: msXL_334v_MMSI+RTI+Arc_F12_086_F.tif
DOI: 10.25346/s6lqjm3j/xjfl3g
title: msXL_334v_MMSI+RTI+Arc_F10_085_F.tif
DOI: 10.25346/s6lqjm3j/0vf47a
title: msXL_334v_MMSI+RTI+Arc_F08_084_F.tif
DOI: 10.25346/s6lqjm3j/xv6xq1
title: msXL_334v_MMSI+RTI+Arc_F06_083_F.tif
DOI: 10.25346/s6lqjm3j/4dpvpu
title: msXL_334v_MMSI+RTI+Arc_F04_082_F.tif
DOI: 10.25346/s6lqjm3j/sdp5gn
title: msXL_334v_MMSI+RTI+Arc_F02_081_F.tif
DOI: 10.25346/s6lqjm3j/ouihgd
title: msXL_334v_MMSI+RTI+Arc_E15_080_F.tif
DOI: 10.25346/s6lqjm3j/iegf51
title: msXL_334v_MMSI+RTI+Arc_E13_079_F.tif
DOI: 10.25346/s6lqjm3j/frsxzh
title: msXL_334v_MMSI+RTI+Arc_E11_078_F.tif
DOI: 10.25346/s6lqjm3j/oqkipw
title: msXL_334v_MMSI+RTI+Arc_E09_077_F.tif
DOI: 10.5281/zenodo.17604790
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS251113y Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS251113y Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.5281/zenodo.17604791
title: Submitted Galaxy Scores to the Gravitational Wave Treasure Map for event MS251113y Preliminary

description: Attached in a .json file is the ranked galaxy information within the contour region of the EM counterpart search associated with the gravitational wave event MS251113y Preliminary. A reference to these calculations can be found here: https://ui.adsabs.harvard.edu/abs/2017ApJ...848L..33A/abstract
DOI: 10.25346/s6lqjm3j/2dsbpt
title: msXL_334v_MMSI+RTI+Arc_E07_076_F.tif
DOI: 10.25346/s6lqjm3j/w5vy8t
title: msXL_334v_MMSI+RTI+Arc_E05_075_F.tif
DOI: 10.25346/s6lqjm3j/30s8db
title: msXL_334v_MMSI+RTI+Arc_E03_074_F.tif
DOI: 10.25346/s6lqjm3j/v8ngep
title: msXL_334v_MMSI+RTI+Arc_E01_073_F.tif
DOI: 10.25346/s6lqjm3j/dktbku
title: msXL_334v_MMSI+RTI+Arc_D16_072_F.tif
DOI: 10.25346/s6lqjm3j/gen7rv
title: msXL_334v_MMSI+RTI+Arc_D14_071_F.tif
DOI: 10.25346/s6lqjm3j/j9ecnq
title: msXL_334v_MMSI+RTI+Arc_D12_070_F.tif
DOI: 10.25346/s6lqjm3j/apqcah
title: msXL_334v_MMSI+RTI+Arc_D10_069_F.tif
DOI: 10.25346/s6lqjm3j/61puij
title: msXL_334v_MMSI+RTI+Arc_D08_068_F.tif
DOI: 10.25346/s6lqjm3j/vq7bsl
title: msXL_334v_MMSI+RTI+Arc_D06_067_F.tif
DOI: 10.25346/s6lqjm3j/myzejk
title: msXL_334v_MMSI+RTI+Arc_D04_066_F.tif
DOI: 10.25346/s6lqjm3j/qyp2vg
title: msXL_334v_MMSI+RTI+Arc_D02_065_F.tif
DOI: 10.25346/s6lqjm3j/qjuynb
title: msXL_334v_MMSI+RTI+Arc_C15_064_F.tif
DOI: 10.25346/s6lqjm3j/3dujx5
title: msXL_334v_MMSI+RTI+Arc_C13_063_F.tif
DOI: 10.25346/s6lqjm3j/w0e4qg
title: msXL_334v_MMSI+RTI+Arc_C11_062_F.tif
DOI: 10.25346/s6lqjm3j/bfyvwy
title: msXL_334v_MMSI+RTI+Arc_C09_061_F.tif
DOI: 10.25346/s6lqjm3j/cbfzsn
title: msXL_334v_MMSI+RTI+Arc_C07_060_F.tif
DOI: 10.25346/s6lqjm3j/g7pk4i
title: msXL_334v_MMSI+RTI+Arc_C05_059_F.tif
DOI: 10.25346/s6lqjm3j/mpdzn0
title: msXL_334v_MMSI+RTI+Arc_C03_058_F.tif
DOI: 10.25346/s6lqjm3j/82q9kq
title: msXL_334v_MMSI+RTI+Arc_C01_057_F.tif
DOI: 10.25346/s6lqjm3j/ch7dgk
title: msXL_334v_MMSI+RTI+Arc_B16_056_F.tif
DOI: 10.25346/s6lqjm3j/gfxfvw
title: msXL_334v_MMSI+RTI+Arc_B14_055_F.tif
DOI: 10.25346/s6lqjm3j/hpgfpq
title: msXL_334v_MMSI+RTI+Arc_B12_054_F.tif
DOI: 10.25346/s6lqjm3j/qnrqzs
title: msXL_334v_MMSI+RTI+Arc_B10_053_F.tif
DOI: 10.25346/s6lqjm3j/vxze6u
title: msXL_334v_MMSI+RTI+Arc_B08_052_F.tif
DOI: 10.25346/s6lqjm3j/bmfmvm
title: msXL_334v_MMSI+RTI+Arc_B06_051_F.tif
DOI: 10.25346/s6lqjm3j/wntcsc
title: msXL_334v_MMSI+RTI+Arc_B04_050_F.tif
DOI: 10.25346/s6lqjm3j/rf8gv9
title: msXL_334v_MMSI+RTI+Arc_B02_049_F.tif
DOI: 10.25346/s6lqjm3j/12ojum
title: msXL_334v_MMSI+RTI+Arc_A15_048_F.tif
DOI: 10.25346/s6lqjm3j/qtgllq
title: msXL_334v_MMSI+RTI+Arc_A13_047_F.tif
DOI: 10.15468/dl.829bm8
title: Occurrence Download

description: A dataset containing 1940 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "and" : [
 "Country is one of (New Zealand)",
 {
 "not" : {
 "Issue" : [
 "is Country coordinate mismatch"
 ]
 }
 }
 ]
 },
 "TaxonKey is one of (Geotria australis [GBIF Backbone Taxonomy])"
 ]
}

 The dataset includes 1940 records from 20 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032048-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/zvhmye
title: msXL_334v_MMSI+RTI+Arc_A11_046_F.tif
DOI: 10.15468/dl.hb9gm6
title: Occurrence Download

description: A dataset containing 5469 species occurrences available in GBIF matching the query:
{
 "and" : [
 "DatasetKey is one of (Oregon State University Herpetological Collection, MVZ Herp Collection (Arctos), UTA Reptiles, PSM Vertebrates Collection, CAS Herpetology (HERP), SDNHM Herpetology Collection, Royal BC Museum - Herpetology Collection, UWBM Herpetology Collection (Arctos), NMNH Extant Specimen Records (USNM, US))",
 "TaxonKey is Thamnophis ordinoides"
 ]
}

 The dataset includes 5469 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032049-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/fsmtbw
title: msXL_334v_MMSI+RTI+Arc_A09_045_F.tif
DOI: 10.25346/s6lqjm3j/gualr9
title: msXL_334v_MMSI+RTI+Arc_A07_044_F.tif
DOI: 10.25346/s6lqjm3j/fn767o
title: msXL_334v_MMSI+RTI+Arc_A05_043_F.tif
DOI: 10.25346/s6lqjm3j/k4qucf
title: msXL_334v_MMSI+RTI+Arc_A03_042_F.tif
DOI: 10.25346/s6lqjm3j/vzfx2g
title: msXL_334v_MMSI+RTI+Arc_A01_041_F.tif
DOI: 10.15468/dl.w4r4y8
title: Occurrence Download

description: A dataset containing 119 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sceloporus heterolepis",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 119 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032050-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/1nnkle
title: msXL_334r_MMSI+RTI+W530R72_039_F.tif
DOI: 10.25346/s6lqjm3j/9qj7tw
title: msXL_334r_MMSI+RTI+W505665_040_F.tif
DOI: 10.25346/s6lqjm3j/n6hkoa
title: msXL_334r_MMSI+RTI+W450R25_030_F.tif
DOI: 10.25346/s6lqjm3j/1drwtp
title: msXL_334r_MMSI+RTI+W450G58_034_F.tif
DOI: 10.15468/dl.waxrqj
title: Occurrence Download

description: A dataset containing 1109319 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (Belgium, Germany, Netherlands)",
 "TaxonKey is one of (Ondatra zibethicus, Myocastor coypus)",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 1109319 records from 79 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032029-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/ixbzdl
title: msXL_334r_MMSI+RTI+W450B47_038_F.tif
DOI: 10.25346/s6lqjm3j/h742e9
title: msXL_334r_MMSI+RTI+W400R25_029_F.tif
DOI: 10.25346/s6lqjm3j/5y5xlg
title: msXL_334r_MMSI+RTI+W400G58_033_F.tif
DOI: 10.25346/s6lqjm3j/ojivvy
title: msXL_334r_MMSI+RTI+W400B47_037_F.tif
DOI: 10.15468/dl.nenuqa
title: Occurrence Download

description: A dataset containing 3823 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Sceloporus horridus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 3823 records from 51 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032051-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/je7cow
title: msXL_334r_MMSI+RTI+W385R25_028_F.tif
DOI: 10.25346/s6lqjm3j/15qq2b
title: msXL_334r_MMSI+RTI+W385G58_032_F.tif
DOI: 10.25346/s6lqjm3j/lxifxb
title: msXL_334r_MMSI+RTI+W385B47_036_F.tif
DOI: 10.25346/s6lqjm3j/jflyso
title: msXL_334r_MMSI+RTI+W365R25_027_F.tif
DOI: 10.25346/s6lqjm3j/hgy07e
title: msXL_334r_MMSI+RTI+W365G58_031_F.tif
DOI: 10.25346/s6lqjm3j/nf0zqs
title: msXL_334r_MMSI+RTI+W365B47_035_F.tif
DOI: 10.25346/s6lqjm3j/xnnnmj
title: msXL_341v_MMSI+RTI+Arc_F10_085_F.tif
DOI: 10.25346/s6lqjm3j/xzswua
title: msXL_341v_MMSI+RTI+Arc_F08_084_F.tif
DOI: 10.25346/s6lqjm3j/w6ivit
title: msXL_341v_MMSI+RTI+Arc_F06_083_F.tif
DOI: 10.25346/s6lqjm3j/ir1rpm
title: msXL_341v_MMSI+RTI+Arc_F04_082_F.tif
DOI: 10.25346/s6lqjm3j/vub9b1
title: msXL_341v_MMSI+RTI+Arc_F02_081_F.tif
DOI: 10.25346/s6lqjm3j/kdonog
title: msXL_341v_MMSI+RTI+Arc_E15_080_F.tif
DOI: 10.25346/s6lqjm3j/dyacve
title: msXL_341v_MMSI+RTI+Arc_E13_079_F.tif
DOI: 10.25346/s6lqjm3j/el2gak
title: msXL_341v_MMSI+RTI+Arc_E11_078_F.tif
DOI: 10.25346/s6lqjm3j/lqngvd
title: msXL_341v_MMSI+RTI+Arc_E09_077_F.tif
DOI: 10.25346/s6lqjm3j/pystjf
title: msXL_341v_MMSI+RTI+Arc_E07_076_F.tif
DOI: 10.25346/s6lqjm3j/umkut3
title: msXL_341v_MMSI+RTI+Arc_E05_075_F.tif
DOI: 10.25346/s6lqjm3j/r1igzl
title: msXL_341v_MMSI+RTI+Arc_E03_074_F.tif
DOI: 10.25346/s6lqjm3j/va8zdq
title: msXL_341v_MMSI+RTI+Arc_E01_073_F.tif
DOI: 10.25346/s6lqjm3j/k8wtqs
title: msXL_341v_MMSI+RTI+Arc_D16_072_F.tif
DOI: 10.25346/s6lqjm3j/es8b5z
title: msXL_341v_MMSI+RTI+Arc_D14_071_F.tif
DOI: 10.25346/s6lqjm3j/awhcnu
title: msXL_341v_MMSI+RTI+Arc_D12_070_F.tif
DOI: 10.25346/s6lqjm3j/afukhg
title: msXL_341v_MMSI+RTI+Arc_D10_069_F.tif
DOI: 10.25346/s6lqjm3j/ykcpyh
title: msXL_341v_MMSI+RTI+Arc_D08_068_F.tif
DOI: 10.25346/s6lqjm3j/jbix8r
title: msXL_341v_MMSI+RTI+Arc_D06_067_F.tif
DOI: 10.25346/s6lqjm3j/94bz6c
title: msXL_341v_MMSI+RTI+Arc_D04_066_F.tif
DOI: 10.25346/s6lqjm3j/orhun9
title: msXL_341v_MMSI+RTI+Arc_D02_065_F.tif
DOI: 10.25346/s6lqjm3j/i4penk
title: msXL_341v_MMSI+RTI+Arc_C15_064_F.tif
DOI: 10.25346/s6lqjm3j/gru46b
title: msXL_341v_MMSI+RTI+Arc_C13_063_F.tif
DOI: 10.25346/s6lqjm3j/llnp9k
title: msXL_341v_MMSI+RTI+Arc_C11_062_F.tif
DOI: 10.25346/s6lqjm3j/fjazur
title: msXL_341v_MMSI+RTI+Arc_C09_061_F.tif
DOI: 10.25346/s6lqjm3j/folmkg
title: msXL_341v_MMSI+RTI+Arc_C07_060_F.tif
DOI: 10.25346/s6lqjm3j/fzvedj
title: msXL_341v_MMSI+RTI+Arc_C05_059_F.tif
DOI: 10.25346/s6lqjm3j/rmjsls
title: msXL_341v_MMSI+RTI+Arc_C03_058_F.tif
DOI: 10.25346/s6lqjm3j/9islyi
title: msXL_341v_MMSI+RTI+Arc_C01_057_F.tif
DOI: 10.25346/s6lqjm3j/ufv1xd
title: msXL_341v_MMSI+RTI+Arc_B16_056_F.tif
DOI: 10.25346/s6lqjm3j/hyt788
title: msXL_341v_MMSI+RTI+Arc_B14_055_F.tif
DOI: 10.25346/s6lqjm3j/clx0ic
title: msXL_341v_MMSI+RTI+Arc_B12_054_F.tif
DOI: 10.25346/s6lqjm3j/mjtrz0
title: msXL_341v_MMSI+RTI+Arc_B10_053_F.tif
DOI: 10.25346/s6lqjm3j/2hxdsp
title: msXL_341v_MMSI+RTI+Arc_B08_052_F.tif
DOI: 10.25346/s6lqjm3j/kgllnc
title: msXL_341v_MMSI+RTI+Arc_B06_051_F.tif
DOI: 10.25346/s6lqjm3j/c9q5tt
title: msXL_341v_MMSI+RTI+Arc_B04_050_F.tif
DOI: 10.25346/s6lqjm3j/ucwnuh
title: msXL_341v_MMSI+RTI+Arc_B02_049_F.tif
DOI: 10.25346/s6lqjm3j/ng8khv
title: msXL_341v_MMSI+RTI+Arc_A15_048_F.tif
DOI: 10.25346/s6lqjm3j/ogxsyn
title: msXL_341v_MMSI+RTI+Arc_A13_047_F.tif
DOI: 10.25346/s6lqjm3j/kc50o4
title: msXL_341v_MMSI+RTI+Arc_A11_046_F.tif
DOI: 10.25346/s6lqjm3j/fpxqdu
title: msXL_341v_MMSI+RTI+Arc_A09_045_F.tif
DOI: 10.25346/s6lqjm3j/r5puac
title: msXL_341v_MMSI+RTI+Arc_A07_044_F.tif
DOI: 10.15468/dl.3xwske
title: Occurrence Download

description: A dataset containing 19077 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Portugal",
 "GadmGid is PRT.7.7_1",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Tracheophyta"
 ]
}

 The dataset includes 19077 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0032052-251025141854904/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25346/s6lqjm3j/etjby1
title: msXL_341v_MMSI+RTI+Arc_A05_043_F.tif
DOI: 10.14279/depositonce-24800
title: Design of Experiments for Cyclic Aging of LFP 18650 Cells: Impact of Charge/Discharge C-Rates, Depth of Discharge, and Temperature on Battery Degradation

description: This dataset comprises experimental data from a comprehensive Design of Experiments (DoE) study investigating the cyclic aging behavior of Lithium Iron Phosphate (LFP) 18650 battery cells under varying operational conditions. The study employs both full factorial and fractional factorial experimental designs to systematically assess the influence of three primary factors on battery degradation: Charge C-Rate: 0.5C to 0.9C (0.9-1.62 A) Discharge C-Rate: 1C to 2.5C (1.8-4.5 A) Depth of Discharge (DOD): 45% to 65% (0.81-1.17 Ah) All cycling experiments were conducted at a controlled ambient temperature of 25°C. The experimental plan includes 15 test cells assigned to eight different factorial combinations, with each condition tested in duplicate to ensure reproducibility. Each cell underwent multiple aging loops. The dataset contains high-resolution time-series measurements recorded at 1 Hz sampling frequency, including voltage, current, temperature, and auxiliary parameters across multiple test steps. Data are stored in partitioned Parquet format for efficient access and analysis, enabling investigation of capacity fade, impedance growth, and state-of-health degradation mechanisms under controlled cycling protocols.
DOI: 10.25346/s6lqjm3j/y3tzfx
title: msXL_341v_MMSI+RTI+Arc_A03_042_F.tif
DOI: 10.25346/s6lqjm3j/7weqks
title: msXL_341v_MMSI+RTI+Arc_A01_041_F.tif
DOI: 10.25346/s6lqjm3j/kwlg25
title: msXL_341r_MMSI+RTI+W530R72_039_F.tif
DOI: 10.25346/s6lqjm3j/5cozhm
title: msXL_341r_MMSI+RTI+W505665_040_F.tif
DOI: 10.34740/kaggle/dsv/13724721
title: Dataset jadwal event lariku.info
DOI: 10.25346/s6lqjm3j/caqh6s
title: msXL_341r_MMSI+RTI+W450R25_030_F.tif
DOI: 10.25346/s6lqjm3j/mpntfx
title: msXL_341r_MMSI+RTI+W450G58_034_F.tif
DOI: 10.34740/kaggle/dsv/13724718
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.25346/s6lqjm3j/zgn25a
title: msXL_341r_MMSI+RTI+W450B47_038_F.tif
DOI: 10.25346/s6lqjm3j/i7k330
title: msXL_341r_MMSI+RTI+W400R25_029_F.tif