cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.7927/nq55-cr83
title: IPCC AR6 Synthesis Report LR Figure 2.1 (c): Changes in global surface temperature

description: The global surface temperature (shown as annual anomalies from a 1850–1900 baseline) has increased by around 1.1°C since 1850–1900. The vertical bar on the right shows the estimated temperature (very likely range) during the warmest multicentury period in at least the last 100,000 years, which occurred around 6500 years ago during the current interglacial period (Holocene). Prior to that, the next most recent warm period was about 125,000 years ago, when the assessed multicentury temperature range [0.5°C–1.5℃] overlaps the observations of the most recent decade. These past warm periods were caused by slow (multi-millennial) orbital variations.
DOI: 10.15468/dl.szh696
title: Occurrence Download

description: A dataset containing 2042 records in GBIF matching the query:
SELECT
 '105' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= -16.25916876999866
 AND decimalLatitude &lt;= -12.166598047573723
 AND decimalLongitude &gt;= 121.42401691442299
 AND decimalLongitude &lt;= 127.90594956561445
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 2042 records were derived from 50 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005484-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nenr7f
title: Occurrence Download

description: A dataset containing 154 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((98.801 9.128076, 98.729843 9.122503999999999, 98.660444 9.105924, 98.59451900000001 9.078747, 98.533694 9.041643000000001, 98.479471 8.99553, 98.43318499999999 8.941546000000001, 98.395974 8.881023000000001, 98.368754 8.815454000000001, 98.352187 8.746456, 98.346678 8.67573, 98.352355 8.605016000000001, 98.369073 8.536054999999999, 98.39641399999999 8.470545, 98.433701 8.410095999999999, 98.480014 8.356194, 98.534211 8.310162999999999, 98.59495800000001 8.273134000000001, 98.660764 8.246015, 98.730011 8.229473, 98.801 8.223913, 98.871989 8.229473, 98.941236 8.246015, 99.007042 8.273134000000001, 99.067789 8.310162999999999, 99.12198600000001 8.356194, 99.168299 8.410095999999999, 99.205586 8.470545, 99.232927 8.536054999999999, 99.249645 8.605016000000001, 99.25532200000001 8.67573, 99.249813 8.746456, 99.23324599999999 8.815454000000001, 99.20602599999999 8.881023000000001, 99.168815 8.941546000000001, 99.122529 8.99553, 99.06830600000001 9.041643000000001, 99.007481 9.078747, 98.94155600000001 9.105924, 98.872157 9.122503999999999, 98.801 9.128076))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 154 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005503-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wu9tzq
title: Occurrence Download

description: A dataset containing 4561 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Asparagus africanus"
 ]
}

 The dataset includes 4561 records from 172 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005502-260120142942310/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.31129795
title: Genome Sequences of Three Polyporaceae Species (Polyporales, Basidiomycota) from South Korea

description: White-rot basidiomycetes in the family Polyporaceae are important decomposers of lignocellulosic biomass in forest ecosystems and are recognized for their potential in industrial applications. Here, we report the draft genome sequences of <i>Lentinus arcularius</i>, <i>Polyporus parvovarius</i>, and <i>Trametes suaveolens</i>, isolated from South Korea. Using PacBio and Illumina sequencing, we obtained hybrid genome assemblies ranging from 37.8 to 57.9 Mb, with GC contents of 51.7–57.7% and completeness values of 97.4–99.0% (BUSCO, Fungi dataset). Gene prediction revealed 13,374–19,374 protein-coding genes per genome. Functional annotation identified a wide array of carbohydrate-active enzymes and biosynthetic gene clusters. Our findings expand the genomic resources for <i>Lentinus</i>, <i>Polyporus</i>, and <i>Trametes</i>, providing new insights into their lignocellulose-degrading capacity and bioactive metabolite potentials.
DOI: 10.6084/m9.figshare.31129795.v1
title: Genome Sequences of Three Polyporaceae Species (Polyporales, Basidiomycota) from South Korea

description: White-rot basidiomycetes in the family Polyporaceae are important decomposers of lignocellulosic biomass in forest ecosystems and are recognized for their potential in industrial applications. Here, we report the draft genome sequences of <i>Lentinus arcularius</i>, <i>Polyporus parvovarius</i>, and <i>Trametes suaveolens</i>, isolated from South Korea. Using PacBio and Illumina sequencing, we obtained hybrid genome assemblies ranging from 37.8 to 57.9 Mb, with GC contents of 51.7–57.7% and completeness values of 97.4–99.0% (BUSCO, Fungi dataset). Gene prediction revealed 13,374–19,374 protein-coding genes per genome. Functional annotation identified a wide array of carbohydrate-active enzymes and biosynthetic gene clusters. Our findings expand the genomic resources for <i>Lentinus</i>, <i>Polyporus</i>, and <i>Trametes</i>, providing new insights into their lignocellulose-degrading capacity and bioactive metabolite potentials.
DOI: 10.15468/dl.bnbe63
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.22199999999999 9.411068999999999, 99.150786 9.405495999999999, 99.081332 9.388916, 99.015354 9.361739, 98.954482 9.324634, 98.900217 9.278521, 98.85389600000001 9.224536000000001, 98.816659 9.164013000000001, 98.789419 9.098444000000001, 98.77284299999999 9.029446999999999, 98.767332 8.958721000000001, 98.773016 8.888007999999999, 98.789749 8.819049, 98.81711300000001 8.753541, 98.85442999999999 8.693094, 98.900779 8.639194, 98.955016 8.593165000000001, 99.015809 8.556138000000001, 99.08166199999999 8.529019999999999, 99.15096 8.512479000000001, 99.22199999999999 8.506919999999999, 99.29304 8.512479000000001, 99.36233799999999 8.529019999999999, 99.428191 8.556138000000001, 99.488984 8.593165000000001, 99.543221 8.639194, 99.58956999999999 8.693094, 99.626887 8.753541, 99.654251 8.819049, 99.670984 8.888007999999999, 99.67666800000001 8.958721000000001, 99.67115699999999 9.029446999999999, 99.65458099999999 9.098444000000001, 99.627341 9.164013000000001, 99.590104 9.224536000000001, 99.543783 9.278521, 99.489518 9.324634, 99.428646 9.361739, 99.362668 9.388916, 99.29321400000001 9.405495999999999, 99.22199999999999 9.411068999999999))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 32 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005505-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/ds/8441556
title: Brazilian Parliamentary Expenses Datasets (BPED)
DOI: 10.14279/depositonce-25164
title: Practical Guide: Responsible Research Data Management (RDM) - BPMN-based top-level process and phase protocols

description: This resource provides a practical, phase-by-phase guide for Responsible Research Data Management (RDM) in academia-industry projects, covering the research lifecycle from planning and data selection through data transfer, storage, processing, deposition, and deletion, including decision gates and expected artefacts. The guide is structured as a BPMN-inspired process map with clearly assigned roles and responsibilities, mandatory vs. optional steps, and embedded guidance (e.g., tools, standards, regulatory aspects). It is intended to support teams in implementing compliant, high-quality, and sustainable RDM practices by making tasks, handovers, and documentation requirements explicit and actionable.
DOI: 10.15468/dl.cpdjey
title: Occurrence Download

description: A dataset containing 54 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.879 9.427068999999999, 99.807783 9.421495999999999, 99.738325 9.404916, 99.67234500000001 9.377738000000001, 99.61147 9.340634, 99.557202 9.29452, 99.510879 9.240536000000001, 99.473641 9.180012, 99.4464 9.114444000000001, 99.429823 9.045446, 99.424312 8.97472, 99.429997 8.904007999999999, 99.446731 8.835049, 99.474096 8.769541, 99.511415 8.709094, 99.557765 8.655194, 99.612005 8.609165000000001, 99.6728 8.572138000000001, 99.73865600000001 8.545021, 99.807957 8.52848, 99.879 8.522919999999999, 99.95004299999999 8.52848, 100.019344 8.545021, 100.0852 8.572138000000001, 100.145995 8.609165000000001, 100.200235 8.655194, 100.246585 8.709094, 100.283904 8.769541, 100.311269 8.835049, 100.328003 8.904007999999999, 100.333688 8.97472, 100.328177 9.045446, 100.3116 9.114444000000001, 100.284359 9.180012, 100.247121 9.240536000000001, 100.200798 9.29452, 100.14653 9.340634, 100.085655 9.377738000000001, 100.019675 9.404916, 99.95021699999999 9.421495999999999, 99.879 9.427068999999999))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 54 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005507-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.awsc9x
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.73184000000001 24.495318, 88.654675 24.489741, 88.579431 24.473148, 88.507976 24.445954, 88.442086 24.408832, 88.383391 24.362706, 88.33334000000001 24.308721, 88.293161 24.248214, 88.263835 24.182683, 88.24606900000001 24.113748, 88.24028300000001 24.043111, 88.2466 23.972512, 88.26484499999999 23.903687, 88.294551 23.838328, 88.334974 23.778037, 88.38511 23.724291, 88.44372 23.678405, 88.509366 23.6415, 88.58044099999999 23.614477, 88.65520600000001 23.597995, 88.73184000000001 23.592456, 88.808474 23.597995, 88.883239 23.614477, 88.954314 23.6415, 89.01996 23.678405, 89.07857 23.724291, 89.12870599999999 23.778037, 89.169129 23.838328, 89.198835 23.903687, 89.21708 23.972512, 89.22339700000001 24.043111, 89.21761100000001 24.113748, 89.199845 24.182683, 89.170519 24.248214, 89.13034 24.308721, 89.08028899999999 24.362706, 89.02159399999999 24.408832, 88.955704 24.445954, 88.884249 24.473148, 88.809005 24.489741, 88.73184000000001 24.495318))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005508-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.18343819
title: SuperDARN data in netCDF format (2003-Feb)

description: 2003-Feb SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.5281/zenodo.6730687
title: SuperDARN data in netCDF format (2003-Feb)

description: 2003-Feb SuperDARN radar data in netCDF format. These files were produced using version 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.


The RST is available here: https://github.com/SuperDARN/rst



The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation.
Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications.
A brief statement on how to acknowledge use of SuperDARN data is provided below.




Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication.
A listing of radars and PIs with contact information can be found here:
(SuperDARN Radar Overview)



Recommended form of acknowledgement for the use of SuperDARN data:



'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'
DOI: 10.7927/b38b-zp83
title: IPCC AR6 Synthesis Report LR Figure 2.1 (d): Humans are responsible

description: Formal detection and attribution studies synthesise information from climate models and observations and show that the best estimate is that all the warming observed between 1850– 1900 and 2010–2019 is caused by humans. The panel shows temperature change attributed to: total human influence; its decomposition into changes in GHG concentrations and other human drivers (aerosols, ozone and land-use change (land-use reflectance)); solar and volcanic drivers; and internal climate variability. Whiskers show likely ranges
DOI: 10.15468/dl.cj4fbr
title: Occurrence Download

description: A dataset containing 8737 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-123.94048 42.74061,-123.70161 40.47269,-119.33035 40.63603,-118.90038 42.77568,-123.94048 42.74061))",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Lynx rufus, Ursus americanus, Sylvilagus bachmani, Neotoma fuscipes, Microtus californicus, Erethizon dorsatum dorsatum, Canis latrans, Pekania pennanti, Cervus canadensis, Dipodomys heermanni, Microtus montanus, Puma concolor, Odocoileus hemionus, Bassariscus astutus, Odocoileus hemionus columbianus, Dendragapus fuliginosus, Sciurus griseus, Spilogale gracilis, Vulpes vulpes, Urocyon cinereoargenteus, Cervus, Odocoileus, Dipodomys californicus, Odocoileus hemionus californicus)"
 ]
}

 The dataset includes 8737 records from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005509-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zgx297
title: Occurrence Download

description: A dataset containing 13 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.73184000000001 24.495318, 88.654675 24.489741, 88.579431 24.473148, 88.507976 24.445954, 88.442086 24.408832, 88.383391 24.362706, 88.33334000000001 24.308721, 88.293161 24.248214, 88.263835 24.182683, 88.24606900000001 24.113748, 88.24028300000001 24.043111, 88.2466 23.972512, 88.26484499999999 23.903687, 88.294551 23.838328, 88.334974 23.778037, 88.38511 23.724291, 88.44372 23.678405, 88.509366 23.6415, 88.58044099999999 23.614477, 88.65520600000001 23.597995, 88.73184000000001 23.592456, 88.808474 23.597995, 88.883239 23.614477, 88.954314 23.6415, 89.01996 23.678405, 89.07857 23.724291, 89.12870599999999 23.778037, 89.169129 23.838328, 89.198835 23.903687, 89.21708 23.972512, 89.22339700000001 24.043111, 89.21761100000001 24.113748, 89.199845 24.182683, 89.170519 24.248214, 89.13034 24.308721, 89.08028899999999 24.362706, 89.02159399999999 24.408832, 88.955704 24.445954, 88.884249 24.473148, 88.809005 24.489741, 88.73184000000001 24.495318))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 13 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005511-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.893pyj
title: Occurrence Download

description: A dataset containing 32 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((99.218 9.509067, 99.146766 9.503494, 99.077292 9.486914000000001, 99.011296 9.459735999999999, 98.950407 9.422631000000001, 98.89612700000001 9.376518000000001, 98.849794 9.322533, 98.812547 9.262009000000001, 98.785301 9.196441, 98.768721 9.127443, 98.76321 9.056718, 98.768896 8.986005, 98.785635 8.917047, 98.813007 8.85154, 98.850334 8.791093999999999, 98.89669499999999 8.737194000000001, 98.950947 8.691166000000001, 99.01175600000001 8.654139000000001, 99.077626 8.627022, 99.146941 8.610481, 99.218 8.604922, 99.28905899999999 8.610481, 99.358374 8.627022, 99.424244 8.654139000000001, 99.48505299999999 8.691166000000001, 99.539305 8.737194000000001, 99.585666 8.791093999999999, 99.62299299999999 8.85154, 99.65036499999999 8.917047, 99.66710399999999 8.986005, 99.67279000000001 9.056718, 99.66727899999999 9.127443, 99.650699 9.196441, 99.623453 9.262009000000001, 99.586206 9.322533, 99.539873 9.376518000000001, 99.48559299999999 9.422631000000001, 99.42470400000001 9.459735999999999, 99.35870799999999 9.486914000000001, 99.28923399999999 9.503494, 99.218 9.509067))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 32 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005512-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eebzqj
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.87913 24.496728, 88.801964 24.491151, 88.726719 24.474558, 88.655264 24.447363, 88.58937299999999 24.410242, 88.530677 24.364116, 88.480626 24.310131, 88.44044599999999 24.249624, 88.41112 24.184093, 88.393354 24.115158, 88.387568 24.044521, 88.393885 23.973922, 88.41213 23.905097, 88.44183700000001 23.839738, 88.48226 23.779447, 88.53239600000001 23.725701, 88.591007 23.679815, 88.656654 23.64291, 88.727729 23.615887, 88.80249499999999 23.599405, 88.87913 23.593866, 88.955765 23.599405, 89.030531 23.615887, 89.101606 23.64291, 89.167253 23.679815, 89.225864 23.725701, 89.276 23.779447, 89.316423 23.839738, 89.34613 23.905097, 89.364375 23.973922, 89.37069200000001 24.044521, 89.364906 24.115158, 89.34714 24.184093, 89.317814 24.249624, 89.27763400000001 24.310131, 89.227583 24.364116, 89.168887 24.410242, 89.102996 24.447363, 89.031541 24.474558, 88.95629599999999 24.491151, 88.87913 24.496728))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 11 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0005514-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.