cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.4231/r7bg2kzx
title: gSSURGO-based Floodplain Maps of Florida

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Florida. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r76q1v65
title: gSSURGO-based Floodplain Maps of Georgia

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Georgia. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r72z13gt
title: gSSURGO-based Floodplain Maps of Hawaii

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Hawaii. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r79g5js3
title: gSSURGO-based Floodplain Maps of Iowa

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Iowa. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r7z60m0v
title: gSSURGO-based Floodplain Maps of Idaho

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Idaho. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r7td9v8k
title: gSSURGO-based Floodplain Maps of Illinois

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Illinois. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r75q4t2s
title: gSSURGO-based Floodplain Maps of Kansas

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Kansas. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r71z42bf
title: gSSURGO-based Floodplain Maps of Kentucky

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Kentucky. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r7x63jwh
title: gSSURGO-based Floodplain Maps of Louisiana

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Louisiana. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r7j10145
title: gSSURGO-based Floodplain Maps of Massachusetts

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Massachusetts. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.15468/dl.x9b6ms
title: Occurrence Download

description: A dataset containing 92122 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Mangifera indica",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 92122 records from 605 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059302-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.4231/r7ns0rtb
title: gSSURGO-based Floodplain Maps of Maryland

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Maryland. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.4231/r7sf2t56
title: gSSURGO-based Floodplain Maps of Maine

description: &lt;p&gt;US national wide gSSURGO based floodplain maps are developed by using Gridded Soil Survey Geographic (gSSURGO) database. Specifically, the SSURGO map units are joined to certain key attributes in the muaggatt and component tables. After joining the spatial data to &lsquo;muaggatt&rsquo; and &lsquo;component&rsquo; tables, map unit polygons are selected by the following two queries: (1) &quot;geomdesc&quot; LIKE &#39;%flood%&#39; AND &quot;comppct_r&quot; &gt;= 85) OR &quot;taxsubgrp&quot; LIKE &#39;%fluv%&#39;; (2) &ldquo;muname&quot; =&#39;Water&#39; OR &quot;flodfreqdcd&quot; in (&#39;Rare&#39;, &#39;Occasional&#39;, &#39;Frequent&#39;, &#39;Very Frequent&#39;)&quot;. The result from this query, which is a polygon feature class or shapefile, is then dissolved to remove any area less than 15000 square meters are removed. More details about this approach can be found in the following publication: Sangwan, Nikhil, and V. Merwade, A faster and economical approach to floodplain mapping by using soil information, Journal of American Water Resources Association, 51(5): 1286-1304. (2015)&lt;/p&gt;
description: This dataset provides a shapefile showing the natural floodplain for Maine. These floodplain polygons for the entire state are extracted from the gSSURGO soil data from the Natural Resources Conservation Service (NRCS).
DOI: 10.15468/dl.ku6mjw
title: Occurrence Download

description: A dataset containing 277990 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Festuca ovina",
 "HasCoordinate is true"
 ]
}

 The dataset includes 277990 records from 999 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0059303-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cjjkuk
title: Occurrence Download

description: A dataset containing 59 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Loricariichthys melanocheilus Reis & Pereira, 2000",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 59 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0003484-250415084134356/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.eqw79x
title: Occurrence Download

description: A dataset containing 20957 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is CHAS Herpetology"
 ]
}

 The dataset includes 20957 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0204574-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sevtyc
title: Occurrence Download

description: A dataset containing 15054 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Cladonia arbuscula, Lecanora mughicola Nyl.)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 15054 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0167958-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.mhhru6
title: Occurrence Download

description: A dataset containing 4412 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Africa",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Oryza sativa L.",
 "Year 1981-2023"
 ]
}

 The dataset includes 4412 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0094708-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hkevtd
title: Occurrence Download

description: A dataset containing 6079 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Chiroptera"
 ]
}

 The dataset includes 6079 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0329537-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8pfwhc
title: Occurrence Download

description: A dataset containing 651272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is China",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 651272 records from 344 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0167965-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d7memg
title: Occurrence Download

description: A dataset containing 3863 species occurrences available in GBIF matching the query:
{
 "and" : [
 "VerbatimScientificName is Sittiparus castaneoventris",
 "BasisOfRecord is one of (Machine Observation, Human Observation)",
 "Year 2011-2021",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen, Specimen, Material citation, Material sample)"
 ]
 }
 }
 ]
}

 The dataset includes 3863 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0084785-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2c3mkz
title: Occurrence Download

description: A dataset containing 136 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Asia",
 "Country is Indonesia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Macaca fascicularis (Raffles, 1821)"
 ]
}

 The dataset includes 136 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0329535-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.