cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/mdepnh/kbpgu8
title: 20170625_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/kp7ezy
title: 20170519_KHO_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/q7cqbm
title: 20180503_BJN_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/rhzbcx
title: 20180420_BJN_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/xxibss
title: 20180714_BJN_REDOBS_gps.txt
DOI: 10.13130/rd_unimi/ddgjj6/3twdiu
title: Maggio_1922_Pagina_044.jpg

description: Bulletin of 1922/05/08
DOI: 10.18710/mdepnh/8gjjd5
title: 20170623_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/9alqpg
title: 20171114_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/htzm0i
title: 20170820_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/rajgww
title: 20170621_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/rqgqtq
title: 20171127_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/tbvuid
title: 20171027_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/um4fof
title: 20170725_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/uw7cxc
title: 20170630_KHO_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/jnh1rp
title: 20181126_BJN_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/ptu42k
title: 20180908_BJN_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/0bcugf
title: 20170626_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/5l0nxh
title: 20171217_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/9bdxdg
title: 20170709_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/hawzxg
title: 20170530_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/meeepo
title: 20170311_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/qnv4dy
title: 20170202_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/vfjpo1
title: 20170901_HOP_REDOBS_gps.txt
DOI: 10.13130/rd_unimi/ddgjj6/jte3ez
title: Maggio_1922_Pagina_045.jpg

description: Bulletin of 1922/05/08
DOI: 10.18710/mdepnh/7rpc3r
title: 20171226_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/hickaw
title: 20170329_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/hvpnf8
title: 20170525_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/l894hd
title: 20170401_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/xyxalg
title: 20170118_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/yrocuf
title: 20170101_KHO_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/03kjb9
title: 20180924_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/cixwhv
title: 20181118_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/gm7hly
title: 20180415_BJN_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/i8vjnq
title: 20180214_BJN_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/izxogq
title: 20181030_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/jmvlo4
title: 20181220_BJN_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/s1aqzz
title: 20180215_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/yxyvom
title: 20180701_BJN_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/42f9dr
title: 20170421_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/4ewcbn
title: 20170420_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/5na5kz
title: 20170629_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/9limlv
title: 20170320_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/fwckqx
title: 20170612_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/h2shi7
title: 20170426_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/irkjdj
title: 20171214_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/junsfi
title: 20170514_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/l3l8dk
title: 20170718_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/mne8lq
title: 20170627_HOP_REDOBS_glo.txt
DOI: 10.18710/zhmbuq/oanmac
title: 20171030_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/qn6dfg
title: 20171206_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/r5bi0r
title: 20171118_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/t33qfy
title: 20170524_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/tuivze
title: 20170119_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/vhsvsa
title: 20170123_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/z6cokz
title: 20170419_HOP_REDOBS_glo.txt
DOI: 10.13130/rd_unimi/ddgjj6/e6y8zv
title: Maggio_1922_Pagina_046.jpg

description: Bulletin of 1922/05/08
DOI: 10.18710/mdepnh/a7o6xu
title: 20170224_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/pnb7sr
title: 20170807_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/s6b398
title: 20170616_KHO_REDOBS_glo.txt
DOI: 10.13130/rd_unimi/ddgjj6/abotwi
title: Maggio_1922_Pagina_047.jpg

description: Bulletin of 1922/05/08
DOI: 10.13130/rd_unimi/lxn1qi
title: ReData: 1923 - Daily meteorological bulletins edited by the Italian Royal Central Meteorological Office

description: This dataset contains the daily meteorological bulletins edited by the Italian Royal Central Meteorological Office relative to the year 1923
description: The scans of the bulletins from UniMi were carried out between 2016 and 2025 by the Garon private company; the remaining scans were completed in February 2025 as part of the “Dieci e Lode” project, funded by the Italian Ministry of Culture (https://aisam.eu/progetti/10-e-lode-en/, accessed on 1st July 2025).
description: Most of the scans (about 95%) were made from bulletins archived at the Department of Environmental Science and Policy of UniMi, while the remaining scans were obtained from bulletins preserved at the Central Historical Library of the Collegio Romano in Rome.
description: To cite this dataset, please refer to the dataset citation of the central ReData dataset: Ceppi Alessandro; Manara Veronica; Brugnara Yuri; Buccheri Gabriele; Caruso Goffredo; Cerri Luca; Di Giovanni Maria; Giazzi Marco; Luperi Ludovico Lapo; Ronca Luca; Sogno Elisa; Maugeri Maurizio, 2025, "ReData: daily meteorological bulletins edited by the Italian Royal Central Meteorological Office from 1879 to 1940", https://doi.org/10.13130/RD_UNIMI/R1GVKF, UNIMI Dataverse
DOI: 10.18710/mdepnh/0lnu5a
title: 20170810_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/0tldyy
title: 20171106_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/1fcijf
title: 20170206_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/1xm69g
title: 20170527_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/2zn6gd
title: 20170517_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/31udm7
title: 20171019_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/3td5ax
title: 20171026_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/3y2ngi
title: 20171229_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/4h1fmc
title: 20171012_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/4wbiwh
title: 20170412_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/5bzgmw
title: 20170901_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/5dnggz
title: 20170525_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/aoxbvn
title: 20170814_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/asexoi
title: 20171016_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/byodg8
title: 20170416_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/cc001z
title: 20170710_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/d93jod
title: 20170905_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/fagji0
title: 20170906_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/g1hand
title: 20170304_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/gdiemd
title: 20171029_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/gh5jy1
title: 20170629_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/gj8xuo
title: 20170923_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/hdeelc
title: 20171208_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/hokf5w
title: 20170627_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/je3huc
title: 20170928_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/jjqi3i
title: 20170930_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/k9edz5
title: 20171023_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/kukgcm
title: 20170924_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/l80nrf
title: 20170313_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/meunt1
title: 20170304_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/mtyz7w
title: 20171020_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/mwlv6u
title: 20170417_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/o1kwgi
title: 20170804_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/o7qyls
title: 20171128_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/oxwxhd
title: 20170203_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/p8pnn6
title: 20170531_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/qarz80
title: 20171031_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/qsf3rw
title: 20171019_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/sqz1q8
title: 20171121_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/u6n9cs
title: 20170622_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/vlmgdj
title: 20170708_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/wcbtz3
title: 20170408_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/wwjcfz
title: 20170415_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/xrw1a9
title: 20170119_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/yu39wt
title: 20170530_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/zhfxql
title: 20170524_KHO_REDOBS_gps.txt
DOI: 10.13130/rd_unimi/ddgjj6/x9sn6t
title: Maggio_1922_Pagina_048.jpg

description: Bulletin of 1922/05/08
DOI: 10.18710/mdepnh/ua20ys
title: 20170914_KHO_REDOBS_glo.txt
DOI: 10.13130/rd_unimi/ddgjj6/bcn6df
title: Maggio_1922_Pagina_049.jpg

description: Bulletin of 1922/05/09
DOI: 10.13130/rd_unimi/ddgjj6/ueggjx
title: Maggio_1922_Pagina_050.jpg

description: Bulletin of 1922/05/09
DOI: 10.18710/mdepnh/0obyhn
title: 20170924_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/1kpgie
title: 20170614_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/2jttx4
title: 20170121_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/2sgpcc
title: 20170511_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/6jhgie
title: 20170806_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/b7xepr
title: 20170413_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/bzb4xi
title: 20170907_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/fzhqwk
title: 20171005_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/gcbs9n
title: 20170906_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/hktum1
title: 20170403_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/imfx91
title: 20170727_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/nd5rtb
title: 20170501_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/nscnen
title: 20170409_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/p6rujq
title: 20171106_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/qsxsgr
title: 20170604_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/qwv4hd
title: 20170803_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/suxqn4
title: 20170812_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/w1xbvn
title: 20170913_KHO_REDOBS_gps.txt
DOI: 10.18710/mdepnh/ydi6yo
title: 20170516_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/ym1cik
title: 20170410_KHO_REDOBS_glo.txt
DOI: 10.18710/mdepnh/yosnxu
title: 20170823_KHO_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/3rxvon
title: 20180508_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/b875iq
title: 20180616_BJN_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/fbpv9o
title: 20180206_BJN_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/fimik3
title: 20180216_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/itfyli
title: 20180821_BJN_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/mergb2
title: 20180327_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/rxebl2
title: 20180811_BJN_REDOBS_gal.txt
DOI: 10.18710/vy1rdy/tde5iq
title: 20180630_BJN_REDOBS_gps.txt
DOI: 10.18710/vy1rdy/v5vqyp
title: 20180726_BJN_REDOBS_glo.txt
DOI: 10.18710/vy1rdy/yzshee
title: 20180217_BJN_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/cncbnq
title: 20170106_HOP_REDOBS_gps.txt
DOI: 10.18710/zhmbuq/jlpq29
title: 20170911_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/sevyt8
title: 20170612_HOP_REDOBS_gal.txt
DOI: 10.18710/zhmbuq/zndori
title: 20170926_HOP_REDOBS_glo.txt
DOI: 10.13130/rd_unimi/ddgjj6/wu4axe
title: Maggio_1922_Pagina_051.jpg

description: Bulletin of 1922/05/09
DOI: 10.18710/mdepnh/adklbu
title: 20170704_KHO_REDOBS_gal.txt
DOI: 10.18710/mdepnh/fw5e7u
title: 20170820_KHO_REDOBS_glo.txt
DOI: 10.5281/zenodo.15623434
title: BPC: A Benchmark Dataset for Causal Business Process Reasoning

description: Large Language Models (LLMs) are increasingly used for boosting organizational efficiency and automating tasks.

While not originally designed for complex cognitive processes, recent efforts have further extended to employ LLMs in activities such as reasoning, planning,

and decision-making. In business processes, such abilities could be invaluable for leveraging the massive corpora LLMs have been trained on for gaining a deep understanding of such processes. In adherence to this goal, we attach here the BP^C dataset, a newly developed set of process-aware Q&A that can be used to assess the ability of LLMs to reason about causal and process perspectives of business operations.

We refer to this view as Causally-augmented Business Processes (BP^C). The benchmark comprises a set of domain-specific BP^C related situations,

a set of questions about these situations, and a set of ground truth answers to these questions.

Reasoning on BP^C is of crucial importance for process interventions and process improvement.

The benchmark could be used in one of two possible modalities: testing the performance of any target LLM and training an LLM to advance its capability to reason about BP^C.
DOI: 10.5281/zenodo.15623435
title: BPC: A Benchmark Dataset for Causal Business Process Reasoning

description: Large Language Models (LLMs) are increasingly used for boosting organizational efficiency and automating tasks.

While not originally designed for complex cognitive processes, recent efforts have further extended to employ LLMs in activities such as reasoning, planning,

and decision-making. In business processes, such abilities could be invaluable for leveraging the massive corpora LLMs have been trained on for gaining a deep understanding of such processes. In adherence to this goal, we attach here the BP^C dataset, a newly developed set of process-aware Q&A that can be used to assess the ability of LLMs to reason about causal and process perspectives of business operations.

We refer to this view as Causally-augmented Business Processes (BP^C). The benchmark comprises a set of domain-specific BP^C related situations,

a set of questions about these situations, and a set of ground truth answers to these questions.

Reasoning on BP^C is of crucial importance for process interventions and process improvement.

The benchmark could be used in one of two possible modalities: testing the performance of any target LLM and training an LLM to advance its capability to reason about BP^C.
DOI: 10.7910/dvn/zq5ea3
title: Survey Questionnaire Translated - Survey Experiment

description: This document is an English translation of the questionnaire used for the survey experiment within the project "Unraveling the Paradox of Anticorruption Messaging: Experimental Evidence from a Tax Administration Reform".
DOI: 10.15468/dl.fzp9mq
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Amietia vertebralis (Hewitt, 1927)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((27.1586 -33.5889,28.2048 -32.9007,25.5395 -32.9007,25.5395 -34.1098,25.6468 -34.1222,25.7787 -34.0734,25.7098 -33.9109,25.8639 -33.797,26.4806 -33.8473,27.1586 -33.5889))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030622-250525065834625/datasets/export for details.
DOI: 10.15468/dl.8muj6h
title: Occurrence Download

description: A dataset containing 7781 records in GBIF matching the query:
SELECT
 kingdom,
 kingdomkey,
 phylum,
 phylumkey,
 class,
 classkey,
 "order",
 orderkey,
 family,
 familykey,
 genus,
 genuskey,
 species,
 specieskey,
 "year",
 IF(ISNULL(kingdomkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY kingdomkey, "year")) kingdomcount,
 IF(ISNULL(phylumkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY phylumkey, "year")) phylumcount,
 IF(ISNULL(classkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY classkey, "year")) classcount,
 IF(ISNULL(orderkey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY orderkey, "year")) ordercount,
 IF(ISNULL(familykey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY familykey, "year")) familycount,
 IF(ISNULL(genuskey), NULL, SUM(COUNT(*)) OVER (
 PARTITION BY genuskey, "year")) genuscount,
 COUNT(*) occurrences,
 MIN(GBIF_TEMPORALUNCERTAINTY(eventdate, eventtime)) mintemporaluncertainty,
 MIN(COALESCE(coordinateuncertaintyinmeters, 1000)) mincoordinateuncertaintyinmeters
FROM
 occurrence
WHERE
 occurrence.countrycode = 'KW'
 AND occurrence.occurrencestatus = 'PRESENT'
 AND (occurrence."year" &gt;= 2000 AND occurrence."year" &lt;= 2025)
 AND occurrence.hasgeospatialissues = FALSE
 AND NOT GBIF_STRINGARRAYCONTAINS(occurrence.issue, 'TAXON_MATCH_FUZZY', TRUE)
 AND (occurrence.distancefromcentroidinmeters &gt;= 2000.0 OR occurrence.distancefromcentroidinmeters IS NULL)
 AND NOT occurrence.basisofrecord IN ('FOSSIL_SPECIMEN', 'LIVING_SPECIMEN')
 AND (occurrence.specieskey IS NOT NULL AND occurrence."year" IS NOT NULL)
GROUP BY
 occurrence.kingdom,
 occurrence.kingdomkey,
 occurrence.phylum,
 occurrence.phylumkey,
 occurrence.class,
 occurrence.classkey,
 occurrence."order",
 occurrence.orderkey,
 occurrence.family,
 occurrence.familykey,
 occurrence.genus,
 occurrence.genuskey,
 occurrence.species,
 occurrence.specieskey,
 occurrence."year"

 The dataset's 7781 records were derived from 46 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030607-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kcre3w
title: Occurrence Download

description: A dataset containing 6323842 species occurrences available in GBIF matching the query:
(Query is too complex. Can be viewed on the landing page)

 The dataset includes 6323842 records from 10783 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0030586-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.tn0p12
title: Occurrence Download

description: A dataset containing 44 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Silene alexandrina (Asch.) Danin"
 ]
}

 The dataset includes 44 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024944-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.84hqn5
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((7.13582 46.17306,6.99826 46.06749,7.43973 45.90754,7.98996 45.95552,8.25868 46.34581,8.08593 46.47377,7.13582 46.17306))",
 "TaxonKey is Arabis serpyllifolia Vill."
 ]
}

 The dataset includes 6 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0033234-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.urt3ee
title: Occurrence Download

description: A dataset containing 52 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Glochidion pomiferum Airy Shaw"
 ]
}

 The dataset includes 52 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015273-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.47hkto
title: Occurrence Download

description: A dataset containing 163199 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Plant Specimen in Yunnan, China from Herbarium (PE),Institute of Botany, Chinese Academy of Sciences"
 ]
}

 The dataset includes 163199 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024945-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nwunds
title: Occurrence Download

description: A dataset containing 106 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Rathbunixa sayana (Stimpson, 1860)",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 {
 "not" : {
 "BasisOfRecord" : [
 "is Fossil"
 ]
 }
 },
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is MANAGED"
 ]
 }
 },
 {
 "not" : {
 "EstablishmentMeans" : [
 "is not null"
 ]
 }
 }
 ]
 },
 {
 "or" : [
 "OccurrenceStatus is Present",
 {
 "not" : {
 "OccurrenceStatus" : [
 "is not null"
 ]
 }
 }
 ]
 }
 ]
}

 The dataset includes 106 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0072088-240229165702484/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yw9a74
title: Occurrence Download

description: A dataset containing 34 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Plethodon asupak Mead, Clayton, Nauman, Olson & Pfrender, 2005",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 1000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 34 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015328-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a0v67c
title: Occurrence Download

description: A dataset containing 8022 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Silene nocturna L."
 ]
}

 The dataset includes 8022 records from 90 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024945-160910150852091/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nb8dgs
title: Occurrence Download

description: A dataset containing 126 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((9.54669 55.82381,10.58722 55.82381,10.58722 56.40685,9.54669 56.40685,9.54669 55.82381))",
 "HasGeospatialIssue is false",
 "TaxonKey is Milvus migrans (Boddaert, 1783)",
 "Year 2000-2023"
 ]
}

 The dataset includes 126 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017343-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ty3y65
title: Occurrence Download

description: A dataset containing 304 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Habenaria epipactidea Rchb.f."
 ]
}

 The dataset includes 304 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0015262-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nm5nkz
title: Occurrence Download

description: A dataset containing 116772 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Plant Specimen from Herbarium (IBK) in China, Guangxi Institute of Botany, Chinese Academy of Sciences"
 ]
}

 The dataset includes 116772 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024947-151016162008034/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6ppwq6
title: Occurrence Download

description: A dataset containing 61 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Alouatta discolor (Spix, 1823)"
 ]
}

 The dataset includes 61 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0011549-231120084113126/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.