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

description: A dataset containing 920351 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Pogoniulus chrysoconus (Temminck, 1832), Cinnyris venustus (Shaw, 1799), Passer griseus (Vieillot, 1817), Prinia subflava (Gmelin, 1789), Streptopelia vinacea (J.F.Gmelin, 1789), Musophaga violacea Isert, 1788, Lybius dubius (J.F.Gmelin, 1788), Lophoceros nasutus (Linnaeus, 1766), Treron waalia (F.A.A.Meyer, 1793), Dendropicos goertae (P.L.S.Müller, 1776), Dendropicos fuscescens (Vieillot, 1818), Centropus senegalensis (Linnaeus, 1766), Papio ursinus ursinus, Poneridia semipullata, Kradibia wakefieldi Wiebes, 1993, Kradibia nigricorpus (Girault, 1915), Apocrypta cercaria Ulenberg, 1985, Phauda flammans (Walker, 1854), Agrioglypta itysalis (Walker, 1859), Asota caricae (Fabricius, 1775), Gynaikothrips uzeli (Zimmermann, 1900), Hypsipetes leucocephalus nigerrimus Gould, 1863, Aleurothrixus floccosus (Maskell, 1896), Asota plana lacteata (Butler, 1881), Gynaikothrips ficorum (Marchal, 1908), Serinus canaria (Linnaeus, 1758), Meselatus bicolor Chen, 1999, Eupristina saundersi Grandi, 1916, Encarsia singhiellae Shih & Polaszek, 2015, Encarsia maculiformis Wang, Huang & Polaszek, Encarsia floralis Wang, Huang & Polaszek, Metaphycus gerardi Sugonjaev, 1996, Sirovena costallifera, Odontofroggatia quinifuniculus Feng & Huang, 2010, Philotrypesis taiwanensis Chen, 1999, Sycophila maculifacies Chen, 1999, Ormyrus lini Chen, 1999, Eufroggattisca okinavensis (Ishii, 1934), Philotrypesis okinavensis Ishii, 1934, Sycophila petiolata Chen, 1999, Acophila microcarpa Chen, 1999, Philotrypesis emeryi Grandi, 1926, Sycophila curta Chen, 1999, Walkerella microcarpae Boucek, 1993, Bruchophagus sensoriae Chen, 1999, Sycoscapter moneres, Sycoscapter gajimaru (Ishii, 1934), Micranisa degastris Chen, 1999, Walkerella kurandensis Boucek, 1988, Micranisa yashiroi (Ishii, 1934))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 920351 records from 311 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017121-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p9h02fxb
title: Alaska Fault Trace Mapping, 2021

description: This dataset provides a detailed (1:10,000) digital map of fault and fold traces in Alaska, USA based on features identified in the freely available ArcticDEM 3.0. The fault traces represented in this dataset either revise the location and accuracy of known active faults or folds archived in the USGS Quaternary Fault and Fold Database, or represent the surface traces of active structures not previously recognized.
DOI: 10.34740/kaggle/dsv/11939473
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.15468/dl.a5y4cg
title: Occurrence Download

description: A dataset containing 6821322 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Orthodera novaezealandiae Colenso, 1882, Philaeus chrysops (Poda, 1761), Harmonia axyridis f. spectabilis, Sassacus vitis (Cockerell, 1894), Pyrrhosoma nymphula (Sulzer, 1776), Megafreya sutrix (Holmberg, 1875), Efferia aestuans (Linnaeus, 1763), Pachydiplax longipennis (Burmeister, 1839), Latrodectus geometricus C.L.Koch, 1841, Pseudomantis albofimbriata Stal, 1860, Phidippus putnami (G.W.Peckham & E.G.Peckham, 1883), Phidippus johnsoni (G.W.Peckham & E.G.Peckham, 1883), Argiope trifasciata (Forsskål, 1775), Dioctria hyalipennis (Fabricius, 1794), Paraphidippus aurantius (Lucas, 1833), Menemerus bivittatus (Dufour, 1831), Maratus griseus (Keyserling, 1882), Orthetrum sabina (Drury, 1773), Nephila pilipes (Fabricius, 1793), Piona nodata (O.F.Müller, 1776), Gelastocoris oculatus (Fabricius, 1798), Setophaga petechia petechia, Orthorhyncus cristatus (Linnaeus, 1758), Riccordia maugaeus (Audebert & Vieillot, 1801), Zelus luridus Stål, 1862, Setophaga adelaidae (S.F.Baird, 1865), Agelaius xanthomus (P.L.Sclater, 1862), Dendragapus fuliginosus (Ridgway, 1873), Naphrys pulex (Hentz, 1846), Anas aucklandica (G.R.Gray, 1844), Pelegrina proterva (Walckenaer, 1837), Setophaga kirtlandii (S.F.Baird, 1852), Cicindela repanda Dejean, 1825, Polioptila californica Brewster, 1881, Troglodytes hiemalis Vieillot, 1819, Oporornis agilis (A.Wilson, 1812), Oiceoptoma noveboracense (J.R.Forster, 1771), Camptostoma imberbe P.L.Sclater, 1857, Vermivora cyanoptera Olson & Reveal, 2009, Setophaga palmarum (J.F.Gmelin, 1789), Eulampis holosericeus (Linnaeus, 1758), Cynictis penicillata G, Rhynocoris erythropus (Linnaeus, 1767), Limnothlypis swainsonii (Audubon, 1834), Calcarius mccownii (Lawrence, 1851), Antennaria dioica (L.) Gaertn., Batrachoseps attenuatus (Eschscholtz, 1833), Copsychus malabaricus (Scopoli, 1786), Aythya australis (Eyton, 1838), Setophaga citrina (Boddaert, 1783))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 6821322 records from 3414 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0017124-250515123054153/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14005956
title: Searches for signatures of ultra-light axion dark matter in polarimetry data of the European Pulsar Timing Array

description: Ultra-light axion-like particles (ALPs) can be a viable solution to dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field, acts as an active birefringent medium, altering the polarisation properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarised radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarisation and negligible fluctuations of their polarisation properties. We have searched for the evidence of ALPs in the polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarisation, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequency between $10^{-8}$~Hz and $2\times10^{-8}$~Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant $g_{a\gamma}$, in the same ballpark as other searches, has been obtained in the mass range between $6\times10^{-24}$~eV and $5\times10^{-21}$~eV. We conclude by discussing problems that can limit the sensitivity of our search for ultra-light axions in the polarimetry data of pulsars, and possible ways to resolve them.
DOI: 10.5281/zenodo.14005957
title: Searches for signatures of ultra-light axion dark matter in polarimetry data of the European Pulsar Timing Array

description: Ultra-light axion-like particles (ALPs) can be a viable solution to dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field, acts as an active birefringent medium, altering the polarisation properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarised radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarisation and negligible fluctuations of their polarisation properties. We have searched for the evidence of ALPs in the polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarisation, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequency between $10^{-8}$~Hz and $2\times10^{-8}$~Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant $g_{a\gamma}$, in the same ballpark as other searches, has been obtained in the mass range between $6\times10^{-24}$~eV and $5\times10^{-21}$~eV. We conclude by discussing problems that can limit the sensitivity of our search for ultra-light axions in the polarimetry data of pulsars, and possible ways to resolve them.
DOI: 10.3535/g28-qkg-awq
title: Acer campestre L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/s22-q3c-gps
title: Potentilla reptans L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/9sb-hg6-mc4
title: Poaceae

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/v9c-lkp-eex
title: Euphorbia seguieriana Neck.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dgx-2xs-yxc
title: Drimys winteri J. R. Forst. & G. Forst.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/h65-nvr-lls
title: Dactylis glomerata L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/p3l-l07-6lj
title: Galium humifusum M.Bieb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/3xm-47f-3k2
title: Thymus L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/wn6-38m-x1j
title: Fragaria viridis Duchesne

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/z7p-fgy-4ne
title: Didymopanax morototoni (Aubl.) Decne. & Planch.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lmc-3gh-fg7
title: Iryanthera paraensis Huber

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/460-3g7-exz
title: Bromus scoparius L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/yhm-cmg-k9d
title: Carduus hamulosus Ehrh.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/lgj-4ph-sm2
title: Aethionema saxatile (L.) W. T. Aiton

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/dpy-hp6-ha8
title: Aegilops triuncialis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/mf5-r1p-e4h
title: Vriesea saundersii (Carrière) É.Morren

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/p54-7d4-4v3
title: Bromus tomentellus Boiss.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/x4e-51z-11x
title: Vriesea scalaris É.Morren

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8pl-94z-sm9
title: Achillea millefolium L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/es0-bzz-a66
title: Alyssum alyssoides (L.) L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.26021/canterburynz.29310860
title: XGB Probability (version 0.1): Mapping Wetlands with High Resolution Planet SuperDove Satellite Imagery

description: These datasets represent predictions and associated probabilities using four machine learning methods, associated with collection: Mapping Wetlands with High Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand (10.26021/canterburynz.c.7848596).The following datasets are available:HGB predictionHGB probabilityMLPC predictionMLPC probabilityRandom forest predictionRandom forest probability XGBoost predictionXGBoost probability [this dataset]For details of the models developed, please see the collection and associated paper. The following files are available in each dataset, each representing an area within New Zealand:<b>xxxxx_mmm_prediction.tif</b>: model prediction, encoded as 8-bit integers where 1 is predicted as wetland (&gt;50% probability), and NA (no data) is non-wetland.<b>xxxxx_mmm_probability.tif</b>: model wetland probability, encoded as 16-bit integers, with probability values from 0 to 1 rescaled from 0 to 10,000. Divide the values by 10,000 to obtain probabilities to four decimal places.In the tile filenames, <b>xxxxx</b> refers to the UUID of the grid area, which can be found in the file nzgrid_uuid.gpkg, and <b>mmm</b> is a code which refers to the model used:<b>hgb</b>: histogram gradient boost<b>mlpc</b>: multi-layer perceptron classification<b>rf</b>: random forest<b>xgb</b>: extreme gradient boostingIn addition to the tif images, two virtual raster tile files are included to enable mapping at the national scale:<b>_mmm_prediction.vrt</b><b>_mmm_probability.vrt</b>All tif images are saved using cloud optimised geotiff (COG), which makes them fast to display even at a national level, although increases the data size. Total size is around 700 MB for the prediction datasets, and ~75 GB for the probability datasets.Metadata for the Planet SuperDove imagery used for each pixel of the predictions is available here: https://doi.org/10.26021/canterburynz.29231837.v
DOI: 10.26021/canterburynz.29310860.v1
title: XGB Probability (version 0.1): Mapping Wetlands with High Resolution Planet SuperDove Satellite Imagery

description: These datasets represent predictions and associated probabilities using four machine learning methods, associated with collection: Mapping Wetlands with High Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand (10.26021/canterburynz.c.7848596).The following datasets are available:HGB predictionHGB probabilityMLPC predictionMLPC probabilityRandom forest predictionRandom forest probability XGBoost predictionXGBoost probability [this dataset]For details of the models developed, please see the collection and associated paper. The following files are available in each dataset, each representing an area within New Zealand:<b>xxxxx_mmm_prediction.tif</b>: model prediction, encoded as 8-bit integers where 1 is predicted as wetland (&gt;50% probability), and NA (no data) is non-wetland.<b>xxxxx_mmm_probability.tif</b>: model wetland probability, encoded as 16-bit integers, with probability values from 0 to 1 rescaled from 0 to 10,000. Divide the values by 10,000 to obtain probabilities to four decimal places.In the tile filenames, <b>xxxxx</b> refers to the UUID of the grid area, which can be found in the file nzgrid_uuid.gpkg, and <b>mmm</b> is a code which refers to the model used:<b>hgb</b>: histogram gradient boost<b>mlpc</b>: multi-layer perceptron classification<b>rf</b>: random forest<b>xgb</b>: extreme gradient boostingIn addition to the tif images, two virtual raster tile files are included to enable mapping at the national scale:<b>_mmm_prediction.vrt</b><b>_mmm_probability.vrt</b>All tif images are saved using cloud optimised geotiff (COG), which makes them fast to display even at a national level, although increases the data size. Total size is around 700 MB for the prediction datasets, and ~75 GB for the probability datasets.Metadata for the Planet SuperDove imagery used for each pixel of the predictions is available here: https://doi.org/10.26021/canterburynz.29231837.v
DOI: 10.3535/bsv-kkl-zjy
title: Sophora alopecuroides L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/d95-7ga-sgw
title: Taeniatherum caput-medusae (L.) Nevski

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/872-ntx-nd0
title: Orthophytum gurkenii Hutchison

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/nzs-3nq-4v0
title: Alchemilla raddeana (Buser) Juz.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/98b-x6e-jtf
title: Crepis marschallii (C. A. Mey.) Sch. Bip.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/w6k-q0p-w46
title: Campanula rapunculoides L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/pw7-t0e-6ld
title: Galium rivale (Sm.) Griseb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/ww6-7t4-nyd
title: Aegilops neglecta Req. ex Bertol.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/tmk-cqt-t99
title: Erysimum nevadense Reut.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/4w1-aaw-jd3
title: Poa compressa L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/7cm-rpm-whg
title: Achillea millefolium L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/adh-tpg-5s3
title: Poa trivialis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/z3h-yhp-pn6
title: Allium rotundum L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/0f0-za4-4k1
title: Aegilops triuncialis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/sxr-802-zlz
title: Poa trivialis L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/eph-v86-cbj
title: Nepeta nuda L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/j4y-r8v-r3k
title: Thinopyrum intermedium subsp. intermedium

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vk0-bws-r9e
title: Poaceae

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/113-s1d-l65
title: Eryngium caeruleum M. Bieb.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/22z-cal-g5w
title: Achillea arabica Kotschy

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/js7-wp6-pn6
title: Stipa pennata subsp. pennata

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vs2-m0g-9q9
title: Hypericum hirsutum L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.15468/dl.b6xjdg
title: Occurrence Download

description: A dataset containing 37 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Brassica oleracea",
 "Country is Chile",
 "HasCoordinate is true"
 ]
}

 The dataset includes 37 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0064029-250717081556266/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.3535/2vg-jst-lpg
title: Clusia gardneri Planch. & Triana

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/gpz-qbb-y39
title: Delphinium hispanicum Costa

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/8w2-hrv-vrx
title: Willemetia stipitata (Jacq.) Dalla Torre

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/5jt-bk6-63x
title: Chamaecytisus spinescens subsp. creticus (Boiss. & Heldr.) K.I.Chr.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/vsv-xln-h9w
title: Erysimum nevadense Reut.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/bxq-ayb-ss0
title: Poa badensis Haenke ex Willd.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/q51-cxc-7yf
title: Trifolium pratense L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/0zp-f10-nrl
title: Poa compressa L.

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.3535/5lt-agv-6c6
title: Bowdichia virgilioides Kunth

description: Digital Specimen for the physical specimen hosted at University of Graz.
DOI: 10.26021/canterburynz.29310392
title: RF Probability (version 0.1): Mapping Wetlands with High Resolution Planet SuperDove Satellite Imagery

description: These datasets represent predictions and associated probabilities using four machine learning methods, associated with collection: Mapping Wetlands with High Resolution Planet SuperDove Satellite Imagery: An Assessment of Machine Learning Models Across the Diverse Waterscapes of New Zealand (10.26021/canterburynz.c.7848596).The following datasets are available:HGB predictionHGB probabilityMLPC predictionMLPC probabilityRandom forest predictionRandom forest probability [this dataset]XGBoost predictionXGBoost probabilityFor details of the models developed, please see the collection and associated paper. The following files are available in each dataset, each representing an area within New Zealand:<b>xxxxx_mmm_prediction.tif</b>: model prediction, encoded as 8-bit integers where 1 is predicted as wetland (&gt;50% probability), and NA (no data) is non-wetland.<b>xxxxx_mmm_probability.tif</b>: model wetland probability, encoded as 16-bit integers, with probability values from 0 to 1 rescaled from 0 to 10,000. Divide the values by 10,000 to obtain probabilities to four decimal places.In the tile filenames, <b>xxxxx</b> refers to the UUID of the grid area, which can be found in the file nzgrid_uuid.gpkg, and <b>mmm</b> is a code which refers to the model used:<b>hgb</b>: histogram gradient boost<b>mlpc</b>: multi-layer perceptron classification<b>rf</b>: random forest<b>xgb</b>: extreme gradient boostingIn addition to the tif images, two virtual raster tile files are included to enable mapping at the national scale:<b>_mmm_prediction.vrt</b><b>_mmm_probability.vrt</b>All tif images are saved using cloud optimised geotiff (COG), which makes them fast to display even at a national level, although increases the data size. Total size is around 700 MB for the prediction datasets, and ~75 GB for the probability datasets.Metadata for the Planet SuperDove imagery used for each pixel of the predictions is available here: https://doi.org/10.26021/canterburynz.29231837.v