Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
773
datasets available to search
ShareScore release 0.9.0
Dataset results
773 results for “Orchid”
Wild for Orchids Citizen Science Campaign Records 2020 - 2023
<p>This dataset represents the geographic distribution of wild orchids in the Maltese Islands, as recorded by the Wild For Orchids Citizen Science Initiative between January 2020 and December 2023. It includes data obtained through citizen science contributions and has undergone rigorous two-stage quality control for species identification and GPS accuracy. Species identification was carried out according to Mifsud (2018). The location data of each records is provided as a shapefile format projected in ETRS89-extended / LAEA Europe (EPSG:3035), and exact GPS location were transformed in 1 km square grid according to the <span>European Forum for Geography and Statistics (EFGS).<br></span></p> <p><span>Wild for Orchids is a Citizen Science Initiative designed and managed by Green House Malta.</span></p>
DeepOrchidSeries: A Sentinel-2 Dataset to inform convolutional SDMs with twelve-month Sentinel-2 image time-series, Orchid family
<p><strong>Deep Species Distribution Modelling from Sentinel-2 Image Time-series: a Global Scale Analysis on the Orchid Family</strong> </p> <ul> <li><strong><em>DeepOrchidSeries</em></strong> dataset gathers Sentinel-2 image time-series around geolocated orchid occurrences. Seasonal evolutions of the habitats are captured in the twelve-month RGB/IR time-series with 640x640m spatial resolution. It allows novel Species Distribution Models (SDMs) coupled with convolutional networks to take advantage of both spatial and temporal information.</li> <li>Our <strong>associated article</strong> is describing the modeling choices made to shape this ambitious dataset. It is submitted to <a href="https://www.frontiersin.org/research-topics/18336/plant-biodiversity-science-in-the-era-of-artificial-intelligence">https://www.frontiersin.org/research-topics/18336/plant-biodiversity-science-in-the-era-of-artificial-intelligence</a>. We believe such global data, methods and scripts are valuable to the conservation ecology community and especially deep-SDMs users. To our knowledge, no similar ready-to-use dataset is available. In the article, the dataset's temporal dimension is proven to significantly improve SDMs performances.</li> <li><strong><em>sen2patch</em></strong> is the gitlab project gathering the code to create such dataset. It is available at <a href="https://gitlab.inria.fr/jestopin/sen2patch">https://gitlab.inria.fr/jestopin/sen2patch</a>.</li> <li><strong><em>DeepOrchidSeries.csv</em></strong> contains all occurrences-level information. <ul> <li>We advice to load it with: <pre><code class="language-python">import pandas as pd df = pd.read_csv("path/to/DeepOrchidSeries.csv", sep=';') df.columns ['gbifid', 'canonical_name', 'decimallatitude', 'decimallongitude', 'speciesKey', 'cell_index', 'bot_country', 'bot_code', 'lvl2_code', 'continent_code']</code></pre> <ul> <li>'gbifid' is the occurrences GBIF ID</li> <li>'canonical_name', is the species canonical name</li> <li>'decimallatitude', 'decimallongitude' are the species coordinates in decimal degrees</li> <li>'speciesKey' is the species GBIF unique identifier</li> <li>'cell_index' is a unique cell ID in a 0.0025° lon/lat grid partitioning the Earth (used to stratify train/val/test set by geographic blocks)</li> <li>'bot_country', 'bot_code', 'lvl2_code', 'continent_code' are geographic subdivisions defined in <a href="https://github.com/tdwg/wgsrpd">https://github.com/tdwg/wgsrpd</a> (code and string for WGSRPD level 1, the botanical countries)</li> </ul> </li> </ul> </li> <li> <p>Initial <a href="https://www.gbif.org/">GBIF</a> query DOI is <a href="http://https://doi.org/10.15468/dl.4bijtu">https://doi.org/10.15468/dl.4bijtu</a> (26 August 2019).</p> </li> <li><strong><em>DeepOrchidSeries.tar</em></strong> file contains the satellite image time-series and is available at <a href="https://lab.plantnet.org/deeporchidseries/">https://lab.plantnet.org/deeporchidseries/</a> <ul> <li><em>.tar</em> archive measure 286 GB and extends to 432 GB once decompressed.</li> <li>Image time-series relative tree paths are constructed from the occurrences unique GBIF IDs.</li> <li>For a given occurence <em>gbifid</em>, matching patches are located in: <em>final_dataset_by_gbifid/gbifid[-2:]/gbifid[-4:-2]</em>, <em>i.e.</em> in a first folder named with the <em>gbifid</em> last two numbers and a subfolder with the previous two ones. Example: the time-series files matching occurrence 2236837714 are located at <em>final_dataset_by_gbifid/14/77/</em>. </li> <li>Image time-series are composed of twelve 16 bits RGB <em>.png</em> and twelve 16 bits IR <em>.png</em> files containing data identical to the original L1C products, no lossy compression was made. There are one RGB and one IR .png file per month.</li> <li>Patches from month MM/YYYY of occurrence <em>gbifid</em> are named<em> </em><em>RGB_YYYY_MM_gbifid_.png</em> and <em>IR0_YYYY_MM_gbifid_.png</em>.</li> </ul> </li> <li><em><strong>models.zip</strong></em> is the archive containing the four PyTorch models weights described in our article and<strong><em> </em></strong><em><strong>inception_env.py</strong></em> the used Inception V3 architecture. <em><strong>index.json</strong></em> contains the dictionnary linking the models class indexes from 0 to 14128 with our labels <em>speciesKey</em>: {"class_index":speciesKey}.</li> </ul> <p> </p> <ul> <li><strong>ACKNOWLEDGMENTS</strong>: We warmly thank Alexander Zizka et al. for providing us the geographically and taxonomically curated set of Orchids occurrences. This dataset contains modified Copernicus Sentinel data and Copernicus Service information (2018). Sentinel-2 MSI data used were available at no cost from ESA Sentinels Scientific Data Hub.</li> </ul>
Data release for "OrchID: a Generalized Framework for Taxonomic Classification of Images Using Evolved Artificial Neural Networks"
<p><strong>Abstract</strong></p> <p>Taxonomic expertise for the identification of species is rare and costly. On-going advances in computer vision and machine learning have led to the development of numerous semi- and fully automated species identification systems. However, these systems are rarely agnostic to specific morphology, rarely can perform taxonomic “approximation” (by which we mean partial identification at least to higher taxonomic level if not to species), and frequently rely on costly scientific imaging technologies.</p> <p>We present a generic, hierarchical identification system for automated taxonomic approximation of organisms from images. We assessed the effectiveness of this system using photographs of slipper orchids (Cypripedioideae), for which we implemented image pre-processing, segmentation, and colour and shape feature extraction algorithms to obtain digital phenotypes for 116 species. The identification system trained on these digital phenotypes uses a nested hierarchy of artificial neural networks for pattern recognition and automated classification that mirrors the Linnean taxonomy, such that user-submitted photos can be assigned a genus, section, and species classification by traversing this hierarchy.</p> <p>Performance of the identification system varied depending on photo quality, number of species included for training, and desired taxonomic level for identification. High quality photos were scarce for some taxa and were under-represented in the training set, resulting in imbalanced network training. The image features used for training were sufficient to reliably identify photos to the correct genus but less so to the correct section and species.</p> <p>The outcomes of this project include a library of feature extraction algorithms called <em>ImgPheno</em>, a collection of scripts for neural network training called <em>NBClassify</em>, a library for evolutionary optimization of artificial neural network construction called <em>AI::FANN::Evolving</em> and a planned web application called <em>OrchID</em> for identification of user-submitted images. All project outcomes are open source and freely available.</p> <p><strong>About this release</strong></p> <p>This release corresponds belongs with our response to the reviewers of PLoS One. At this stage of the review cycle the manuscript is assessed as 'minor revision'. Consequently, we don't anticipate making more releases until publication.</p>
Lineage and role in integrative taxonomy of a heterotrophic orchid complex
<p>Lineage-based species definitions applying coalescent approaches to species delimitation have become increasingly popular. Yet, the application of these methods and the recognition of lineage-only definitions have recently been questioned. Species delimitation criteria that explicitly consider both lineages and evidence for ecological ‘role’ shifts provide an opportunity to incorporate ecologically meaningful data from multiple sources in studies of species boundaries. Here, such criteria were applied to a problematic group of mycoheterotrophic orchids, the <em>Corallorhiza striata</em> complex, analyzing genomic, morphological, phenological, reproductive-mode, niche, and fungal host data. A recently developed method for generating genomic polymorphism data–ISSRseq–demonstrates evidence for four distinct lineages, including a previously unidentified lineage in the Coast Ranges and Cascades of California and Oregon, USA. There is divergence in morphology, phenology, reproductive mode, and fungal associates among the four lineages. Integrative analyses, conducted in population assignment and redundancy analysis frameworks, provide evidence of distinct genomic lineages and a similar pattern of divergence in the ‘extended’ data, albeit with weaker signal. However, none of the ‘extended’ datasets fully satisfy the condition of a significant ‘role’ shift, which requires evidence of fixed differences. The four lineages identified in the current study are recognized at the level of variety, short of comprising different species. This study represents the most comprehensive application of ‘lineage+role’ to date and illustrates the advantages of such an approach.</p>
Figs. 17–20 in Description of a new species of Anthocoris (Hemiptera: Heteroptera: Anthocoridae) from southern India, associated with striped mealybug on purple orchid tree
Figs. 17–20. Anthocoris muraleedharani Yamada, sp. nov. 17 – adult habitus; 18 – mature nymph feeding on solenopsis mealybug; 19 – young nymph feeding on solenopsis mealybug; 20 – eggs inserted into plant tissue (arrows show exposed operculum of egg).
Figs. 1–6 in Description of a new species of Anthocoris (Hemiptera: Heteroptera: Anthocoridae) from southern India, associated with striped mealybug on purple orchid tree
Figs. 1–6. Anthocoris muraleedharani Yamada, sp. nov., paratypes, male (1–2, 5–6) and female (3–4). 1 – head and pronotum, dorsal view; 2–3 – antennae; 4 – left fore wing, dorsal view; 5 – ostiolar peritreme and evaporatorium, left lateroventral view; 6 – abdominal sterna II–III, ventral view. Scale bars = 0.5 mm for 1–4, 6; 0.1 mm for 5.
Figs. 12–16 in Description of a new species of Anthocoris (Hemiptera: Heteroptera: Anthocoridae) from southern India, associated with striped mealybug on purple orchid tree
Figs. 12–16. Anthocoris muraleedharani Yamada, sp. nov. 12–13 – habitus of holotype, dorsal and lateral views; 14–15 – head and pronotum, male (14) and female (15), dorsal view; 16 – ostiolar peritreme and evaporatorium, female, left lateroventral view. Scale bars = 1.0 mm for 12–13; 0.5 mm for 14–15: 0.1 mm for 16.
Raw data and scripts from de Lima et al. Succulence explains salinity tolerance in a Neotropical orchid without any evidence of local adaptation to salt spray
Open the record for dataset details and reuse information.
Beyond the various contrivances by which orchids are pollinated: global patterns in orchid pollination biology
<p>Global database of Orchidaceae to explore the frequency of different breeding systems, means of pollinator attraction, and pollinator diversity, and how these features vary geographically and by growth habit.</p> <p>Two files: </p> <p>Pollination List Literature Cited thru 2024 (word file)</p> <p>Pollination List thru 2024 (excel file)</p>
Figs 10–15 in A new species of Cephaloleia from Panama with description of larva and first record of orchid-feeding in Cephaloleiini (Coleoptera: Chrysomelidae: Cassidinae)
Figs 10–15. Egg and larva of Cephaloleia orchideivora sp. nov. 10 – egg containing nearly fully developed larva on Oerstedella leaf; 11 – freshly emerged first instar larva, live and prior to feeding; 12 – second instar larva fully grown; 13 – dissected head of first instar larva showing the location and conformation of the stemmata; 14 – mandible dissected, embedded in Hoyers medium and viewed through a compound microscope; a fourth tooth, deeper in the preparation and less focused appears between the second and third teeth; 15 – lateral view of the opposing mandible and its shallowly lobed teeth and concave mesal surface. All scale bars equal to 1 mm.
Figs 16–21 in A new species of Cephaloleia from Panama with description of larva and first record of orchid-feeding in Cephaloleiini (Coleoptera: Chrysomelidae: Cassidinae)
Figs 16–21. Larva of Cephaloleia orchideivora sp. nov. 16 – first abdominal spiracle; 17 – lateral view of head (second instar); 18 – ventral surface of same head, maxilla, maxillary palps, labium and labial palps, antenna and clypeus (lacking setal fringe); 19 – maxilla; 20 – apical segment of the antenna; 21 – leg.
Figs 1–3 in A new species of Cephaloleia from Panama with description of larva and first record of orchid-feeding in Cephaloleiini (Coleoptera: Chrysomelidae: Cassidinae)
Figs 1–3. Cephaloleia orchideivora sp. nov. 1 – dorsal aspect (Chiriquí population); 2 – ventral aspect; 3 – dorsal aspect (Cerro Jefe population).
Figures 2–5 in First record of the orchid bee Euglossa dilemma (Hymenoptera: Apidae) in Hispaniola, the Antilles
Figures 2–5. Males of Euglossa dilemma in the Cordillera Septentrional, Dominican Republic. 2–3) Gathering compounds from basil aromatic leaves (Ocimum basilicum). 4) Group collecting fragrances. 5) Attracted to a tissue containing clove oil (Syzygium aromaticum), placed in the basil plant area. Photos: Lisa McDowell Johnson.
Figure 1 in First record of the orchid bee Euglossa dilemma (Hymenoptera: Apidae) in Hispaniola, the Antilles
Figure 1. Map of Hispaniola showing the occurrence point (latitude 19.644207, longitude −70.857325) of Euglossa dilemma in the Cordillera Septentrional of Dominican Republic.
Figures 2–7. Cayman Islands Sphingidae. 2 in A checklist of the hawkmoths (Lepidoptera: Sphingidae) of the Cayman Islands: with implications for the pollination of the ghost orchid Dendrophylax fawcettii Rolfe (Orchidaceae: Angraecinae) and consideration of bat predation
Figures 2–7. Cayman Islands Sphingidae. 2) Isognathus rimosa. 3) Erinnyis obscura. 4) Phryxus caicus. 5) Predation of Pachylia ficus larva by Mangrove Cuckoo, Coccyzus minor. 6) Pachylia ficus. 7) Enyo lugubris. Photographic credits: M.C. Rose-Smyth (2, 27.i.2017; 3, 08.viii.2018; 4, 24.xiii.2015, 6, 05.iv.2018; 7, 13.ii.2018), Yves-Jacques Rey-Millet (5, 29.xii.2012).
Figures 8–11. Cayman Islands Sphingidae. 8 in A checklist of the hawkmoths (Lepidoptera: Sphingidae) of the Cayman Islands: with implications for the pollination of the ghost orchid Dendrophylax fawcettii Rolfe (Orchidaceae: Angraecinae) and consideration of bat predation
Figures 8–11. Cayman Islands Sphingidae. 8) Eumorpha vitis. 9) Eumorpha fasciatus. 10) Eumorpha satellitia posticatus. 11) Xylophanes tersa. Photographic credits: Stuart Mailer (8, 12.v.2010), Peter and Norma Davey (9, 10.ii.2018), Gary J. Goss (10, 26.vi.2017), M.C. Rose-Smyth (11, NTCI collection).
Figure 1 in A checklist of the hawkmoths (Lepidoptera: Sphingidae) of the Cayman Islands: with implications for the pollination of the ghost orchid Dendrophylax fawcettii Rolfe (Orchidaceae: Angraecinae) and consideration of bat predation
Figure 1. Collection and observation locations in the Cayman Islands. Little Cayman: 1. Nature Trail; 2. Stonewall Dr., Spyglass Hill; 3. Pirates Point; 4. South Town (Blossom Village); 5. Cross the Land Road (now Guy Banks); 6. Central Forest, south of Sparrowhawk Hill; 7. Coppice Rd. Cayman Brac: A. West End (Cotton Tree Land); B. Stake Bay (Stakes Bay in Jordan 1940); C. Arlin Reid Drive; D. Earthquake Hole; E. Spot Bay; E1. Lighthouse Trail. Grand Cayman: F. West Bay; G. Crystal Harbour; H. George Town (Georgetown in Jordan 1940); I. Ocean Club; J. Newlands; K. North Sound Estates; L. Savannah; M. Agricultural Grounds/Pavilion/Lottery Rd.; N. Valley Gardens; O. Bodden Town; P. High Rock; Q. East End; R. Colliers Wilderness Reserve; S. Queen Elizabeth II Botanic Park; T. Old Man Bay; U. Mastic Trail; V. Hutland (Hut Rd.); W. North Side; X. North Sound, Booby Cay (Booby Bay in Jordan 1940).
Figure 12 in A checklist of the hawkmoths (Lepidoptera: Sphingidae) of the Cayman Islands: with implications for the pollination of the ghost orchid Dendrophylax fawcettii Rolfe (Orchidaceae: Angraecinae) and consideration of bat predation
Figure 12. Tongue lengths of twenty of the twenty-three species of hawkmoth found in Grand Cayman, plus that of Dolba hyloeus. Data from: Miller (1997) supplemented by Haber and Frankie (1989), Houlihan et al. (2019): and Danaher et al. (2019). Species are grouped by "pollinia carriers" and "visitors to flowers" in Florida, according to Houlihan et al. (2019) and Danaher et al. (2019) and "not observed". Colour codes are: red = species not occurring in Grand Cayman; blue = species occurring in Grand Cayman.
Figure 4 in Dactylorhiza Fuchsii (Druce) Soó As A Model Object In In Vitro Culture Study For Development Of Terrestrial Orchids
Figure 4. Root of D. fuchsii growing in the Figure 5. Root of D. fuchsii one year after exposition in NBG: arrow indicates elaborate transplanting ex vitro: arrow indicates some coiled structures known as pelotons of peloton-like structure as they do within the orchid mycorrhizal fungi in the root cortex (section was cells (section was stained with Trypan Blue; bar stained with Trypan Blue; bar = 50 mm) = 50 mm).
Figure 1 in Dactylorhiza Fuchsii (Druce) Soó As A Model Object In In Vitro Culture Study For Development Of Terrestrial Orchids
Figure 1. Development of Dactylorhiza fuchsii (Druce) Soó in vitro conditions: A – beginning of morphogenesis after germination with development of protocorms, characteristic for orchids; B – initialization of rooting; C – sterile plantlets after exposition at 2 °C in the dark, simulating the natural dormancy period; D – plantlet before transplanting ex vitro (ro – root; tu – tuber).
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.