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.
17,039
datasets available to search
ShareScore release 0.9.0
Dataset results
17,039 results for “Natural”
Fig. 1 in Assessing the natural circulation of canine vector-borne pathogens in foxes, ticks and fleas in protected areas of Argentine Patagonia with negligible dog participation
Fig. 1. Map of Latin America, showing the study areas in the insert. Black circle: Bosques Petrificados National Park; grey circle: Monte León National Park.
Fig. 1 in A newly naturalized species in Korea, Pennisetum flaccidum Griseb. (Poaceae)
Fig. 1. Photograph of Pennisetum flaccidum. A. Habit. B. Collar region. C. Rhizome. D, E. Inflorescence. F-H. Spikelets. Photograph taken on August 30, 2012 at Gunsan, Jeonranbuk-do, Korea.
Fig. 10 in Integrative taxonomy helps to revise systematics and questions the purported cosmopolitan nature of the type species within the genus Diaforobiotus (Eutardigrada: Richtersiusidae)
Fig. 10 Diaforobiotus svalbardicus sp. nov.: eggs seen in PCM: A, D, G focus on egg processes surface; B, E, H focus on egg processes midsections; C, F, I focus on egg surface between processes. Triples A–C, D–F, G–I represent three different eggs photographed with dif-
Fig. 1 in Integrative taxonomy helps to revise systematics and questions the purported cosmopolitan nature of the type species within the genus Diaforobiotus (Eutardigrada: Richtersiusidae)
Fig. 1 Diaforobiotus islandicus (Richters, 1904): habitus and cuticular pores seen in PCM: A adult habitus, dorso-ventral projection (neotype); B, C cuticular pores on dorsal and ventral side of the body, respectively; D pulvinus on the internal surface of leg III. Filled flat arrowheads indicate cuticular bars above the claws in legs I–III. Scale bars inμm
Fig. 8 in Integrative taxonomy helps to revise systematics and questions the purported cosmopolitan nature of the type species within the genus Diaforobiotus (Eutardigrada: Richtersiusidae)
Fig. 8 Diaforobiotus svalbardicus sp. nov.: bucco-pharyngeal apparatus seen in PCM: A dorsal projection of the entire bucco-pharyngeal apparatus; B, C dorsal (B) and ventral (C) views of the oral cavity armature; D, E dorsal (D) and ventral (E) view of macroplacoids. Empty arrows indicate dorsal spikes, filled flat arrowheads indicate the first band of teeth, empty flat arrowheads indicate the second band of teeth, filled indented arrowheads indicate the third band of teeth, empty indented arrowhead indicates the medial tooth in dorsal portion of the third band of teeth whereas filled arrows indicate constrictions in macroplacoids. Scale bars in μm
Fig. 4 in Integrative taxonomy helps to revise systematics and questions the purported cosmopolitan nature of the type species within the genus Diaforobiotus (Eutardigrada: Richtersiusidae)
Fig. 4 Diaforobiotus islandicus (Richters, 1904): eggs seen in PCM: A, C, E focus on egg processes; B, D, F focus on egg surface between processes. Pairs A–B, C–D, E–F represent three different eggs photographed with different focus. Filled flat arrowheads indicate rings of pores surrounding egg processes. Scale bars in μm
Fig. 6 in Integrative taxonomy helps to revise systematics and questions the purported cosmopolitan nature of the type species within the genus Diaforobiotus (Eutardigrada: Richtersiusidae)
Fig. 6 Diaforobiotus svalbardicus sp. nov.: habitus and cuticular pores seen in PCM: A adult habitus, dorso-ventral projection (holotype); B, C cuticular pores on dorsal and ventral side of the body, respectively (holotype). Filled flat arrowheads indicate cuticular bars above the claws in legs I–III. Scale bars in μm
BRAIN Journal-On the Idea of a New Artificial Intelligence Based Optimization Algorithm Inspired From the Nature of Vortex-Figure 1. Working mechanism of the VOA.
<p>As it can be seen from the algorithm steps, the VOA employs simple equations. It is an<br> advantage that the algorithm can be formed and applied within optimization problems whereas<br> alternative algorithms may contain some complex solution steps (This situation may be also an<br> disadvantage for the VOA when it is applied in more difficult optimization problems but while the<br> world is transformed into a ‘strong simplicity’, the VOA may be a practical solution approach).<br> The working mechanism of the VOA can be visualized briefly as like in Figure 1.</p>
Agriculture - General: Natural Resources and Environment 2
<p>Original data comes from a project which takes or took place as part of the DFG priority program “Exploratories for large-scale and long-term functional biodiversity research”. The data is stored together with descriptive metadata, in combination called a dataset, in the project repository (<a href="https://www.bexis.uni-jena.de">https://www.bexis.uni-jena.de</a>). Species information was extracted from that original dataset. The second paragraph is part of the metadata of the original dataset.The soil macrofauna on selected and avaialable EPs and VIPs was sampled in Spring and Autumn 2008 to relate land-use to soil diversity.</p> <p>Birkhofer K (2016). Species Soil Macrofauna 2008. Biodiversity Exploratories. Occurrence dataset <a href="https://doi.org/10.15468/frzxwp">https://doi.org/10.15468/frzxwp</a> accessed via GBIF.org</p>
Agriculture - General: Natural Resources and Environment
<p>Original data comes from a project which takes or took place as part of the DFG priority program “Exploratories for large-scale and long-term functional biodiversity research”. The data is stored together with descriptive metadata, in combination called a dataset, in the project repository (<a href="https://www.bexis.uni-jena.de">https://www.bexis.uni-jena.de</a>). Species information was extracted from that original dataset. The second paragraph is part of the metadata of the original dataset.‘Sammelarten" sind durch agg= Aggregate oder total gekennzeichnet. Sie umfassen jene Taxa, die teilweise bis zur Kleinart, Subspecies oder Varietas bestimmt wurden, teilweise aber auch nur auf Gattungs- (… spec. (indet.)) oder Artebene. Taxonomie nach Wisskirchen,Haeupler (1998)Standardliste für Deutschland. Lebensformen nach Raunkiaer, C. (1910): Statistik der Lebensformen als Grundlage für die biologische Pflanzengeographie.-Beih. Biol. Cbl. 27 II, 170 - 206d. Rote Liste: KORNECK, D., SCHNITTLER, M., VOLLMER, I. (1996): Rote Liste der Farn- und Blütenpflanzen (Pteridophyta et Spermatophyta) Deutschlands. – LUDWIG, G., SCHNITTLER, M. [Hrsg.]: Rote Listen gefährdeter Pflanzen Deutschlands. – Schriftenr. Vegetationskd. 28: 21–187, Bundesamt für Naturschutz, Bonn.’</p> <p>Socher S (2016). vegetation releves on grassland gridplots 2007-2009. Biodiversity Exploratories. Occurrence dataset <a href="https://doi.org/10.15468/dmjxfo">https://doi.org/10.15468/dmjxfo</a> accessed via GBIF.org</p>
Agriculture - General: Natural Resources and Environment, Plant Production and Protection
<p>Original data comes from a project which takes or took place as part of the DFG priority program “Exploratories for large-scale and long-term functional biodiversity research”. The data is stored together with descriptive metadata, in combination called a dataset, in the project repository (<a href="https://www.bexis.uni-jena.de">https://www.bexis.uni-jena.de</a>). Species information was extracted from that original dataset. The second paragraph is part of the metadata of the original <a href="<a href="http://dataset.in/">http://dataset.in/</a>">dataset.In this project we investigate seed bank and bryophyte propagule content in top soil in grasslands. Müller J (2016). Seed bank grassland. Biodiversity Exploratories. Occurrence dataset <a href="https://doi.org/10.15468/jax26w">https://doi.org/10.15468/jax26w</a> accessed via GBIF.org</p>
Data from: Numerical Simulation of the Atmospheric Signature of Artificial and Natural Seismic Events
<p>This data is related to the seismic hammer experiment discussed in "Numerical Simulation of the Atmospheric Signature of Artificial and Natural Seismic Events" by Martire et al. (2018, DOI will be added upon acceptance of the manuscript).</p> <p>The .zip file contains 3 .mseed files, and 1 .txt file. The .mseed are the raw seismometer signals. The .txt details the position of the sensor.</p> <p>Remaining data used in our paper can be found in the repository related to "Detection of Artificially Generated Seismic Signals using Balloon-borne Infrasound Sensor" by Krishnamoorthy et al. (2018, DOI 10.1002/2018GL077481). That repository has DOI 10.6084/m9.figshare.6137507.</p>
Are we overestimating protistan diversity in nature?*
<p><em>*Supplemental information for submitted publication</em>: David A. Caron & Sarah K. Hu. <em>Are we overestimating protistan diversity in nature? </em>In Review. Trends in Microbiology.</p> <p><em><strong>18S rRNA gene tag-sequencing dataset </strong></em></p> <p><em>Summary</em>: Single-celled microbial eukaryotes (protists) fulfill fundamental roles in carbon fixation, energy flow, elemental transfer, decomposition, and diseases in virtually all environments on the planet. Until recently it has been difficult for ecologists to determine the full breadth of protistan species richness in natural communities using the traditional morphology-based taxonomy, but high-throughput sequencing (HTS) of target genes has revealed unprecedented and unexpected species richness. The most common use of HTS is to cluster sequences into approximately species-level designations, often as Operational Taxonomic Units (OTUs); yet, recent estimates of total OTUs appear to be approaching the total number of individual protists in a sample. Thus, are we overestimating protistan diversity in nature? In an effort to explore this question we processed a set of sequences using several common approaches (Figure 1, <em>Schematic_V4tagseqsamples.pdf</em>). A full description of sample collection, processing, and analysis are also available.</p> <p> </p> <p><em>Data availability & contents:</em></p> <ul> <li>All sequence data is publicly available from the Short Read Archive under <strong>SRA ID: SRP110149</strong>. Sequences amplified using the Stoeck et al. (2010) primers are under accession numbers <strong>SAMN07211761- SAMN07211764</strong> and those amplified with the Balzano et al. (2015) primers can be found under <strong>SAMN07211767- SAMN07211770</strong>.</li> <li>QIIME2 artifact files for running closed reference, de novo, and open-reference OTU clustering: derep_table.qza, derep_seqs.qza. To run, you'll need to acquire PR2 database (https://github.com/vaulot/pr2database)</li> <li>QIIME2 artifact files of trimmed reads to run QC and determine Amplicon Sequence Variants: demux_trimmed.qza</li> <li>Schematic_V4tagseqsamples.pdf - representation of sample collection, processing, and analysis (See below for full description).</li> </ul> <p> </p> <p><em>Sample collection and PCR amplification</em></p> <p>Seawater was collected in April 2014 at the San Pedro Ocean time-series station (SPOT; 33°33’N, 118°24’W) from 5 m, the subsurface chlorophyll maximum (SCM, 32 m), 150 m, and 890 m. Water was sequentially pre-filtered through 200 µm and 80 µm mesh to reduce the presence of multicellular eukaryotes (metazoa) and finally vacuum filtered into 47 mm GF/F filters (nominal pore size 0.7 µm; Whatman, International Ltd, Florham Park, NJ, USA) and immediately flash frozen for RNA extractions. Details can be found in Hu <em>et al. </em>(2016) and protocols.io (dx.doi.org/10.17504/protocols.io.hisb4ee).</p> <p>Total extracted RNA was reverse transcribed into cDNA (iScript Reverse Transcription Supermix; Bio-Rad Laboratories, Hercules, CA, USA, #170-8840). cDNA was PCR amplified using either <a href="#_ENREF_3">Stoeck<em> et al.</em> (2010</a>) V4 primers [FWD 5’-CCAGCASCYGCGGTAATTCC-3’, REV 5’- ACTTTCGTTCTTGATYRA-3’] or <a href="#_ENREF_1">Balzano<em> et al.</em> (2015</a>) V4 primers [FWD 5’-CCAGCASCYGCGGTAATTCC-3’, REV 5’- ACTTTCGTTCTTGATYRR-3’], the latter having an extra degenerate nucleotide on the 3’ end of the reverse primer. PCR reactions for both sets of primers were identical, differing only by the added V4 primers, and consisted of 1X Phusion High-Fidelity DNA polymerase (New England Biolabs, Ipswich, MA, USA, #M0530S), 200 µM of dNTPs, 0.5 µM of each V4 forward and reverse primer, 3% DMSO, 50 mM of MgCl, and 5 ng of cDNA starting material.</p> <p>The PCR thermal profile for the <a href="#_ENREF_3">Stoeck<em>, et al.</em> (2010</a>). V4 primers consisted of a 98°C denaturation step for 30 seconds (s), followed by 10 cycles of 10 s at 98°C, 30 s at 53°C, and 30 s at 72°C, and then 15 cycles of 10 s at 98°C, 30 s at 48°C, and 30 s at 72°C, and a final elongation step at 72°C for ten minutes, as described in <a href="#_ENREF_2">Rodríguez-Martínez<em> et al.</em> (2012</a>). The thermal profile for the <a href="#_ENREF_1">Balzano<em>, et al.</em> (2015</a>) PCR reactions was comprised of 98°C denaturation step for 30 seconds (s), followed by 14 cycles of 30 s at 98°C, 30 s at 53°C, and 30 s at 72°C, and then 21 cycles of 30 s at 98°C, 30 s at 53 and 48°C (duplicate reactions run at each temperature), and 30 s at 72°C, and a final elongation step at 72°C for one minute (<a href="#_ENREF_1">Balzano<em>, et al.</em> 2015</a>). PCR products were purified using AMPure XP beads (manufacturer info), quality checked on the Qubit fluormeter (v. 2.0 Life technologies) and Agilent Bioanalyzer (information). Extraction and PCR amplification steps can be found at protocols.io (dx.doi.org/10.17504/protocols.io.hk3b4yn and dx.doi.org/10.17504/protocols.io.hdmb246).</p> <p><em>Sequence analysis</em></p> <p>Raw sequences were quality filtered and clustered into OTUs or ASVs using both QIIMEv1 and v2. Bioinformatic pipelines are available at github (<a href="https://github.com/shu251">https://github.com/shu251</a>). Initial quality control for the QIIMEv1 pipeline consisted of merging paired end sequences, quality filtering (Q>20), V4 primers were removed (cutadapt), and sequence were filtered by length (sequences longer than 500 bps or shorter than 150 bps were removed). In QIIMEv2, V4 primers were removed (cutadapt), sequences were filtered for quality (Q>20), and paired end reads were merged and dereplicated.</p> <p> </p> <p>Before OTU clustering in QIIMEv1, quality checked sequences were combined and chimeras were removed using a reference-based approach (vsearch). Open-reference OTU clustering was conducted (Rideout et al.) with step 4 suppressed. <em>De novo</em> OTU clustering, closed-reference OTU clustering, and Amplicon Sequence Variant (ASV) determination was conducted in QIIMEv2. Following OTU or ASV clustering, chimeras were removed using a reference-based approach (vsearch). For reference-based bioinformatic steps (chimera removal, open-reference OTU clustering, and closed-reference OTU clustering) the Protist Ribosomal 2 database v4.75 (<a href="https://github.com/vaulot/pr2database">https://github.com/vaulot/pr2database</a>) was used. OTU or ASV tables were compiled in R and all code is available at github (https://github.com/shu251).</p> <p><strong>References</strong></p> <p>Balzano S, Abs E, Leterme SC. 2015. Protist diversity along a salinity gradient in a coastal lagoon. Mar 25;74:263-277.</p> <p>Hu, S. K. and others 2016. Protistan diversity and activity inferred from RNA and DNA at a coastal ocean site in the eastern North Pacific. FEMS Microbiol. Ecol. <strong>92: </strong>1-13.</p> <p>Rodríguez-Martínez R, Rocap G, Logares R, Romac S, Massana R. 2012. Low evolutionary diversification in a widespread and abundant uncultured protist (MAST-4). Mol Biol Evol. May 01;29:1393-1406.</p> <p>Stoeck T, Bass D, Nebel M, Christen R, Jones MDM, Breiner H-W, Richards TA. 2010. Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Ecol. Mar 01;19:21-31.</p>
Herbarium specimen image of Tectaria incisa, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Pellaea rotundifolia, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Pteris cretica, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Pteris cretica, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Osmunda regalis, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Microlepia setosa, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
Herbarium specimen image of Adiantum aleuticum, part of the collection of Finnish Museum of Natural History LUOMUS, University of Helsinki
Part of a training dataset of scanned herbarium specimens. The data paper and a summary landing page will be published on Zenodo as it gets published.<br><br>Content of this deposition:<br><br>- A JSON-LD datafile listing the label data associated with this herbarium specimen. The Darwin and Dublin Core data standards are used for most values.<br>- A JPEG image file of the scanned herbarium sheet.<br>- A lossless TIFF image from which the JPEG image has been derived.
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.