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.
1,838
datasets available to search
ShareScore release 0.9.0
Dataset results
1,838 results for “location”
Text-fig. 1. Geographic location of the studied sections. 1. Gaverdovsky, 2. Volchaya Balka, 3. Tuapse highway bridge, 4. Maikop city park. in Late Miocene (Early Turolian) Vertebrate Faunas And Associated Biotic Record Of The Northern Caucasus: Geology, Taxonomy, Palaeoenvironment, Biochronology
Text-fig. 1. Geographic location of the studied sections. 1. Gaverdovsky, 2. Volchaya Balka, 3. Tuapse highway bridge, 4. Maikop city park.
Text-fig. 1. Map of Germany with outline of North Rhine- Westphalia indicated; detailed map with sample locations (asterisks), motorways and major cities. in Everything Is A Question Of Time - Age Of Important Quaternary Palaeontological Finds From Westphalia
Text-fig. 1. Map of Germany with outline of North Rhine- Westphalia indicated; detailed map with sample locations (asterisks), motorways and major cities.
Text-fig. 1. Location of fossiliferous localities in the Ashawq Formation in south-western Oman (the star labelled Thaytiniti shows the area depicted in Text-fig. 2). in Large Mammals From The Rupelian Of Oman - Recent Finds
Text-fig. 1. Location of fossiliferous localities in the Ashawq Formation in south-western Oman (the star labelled Thaytiniti shows the area depicted in Text-fig. 2).
Text-fig. 1. Map of Southwest England indicating general and detailed location of the Watchet to St. Audries Bay area on the West Somerset coast. in 'Cenoceras Islands' In The Blue Lias Formation (Lower Jurassic) Of West Somerset, Uk: Nautilid Dominance And Influence On Benthic Faunas
Text-fig. 1. Map of Southwest England indicating general and detailed location of the Watchet to St. Audries Bay area on the West Somerset coast.
Text-fig. 1. Schematic maps showing location of the Prague Basin in the Barrandian area of the Czech Republic (a), the Koněprusy area (b), quarries in the Koněprusy area (c) and Jirásek's and Preisler's quarries (d). The exact location of the section described by Hladil et al. (1993) (1) and the new sections where the brachiopods were extracted (2) are figured. Abbreviations: UDI – upper dark interval, VČS-E – Velkolom Čertovy schody – východ quarry. in Rhynchonelliform Brachiopods And Trilobites Of The 'Upper Dark Interval' In The Koněprusy Area Devonian, Eifelian, Kačák Event; The Czech Republic
Text-fig. 1. Schematic maps showing location of the Prague Basin in the Barrandian area of the Czech Republic (a), the Koněprusy area (b), quarries in the Koněprusy area (c) and Jirásek's and Preisler's quarries (d). The exact location of the section described by Hladil et al. (1993) (1) and the new sections where the brachiopods were extracted (2) are figured. Abbreviations: UDI – upper dark interval, VČS-E – Velkolom Čertovy schody – východ quarry.
Text-fig. 1. Location of Gánovce-Hrádok Neanderthal site in northern Slovakia and the rest of the travertine mound (map source: https://commons.wikimedia.org and Google Earth; 2017). in Revised Floral And Faunal Assemblages From Late Pleistocene Deposits Of The Gánovce-Hrádok Neanderthal Site -Biostratigraphic And Palaeoecological Implications
Text-fig. 1. Location of Gánovce-Hrádok Neanderthal site in northern Slovakia and the rest of the travertine mound (map source: https://commons.wikimedia.org and Google Earth; 2017).
Text-fig. 1. Location map of the Monticino quarry near Brisighella, Emilia-Romagna region, north-eastern Italy. in New Light On Parasorex Depereti (Erinaceomorpha: Erinaceidae: Galericini) From The Late Messinian (Mn 13) Of The Monticino Quarry (Brisighella, Faenza, Italy)
Text-fig. 1. Location map of the Monticino quarry near Brisighella, Emilia-Romagna region, north-eastern Italy.
Fig. 1. Sample places location. Points number 1, 3, 7, 12, 14, 18 and 20 in Reproductive biology of Rhaphiodon vulpinus (Ostariophysi: Cynodontidae) in the Tocantins River Basin, Brazil
Fig. 1. Sample places location. Points number 1, 3, 7, 12, 14, 18 and 20 = Tocantins river; 2 = Sono river; 4 = Lajeadinho river; 5 = Santa Luzia river; 6 = Mangues river; 8 = Areias river; 9 = Crixás river; 10 = Capivara Lagoon; 11 = Manuel Alves river; 13 = São Valério river; 15 = Santa Tereza river; 16 = Dionízio Lagoon; 17 = Água Branca Lagoon; 19 = Paranã river and 21 = Bonita Lagoon.
Fig. 6 in Environmental factors related to entry into and ascent of fish in the experimental ladder located close to Itaipu Dam
Fig. 6. Temporal variability (a) and correlogram of total abundance (b) of small-sized fish recorded in the experimental fish ladder (Pool A = 10 m, Pool B = 27 m) located near Itaipu Dam.
Fig. 3 in Environmental factors related to entry into and ascent of fish in the experimental ladder located close to Itaipu Dam
Fig. 3. Monthly variations in abundance of the main middle- and large-sized species in the experimental fish ladder (Pool A = 10 m, Pool B = 27 m) located near Itaipu Dam.
Fig. 2 in Environmental factors related to entry into and ascent of fish in the experimental ladder located close to Itaipu Dam
Fig. 2. Abundance of the main middle- and large-sized species of fish captured in the samples taken in the experimental fish ladder located near Itaipu Dam. The first three letters of each species (found in text) are shown.
Fig. 1 in Environmental factors related to entry into and ascent of fish in the experimental ladder located close to Itaipu Dam
Fig. 1. Variation in temperature, river level, spillway discharge (SD) and turbine discharge (TD) at the experimental ladder located near Itaipu Dam, during the sampling period (a) and correlogram of the variables (b).
Fig. 5 in Environmental factors related to entry into and ascent of fish in the experimental ladder located close to Itaipu Dam
Fig. 5. Correlograms of the residuals of the autoregressive models applied (VV: spillway discharge; VT: turbine discharge) to the data collected in the experimental ladder located near Itaipu Dam.
Citation Location, Elements and Purpose of ICPSR Research Data Citations
<p>The dataset contains an analysis of a randomly chosen sample of 1,073 publications that cite ICPSR research datasets. The collected research data (re)use indications were analyzed according to their location in the full-text, their metadata elements, and their citation purpose.</p> <p>The data was collected and analyzed in 2020 for a PhD thesis on research data and software (re)use indications in scholarly works.</p>
Agronomic, rheological and nutritional phenotypic data of 50 spelt varieties grown at 3 locations in Switzerland during 2 growing seasons (2021-2022)
<p>This dataset contains agronomic, rheological, and nutritional parameters of 50 winter spelt varieties tested during 2 growing seasons (2021-2022) at 3 locations in Switzerland. The dataset has been used to investigate the links between genotype and phenotype of spelt varieties, published in https://doi.org/10.1007/s10681-024-03400-8.</p> <p>The field trials were performed under the Swiss Extenso (low input) conditions, conducted by Agroscope and DSP, and under organic conditions, performed by GZPK. </p> <h3>Methods </h3> <p><em>Field trials </em></p> <div>Field trials were set up over the course of two growing seasons – 2020/2021, 2021/2022 – in three sites across the Swiss Central Plateau. The experimental sites were located in Changins (46°19′ N 6°14′ E, 455m a.s.l), Delley (46°55′ N 6°58′ E, 494m a.s.l) and Feldbach (47°14'24.00" N, 8°47'9.60" E, 410m a.s.l.).</div> <div>Each variety was grown in a plot of 7.1 m<sup>2</sup> (1.5 m*4.7 m) in Changins and Delley, and 4.5 m<sup>2</sup> (1.5 m*3 m) in Feldbach. We replicated the experiment three times per location. At each site, we used a complete randomized block design, with plots being randomized within each block. Density of sowing was 180 spikelets/m<sup>2</sup>. Plots were sowed mechanically each autumn. In Changins and Delley, the plots were mechanically fertilized with 100 kg N/ha (ammonium nitrate), applied in two splits (60 at heading stage—40 at flowering stage). In Feldbach, the fields were treated organically, and therefore no synthetic fertilizer was applied.</div> <div> </div> <div> </div> <div><em>Agronomic and morphological characteristics </em></div> <div> <p>For each plot, we recorded the heading date as the day of the year, in which 50% of the ears of the plot had fully emerged from the flag leaf. Once the plants and ears were fully developed, plant height was measured in each plot, by taking the average height in centimeters from the ground to the top of five random ears, excluding awns.</p> <p>At maturity, we harvested each plot with a combine harvester (Zürn 150, Schontal-Westernhausen, Switzerland). The harvested grains were weighed first, dehusked, sorted and cleaned with a sieve cleaner, and then weighted again. We measured specific weight and water content using a Dickey–John machine (GAC 2100). Grain yield was subsequently standardized to 15% of humidity. Protein content (%) was measured at the plot level with a near-infrared instrument (ProxiMate™, Büchi instruments). Thousand kernel weight (TKW, g), as well as kernel length and width (mm), were measured at the plot level with a Marvin seed analyzer (GTA Sensorik, Neubrandenburg, Germany).</p> <p>Additional measurements in Changins: we computed harvest index for each plot by cutting 30 individual culms just before harvest. Plants were cut just above the ground, oven-dried for 3 days at 80 °C and then weighed. We then threshed, dehusked, sieved and weighed the obtained grains. The harvest index was computed by taking the ratio of grain mass over total mass.</p> <p> </p> <p><em>Rheological characteristics </em></p> </div> <div> <p>At all sites, Zeleny sedimentation value (mL) was assessed based on the International Association for Cereal Science and Technology standard method 116/1.The analyses were performed by the analytical laboratory of DSP, Delley, at the variety level for each site—i.e., grains from the three replicates per site were pooled together and subsequently milled.</p> <p>Additional measurements in Changins were done for each variety, based on a pooled sample of the three replicates. Extensograph properties of the obtained dough were assessed according to ICC standard method 114/1; area under curve (energy, cm2), resistance to extension at 5 cm extension (EE), and extensibility of the dough (mm) were measured. The analyses were performed by the accredited laboratory “Versuchsanstalt für Getreideverarbeitung” based in Austria (<a href="https://www.vfg.or.at/">https://www.vfg.or.at/</a>).</p> <p> </p> <p><em>Nutritional characteristics </em></p> </div> <div> </div> <div>We assessed the structure of starch (amylose content) and the fatty acid composition for each variety in Changins. These analyses were done by pooling grains from the three replicates in Changins and milling them. The amylose and amylopectin contents of starch were determined enzymatically via an assay based on the precipitation of amylopectin complexes with the lectin concanavalin A, according to K-Amy 06/18. The fatty acid composition was analyzed by GC-FAME, via in situ transesterification, according to the method of Ampuero Kragten et al. (<a title="Kragten SA, Collomb M, Dubois S, Stoll P (2014) Determination of fatty acid composition in feed: analytical methods. Agrarforschung Schweiz 5(9):330&ndash;337" href="https://link.springer.com/article/10.1007/s10681-024-03400-8#ref-CR36">2014</a>). These analyses were performed at the accredited analytical laboratory of Agroscope, Posieux.</div> <div> </div> <div>Kragten SA, Collomb M, Dubois S, Stoll P (2014) Determination of fatty acid composition in feed: analytical methods. Agrarforschung Schweiz 5(9):330–337</div> <div> </div> <div> </div> <div><em>DNA extraction & Genotyping </em></div> <div> </div> <div>DNA was extracted from all cultivars, and sent to TraitGenetics (SGS institute Frenius, Gatersleben DE) for SNP genotyping on the 25 K XT Infinium array for wheat.</div> <div> </div> <div> </div>
Agronomic performance of cultivar mixtures of winter wheat varieties, obtained from mixture field trials at 5 locations in Switzerland from 2019 to 2020, together with yield data from the varieties in pure stand obtained from the national variety testing trial network
<p>This dataset contains agronomic parameters of 32 winter wheat variety mixtures tested during 2 growing seasons (2019-2020) at 5 locations in Switzerland, as well as yield data of these varieties in pure stands originating from the Swiss national variety testing network. The dataset has been used to investigate the links between asynchrony and yield stability, published in <a href="https://doi.org/10.1002/csc2.21151">https://doi.org/10.1002/csc2.21151</a>. </p> <p>The field trials were performed under the Swiss Extenso (low input) conditions, conducted by Agroscope and DSP. </p> <h2>Methods </h2> <p><em>Field trials </em></p> <p>The experiment took place in five sites across Switzerland, in 2019 and 2020. The sites were located in Nyon (1260), Delley (1567), Utzenstorf (3428), Zurich (8046), and Ellighausen (8566).</p> <p>Experimental communities consisted of 32 different two-variety mixtures grown in 7.1-m<sup>2</sup> plots (1.5 × 4.7 m). We replicated the mixture experiment three times per site with the exact same variety composition. We used a randomized block design, with plots being randomized at each site within each block. Density of sowing was 350 seeds/m<sup>2</sup>, and seeds were mixed beforehand at a 50:50 ratio in terms of mass. We used the 50:50 mass ratio as this is what is generally done in practice by farmers and seed suppliers. Plots were sown mechanically each autumn. The plots were mechanically fertilized according to the Principles of Agricultural Crop Fertilisation in Switzerland (Federal Office for Agriculture) with an average of 140 kg N/ha (ammonium nitrate), applied in three splits (40 at the tillering stage—60 at stem elongation stage—40 when the flag leaf is visible). The experimental trials were conducted following the extenso Swiss scheme, which means that there was no application of any fungicide, insecticide, or plant growth regulator. </p> <p>The performances of single varieties were obtained by going through the trials of the national variety testing program. We gathered the data for the years 2018/2019 and 2019/2020. The data regarding single varieties could be obtained for three out of the five sites used for the mixtures: 1260, 1567, and 8566. Because there were no national variety trials at the two other sites (8046, 3428), we could not get any data for single varieties in these sites. Thus, all further analyses including single variety data were only done for the three sites mentioned above. At each of these sites, the variety trials were located on the same plot as the mixture trials, even though a little further apart. Therefore, soil parameters and crop precedents were the same between the mixture and variety testing trials. Furthermore, we only selected the national variety testing trials that respected the <em>extenso</em> conditions, that is, no fungicide, pesticide, or growth regulator application, and that received the same amount of fertilization as the mixture trials. In 8566 and 1567, sowing and harvesting dates were identical between the two trials; in 1260, sowing and harvesting dates could vary but remained within a week of each other.</p> <p> </p> <p><em>Data collection </em></p> <p>For each plot, heading dates were monitored, and average height at BBCH 59–75 was measured.</p> <p>The prevalence of diseases was scored twice in the growing season. Specifically, the severity of brown rust, yellow rust, powdery mildew, and Septoria tritici blotch was assessed. This was performed by grading each individual plot from 1 to 9 for each disease, with 1 representing no disease and 9 a complete infection. The scoring scale follows a logistic progression based on the symptoms of the top three leaves. We used the data from the final scoring for statistical analysis, as the disease severity was usually more important then.</p> <p>At maturity, we harvested each plot with a combine harvester. The harvested grains were dried when needed, weighed a first time, then sorted and cleaned by air and with a sieve cleaner, and subsequently weighted again. We measured specific weight and water content at the plot level using a Dickey-John machine (GAC 2100). Grain yield was subsequently standardized to 15% of humidity. Protein content was measured at the site level with a near-infrared instrument (ProxiMate; Büchi instruments).</p>
LiDAR reveals a preference for intermediate visibility by a forest-dwelling ungulate species: Deer locational data
<ol> <li>Visibility (viewshed) plays a significant and diverse role in animals' behavior and fitness. Understanding how visibility influences animal behavior requires the measurement of habitat visibility at spatial scales commensurate to individual animal choices. However, measuring habitat visibility at a fine spatial scale over a landscape is a challenge, particularly in highly heterogeneous landscapes (e.g., forests). As a result, our ability to model the influence of fine-scale visibility on animal behavior has been impeded or limited.</li> <li>In this study, we demonstrate the application of the concept of 3D cumulative viewshed in the study of animal spatial behavior at a landscape level. Specifically, we employed a newly described approach that combines terrestrial and airborne LiDAR to measure fine-scale habitat visibility (3D cumulative viewshed) on a continuous scale in forested landscapes. We applied the LiDAR-derived visibility to investigate how visibility in forests affects the summer habitat selection and the movement of 20 GPS-collared female red deer <em>Cervus</em> <em>elaphus</em> in a temperate forest in Germany. We used integrated step selection analysis to determine whether red deer show any preference for fine-scale habitat visibility and whether visibility is related to the rate of movement of red deer.</li> <li>We found that red deer selected intermediate habitat visibility. Their preferred level of visibility during the day was substantially lower than that of night and twilight, whereas the preference was not significantly different between night and twilight. In addition, red deer moved faster in high-visibility areas, possibly mainly to avoid predation and anthropogenic risk. Furthermore, red deer moved most rapidly between locations in the twilight.</li> <li>For the first time, the preference for intermediate habitat visibility and the adaption of movement rate to fine-scale visibility by a forest-dwelling ungulate species at a landscape scale was revealed. The LiDAR technique used in this study offers fine-scale habitat visibility at the landscape level in forest ecosystems, which would be of broader interest in the fields of animal ecology and behavior.</li> </ol>
Sample locations of building types in Osaka-Kobe City-region
<p>Geopackage containing 100 sample locations for 12 different building types within the Osaka-Kobe City-region (total of 1200 samples for 2013-14). Data related to the following journal paper "<strong>Shrinkage and Morphological Change: A Study of Building Type Evolution in the Osaka-Kobe City-region in Japan</strong>"</p>
Literary locations in Piedmont Landscape and Literary Park SPOTIT tool
<p>To contribute to creating a technological infrastructure for further development of this sector of literary tourism in the SPOTIT tool frame, the UNIVR team created a layer of literary locations of the case study. Through GIS technology, it is possible to look for traces of the past, connecting the social memory and finding those elements that contribute to the literary cultural imagery of the area. The literary locations layer, together with other layers dedicated to local tourist attractions, is an added value for other future technological tools.</p>
Multi-location trials and population-based genotyping reveal high diversity and adaptation to breeding environments in a large collection of red clover
<p>This dataset accompanies the article with the same title made available on bioRxiv <a href="https://doi.org/10.1101/2022.12.19.520744">https://doi.org/10.1101/2022.12.19.520744</a> </p>
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.