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.
1,112
datasets available to search
ShareScore release 0.9.0
Dataset results
1,112 results for “canalization”
LTER-Italy site Lago Sos Canales figure
<p>Geographical representation of the LTER-Italy site Lago Sos Canales (LTER_EU_IT_052) - DEIMS-ID <a href="https://deims.org/e8374da3-1644-460b-bd4c-bf669514dd22">https://deims.org/e8374da3-1644-460b-bd4c-bf669514dd22</a></p>
Regional drinking water quality monitoring program: long-term monitoring of water quality in select canals, reservoirs, and treatment plants of the greater Phoenix, Arizona metropolitan area drinking water system, ongoing since 1998
Regional Drinking Water Quality Monitoring Program ================================================== Arizona Statue University (ASU) has been working with regional water providers (Salt River Project (SRP), Central Arizona Project (CAP)) and metropolitan Phoenix cities since 1998 on algae-related issues affecting drinking water supplies, treatment, and distribution. The results have improved the understanding of taste and odor (T&O) occurrence, control, and treatment, improved the understanding of dissolved organic and algae dynamics, and initiated a forum to discuss and address regional water quality issues. The monitoring benefits local Water Treatment Plants (WTPs) by optimizing ongoing operations (i.e., reducing operating costs), improving the quality of municipal water for consumers, facilitating long-term water quality planning, and providing information on potentially future-regulated compounds. ASU has been monitoring water quality in terminal reservoirs (Lake Pleasant, Saguaro Lake, and Bartlett Lake) continuously from 1998 to the present for algae-related constituents (taste and odors, and more recently metals from the upper reservoirs), nutrients, and disinfection by-product precursors (i.e., total and dissolved organic carbon and organic nitrogen). Additional monitoring has been conducted in the SRP and CAP canal systems and in water treatment plants in Phoenix, Tempe and Peoria. During this work the Valley has been in a prolonged drought and recently one above average wet year, and this data provides important baseline data for development of new or expanded WTPs and management of existing WTPs in the future. The current work has improved the understanding of T&O sources and treatment, but additional research and monitoring into the future is necessary. Reservoir monitoring is conducted once per month at Bartlett Lake, Saguaro Lake, and Lake Pleasant, and quarterly at Roosevelt, Apache, and Canyon Lakes. Samples are depth integrated in the epilimnion a
PFAS, Coliform, and E. coli Data from Freshwater Canals, Brackish Water in Biscayne Bay, and Ocean Salt Water from Miami Beaches, Florida, USA, July 2023
This package contains data on levels of Per- and polyfluoroalkyl substances (PFAS), Coliform, and E. coli from samples collected at 15 water sampling sites in and around Biscayne Bay, Florida on 2023-07-27 as part of the Coastal Ecosystem-Research Experience for Teachers (CE-BIORETS) program. The sites included waterways leading to Biscayne Bay (freshwater canals), Biscayne Bay directly (marine brackish water), and ocean water from Miami beaches (marine salt water). A total of 500 mL of surface water was collected (at approximately 30 cm depth) from each site. Samples were run through a Solid Phase Extraction process (SPE) and then dried using a Nitrogen Evaporator. Extracts were then analyzed by Liquid Chromatography-Triple quadrupole Mass Spectrometry (LC-MS/MS) to determine the quantity of each of the different PFAS (ng/L) present in the sample. The same sites were selected for Coliform and E. coli colony forming units’ detection, and samples were collected at the same time as the PFAS samples. Samples were analyzed by pouring 100 mL of collected water into the wells on a ColiPlate. The 15 plates were incubated for 1 day at 37°C to determine if Coliforms and E. coli were detected. Data collection for this project is complete.
Indicative distribution map for Ecosystem Functional Group SF2.1 Water pipes and subterranean canals
<p>This archive contains indicative distribution maps and profiles for <strong>SF2.1 Water pipes and subterranean canals</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Indicative distribution map for Ecosystem Functional Group F3.5 Canals, ditches and drains
<p>This archive contains indicative distribution maps and profiles for <strong>F3.5 Canals, ditches and drains</strong>, a ecosystem functional group (EFG, level 3) of the <a href="https://global-ecosystems.org/">IUCN Global Ecosystem Typology</a> (v2.0). Please refer to Keith <em>et al.</em> (2020) for details.</p> <p>The descriptive profiles provide brief summaries of key ecological traits and processes, maps are indicative of global distribution patterns, and are not intended to represent fine-scale patterns. The maps show areas of the world containing major (value of 1, coloured red) or minor occurrences (value of 2, coloured yellow) of each ecosystem functional group. Minor occurrences are areas where an ecosystem functional group is scattered in patches within matrices of other ecosystem functional groups or where they occur in substantial areas, but only within a segment of a larger region. Given bounds of resolution and accuracy of source data, the maps should be used to query which EFG are likely to occur within areas, rather than which occur at particular point locations. Detailed methods and references for the maps are included in the profile (xml format).</p>
Hohokam canals as multi-use facilities: Pre-historic canal system in the central Arizona-Phoenix metropolitan area
This is the digitized version of a map of the Hohokam canal system in what is now the Phoenix metropolitan area. It is based on the thesis research by J. B. Howard (Howard, J. (1990). Paleohydraulics : techniques for modeling the operation and growth of prehistoric canal systems. Thesis (M.A.)--Arizona State University, 1990). The original paper map is based on previous archaeological data, overlayed onto USGS 7.5 minute quadrangle maps to recreate the canal pattern.
ds-uct-002: Root Canal Strain: X-Ray micro-CT of four teeth before and after root canal procedure.
<p><strong>Summary</strong>:<br> .X-Ray micro-computed tomography (micro-CT) of four teeth before (TomoB) and after (TomoA) simulation of root canal treatment and retreatment procedures instrumented with strain-gauge, including reconstructions, for two different resolutions (TomoB and TomoA with voxel sizes of 20.0 μm and 10.5 μm, respectively).<br> .The 3D image was generated with an X-Ray micro-CT Scanner version Xradia Versa 510 from Zeiss performed by A Pereira at the UFF micro-CT Facility.<br> .For use of these data, please remember to cite the DOI of the Zenodo repository and relevant papers.</p> <p><strong>Details</strong>:<br> .Tomo1B/Tomo2B/Tomo3B/Tomo4B (1024) - Voxel size: 20.0 μm; Sample-source: 45.0 mm; Sample-detector: 110 mm; Optical magnification: 0.4X; Filter: LE#1; Beam energy: 60 kV; Power: 5 W; Exposure time: 2.0 sec; Projections: 1600.<br> .Tomo1A/Tomo2A/Tomo3A/Tomo4A (2048) - Voxel size: 10.5 μm; Sample-source: 48.2 mm; Sample-detector: 110 mm; Optical magnification: 0.4X; Filter: LE#2; Beam energy: 60 kV; Power: 5 W; Exposure time: 7.0 sec; Projections: 1600.</p> <p><strong>Contents</strong>:<br> ._info_ds-uct-002.txt<br> .ds-uct-002_root_canal_strain_tomo1b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo2b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo3b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo4b_20um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo1a_10um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo2a_10um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo3a_10um_8bits.zip<br> .ds-uct-002_root_canal_strain_tomo4a_10um_8bits.zip<br> .PB_PARECER_CONSUBSTANCIADO_CEP_2650528.pdf</p>
NYU FloodSense Gowanus canal mounted sensor depth
<p>Water depth level in mm from a sensor mounted mounted above the Gowanus Canal, Brooklyn, NY (40.674490, -73.994458).</p> <p>The sensor is designed to detect flood water that fills the street and blocks vehicle and pedestrian traffic, as well as depositing micro-organisms on the street. This one is used for data validation.</p> <p>The sensor transmits its data via LoRaWAN and is equipped with a solar panel for continuous operation.</p> <p>Data is collected at ~5min intervals. Time fields are in local time (New York). Time fields are in local time (New York). Date format is: 2020-10-04 20:11:45.742594232-04:00</p> <p>Two flood events have been observed in this dataset between these date ranges:</p> <ol> <li> <p>"2020-11-15 19:37:00.000000000-05:00" to "2020-11-16 00:30:00.000000000-05:00"</p> </li> <li> <p>"2020-11-30 10:20:00.000000000-05:00" to "2020-11-30 13:30:00.000000000-05:00"</p> </li> </ol> <p>One type of erroneous data has been observed:</p> <ul> <li>There are ~1% rises in distance measures on days with sun which suggests that the distance sensor is affected by direct sunlight</li> </ul> <p>This data is prelimary and is for prototyping purposes. Not to be used as a reliable data source as it is.</p> <p>This dataset will be updated when more data is collected.</p> <p>Please see our github org for sensor information and build instructions: <a href="https://github.com/floodsense">github.com/floodsense</a></p> <p> </p>
Dataset for the manuscript "ExSTED microscopy reveals contrasting functions of dopamine and somatostatin CSF-c neurons along the central canal"
<p>Description: Dataset that supports the expansion-STED and light sheet microscopy methods in spinal cord and support the findings in the manuscript: ExSTED microscopy reveals contrasting functions of dopamine and somatostatin CSF-c neurons along the central canal (Elham Jalalvand, Jonatan Alvelid, Giovanna Coceano, Steven Edwards, Brita Robertson, Sten Grillner, Ilaria Testa).</p> <p>The software used to open the files and perform the analysis: Imspector v0.10_rev8575 and ImageJ 1.52i.</p> <p>The preprint of the manuscript can be found here: https://doi.org/10.1101/2021.08.17.456595</p>
The PIRATE: an anthropometric earPlug with exchangeable microphones for Individual Reliable Acquisition of Transfer functions at the Ear canal entrance
<p>We present the open design of the PIRATE, an anthropometric earPlug with exchangable microphones for Individual Reliable Acquisition of Transfer functions at the Ear canal entrance. Its outer shape is available in 5 sizes and provides a deep, tight and reproducible fit in virtually all human ears. The design includes a recess to accommodate a MEMS microphone. Thus, the same microphone can be conveniently used in different earplugs without losing accuracy, and the microphone can be removed for calibration. The PIRATE or previous versions of it have been utilized in several studies with more than 200 subjects</p> <p>From the provided model, the earplugs can be 3D printed, and only minor working steps are necessary before use. These steps are described in the documentation.</p> <p> </p> <p>Reference:</p> <p>Denk F., Brinkmann F., Stirnemann S., Kollmeier B. (2019) "The PIRATE: an anthropometric earPlug with exchangeable microphones for Individual Reliable Acquisition of Transfer functions at the Ear canal entrance," Fortschritte der Akustik - DAGA, Rostock, Germany</p>
Data part of the manuscript Anaerobic methanotrophy is stimulated by graphene oxide in a brackish urban canal sediment
<p>We surveyed three canals in the city of Amsterdam (Netherlands) for it methane emissions and potential to filter methane through anaerobic oxidation of methane in the canal sediment. To unravel the mechanisms involved we characterised the sediment geochemically. All data present in the manuscript is available in the Excel file.</p>
Geochemical data of bottom sediments from a network of drainage canals located in the low-lying coastal area of Ravenna, Italy.
<p>This dataset contains all raw geochemical data of bottom sediments from a network of drainage canals located in the low-lying coastal area of Ravenna. The dataset is divided in three separated excel worksheets: </p> <p>- <strong>Focus Area</strong>. Sediment composition of the 21 sediment samples collected in 2022 in the Focus Area. Refer to Figs. 1 and 2 in the manuscript Giambastiani et al., 2024 for the sample locations. Listed are also other information related to sampling, such as depositional facies (BR: beach ridge deposits; IF: Interfluvial floodplain deposits), distance from the sea, altimetry, amount of fertilizer applied based on the land use, and EC of drainage water. <br>The sediment samples were collected in March 2022 along the drainage system of the lowlying coastal aquifer of Ravenna (Italy) by the authors.</p> <p>- <strong>LRC, Land Reclamation Consortium</strong>. PTEs composition of the sediment samples of the Land Reclamation Consortium dataset. Refer to Fig. 1 and 2 in the manuscript Giambastiani et al., 2024 for the location. Listed are also other information related to sampling, such as distance from the sea, altimetry, and amount of fertilizer applied based on the land use. <br>The sediment samples were collected since 2010 along the drainage system of the lowlying coastal aquifer of Ravenna (Italy) by The Land Reclamation Consortium of Romagna (Italy). No other uses apart from scientific purpose is allowed without notice to the authors.</p> <p>- <strong>Wells</strong>. Physical and chemical groundwater parameters of 4 wells localted within the Focus Area. Refer to Fig.2 in the manuscript Giambastiani et al., 2024 for the location. <br>Data were collected during previous studies by Greggio et al. (2020) and reprocessed to obtain vertical profiles of EC, pH, Eh, and chemical concentrations along the coastal aquifer depth.</p> <p>More informations regarding the source, ownership, collection methodologies and analytical techniques are in Giambastiani et al., 2024.</p>
Data from: Genetic and environmental canalization are not correlated among altitudinally varying populations of Drosophila melanogaster
<p>Organisms are exposed to environmental and mutational effects influencing both mean and variance of phenotypes. Potentially deleterious effects arising from this variation can be reduced by the evolution of buffering (canalizing) mechanisms, ultimately reducing phenotypic variability. There has been interest regarding the conditions enabling the evolution of canalization. Under some models, the circumstances under which genetic canalization evolves is limited, despite apparent empirical evidence for it. It has been argued that genetic canalization evolves as a correlated response to environmental canalization (congruence model). Yet, empirical evidence has not consistently supported predictions of a correlation between genetic and environmental canalization. In a recent study, a population of <em>Drosophila </em>adapted to high altitude showed evidence of genetic decanalization relative to those from low altitudes. Using strains derived from these populations, we tested if they varied for multiple aspects of environmental canalization We observed the expected differences in wing size, shape, cell (trichome) density and mutational defects between high- and low-altitude populations. However, we observed little evidence for a relationship between measures of environmental canalization with population or with defect frequency. Our results do not support the predicted association between genetic and environmental canalization.</p>
Fig. 7 in New sponge species from Seno Magdalena, Puyuhuapi Fjord and Jacaf Canal (Chile)
Fig. 7. Biemna aurantiaca Bertolino, Costa & Pansini sp. nov., holotype (CILE 20; MSGN 61497). A–B. The holotype in life. C. Plumoreticulate skeleton.
Fig. 5 in New sponge species from Seno Magdalena, Puyuhuapi Fjord and Jacaf Canal (Chile)
Fig. 5. Axinella coronata Bertolino, Costa & Pansini sp. nov., holotype (CILE 22; MSGN 61494). A–B. The holotype in life. C. Plumose multispicular skeleton. D. Cross section of the skeleton. E. Ectosome. F. Magnification of a single tylostyle, surrounded by a crown of thin styles.
Fig. 9 in New sponge species from Seno Magdalena, Puyuhuapi Fjord and Jacaf Canal (Chile)
Fig. 9. Biemna erecta Bertolino, Costa & Pansini sp. nov., holotype (CILE 74; MSGN 61496). A–B. The holotype in life. C. Plumose skeleton. D–E. Choanosome. F. Basal peduncle skeleton.
NYU FloodSense Gowanus Canal mounted distance sensor
<p>Ultrasonic distance data in mm from a sensor mounted above the Gowanus Canal, Brooklyn, NY (40.674490, -73.994458). The sensor is designed to detect flood water that fills the street and blocks vehicle and pedestrian traffic, as well as depositing micro-organisms on the street. This one is used for data validation.</p> <p>The sensor transmits its data via LoRaWAN and is equipped with a solar panel for continuous operation.</p> <p>Data is collected at ~5min intervals. Time fields are in local time (New York).</p> <p>One type of erroneous data has been observed:</p> <ul> <li>There are ~1% rises in distance measures on days with sun which suggests that the distance sensor is affected by direct sunlight</li> </ul> <p>This data is prelimary and is for prototyping purposes. Not to be used as a reliable data source as it is.</p> <p>This dataset will be updated when more data is collected.</p> <p>Please see our github org for sensor information and build instructions: <a href="https://github.com/floodsense">github.com/floodsense</a></p>
NYU FloodSense Gowanus canal mounted sensor depth
<p>Water depth level in mm from a sensor mounted mounted above the Gowanus Canal, Brooklyn, NY (40.674490, -73.994458) from October 4th 2020 to January 8th 2021.</p> <p>The sensor is designed to detect flood water that fills the street and blocks vehicle and pedestrian traffic, as well as depositing micro-organisms on the street. This one is used for data validation.</p> <p>The sensor transmits its data via LoRaWAN and is equipped with a solar panel for continuous operation.</p> <p>Data is collected at ~5min intervals. Time fields are in local time (New York). Time fields are in local time (New York). Date format is: 2020-10-04 20:11:45.742594232-04:00</p> <p>Two flood events have been observed in this dataset between these date ranges:</p> <ol> <li> <p>"2020-11-15 19:37:00.000000000-05:00" to "2020-11-16 00:30:00.000000000-05:00"</p> </li> <li> <p>"2020-11-30 10:20:00.000000000-05:00" to "2020-11-30 13:30:00.000000000-05:00"</p> </li> </ol> <p>One type of erroneous data has been observed:</p> <ul> <li>There are ~1% rises in distance measures on days with sun which suggests that the distance sensor is affected by direct sunlight</li> </ul> <p>This data is prelimary and is for prototyping purposes. Not to be used as a reliable data source as it is.</p> <p>This dataset will be updated when more data is collected.</p> <p>Please see our github repo for sensor information and build instructions: <a href="https://github.com/floodsense">github.com/floodsense</a></p>
Fig. (10-17): (10) Dichrogaster aestivalis, fore wing; (11) C. armator, areolet of fore wing; (12) Mesostenus sp., areolet of fore wing; (13) Venturia canescens, ovipositor; (14) Barichneumon sp.; ventral aspect of metasoma; (15) Ctenichneumon sp., ventral aspect of metasoma; (16) Exochus castaniventris, frontal view of head; (17) Diplazon laetatorius, frontal view of head. in Ichneumonidae from the Suez Canal region Egypt (Hymenoptera, Ichneumonoidea)
Fig. (10-17): (10) Dichrogaster aestivalis, fore wing; (11) C. armator, areolet of fore wing; (12) Mesostenus sp., areolet of fore wing; (13) Venturia canescens, ovipositor; (14) Barichneumon sp.; ventral aspect of metasoma; (15) Ctenichneumon sp., ventral aspect of metasoma; (16) Exochus castaniventris, frontal view of head; (17) Diplazon laetatorius, frontal view of head.
Fig. (18-26): (18) D. laetatorius, hind wing; (19) Netelia sp., hind wing; (20) Netelia sp., frontal view of head; (21) D. laetatorius, propodeum; (22) Syrphophilus bizonarius, propodeum; (23) D. laetatorius, dorsal aspect of metasoma; (24) Netelia sp., lateral aspect of first metasomal segment showing glymma; (25) Exetastes syriacus, ovipositor; (26) Exeristes roborator, ovipositor. in Ichneumonidae from the Suez Canal region Egypt (Hymenoptera, Ichneumonoidea)
Fig. (18-26): (18) D. laetatorius, hind wing; (19) Netelia sp., hind wing; (20) Netelia sp., frontal view of head; (21) D. laetatorius, propodeum; (22) Syrphophilus bizonarius, propodeum; (23) D. laetatorius, dorsal aspect of metasoma; (24) Netelia sp., lateral aspect of first metasomal segment showing glymma; (25) Exetastes syriacus, ovipositor; (26) Exeristes roborator, ovipositor.
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.