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1,271 results for “Data Flow”
Data from: Inversions dominate evolution in the European Sardine (Sardina pilchardus) amid strong gene flow
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Data from: Understanding species boundaries that arise from complex histories: Gene flow across the speciation continuum in the spotted whiptail lizards
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Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr
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Data and scripts for the colour analysis from: Gene flow throughout the evolutionary history of a colour polymorphic and generalist clownfish
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Data for: Parameter selection and optimization of a computational network model of blood flow in single-ventricle patients
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Dataset on sub-daily vertical profiles of physicochemical parameters and chlorophyll concentration in El Val reservoir, together with its daily meteorological data, storage state and downstream flow (2018-2022).
This dataset contains the physicochemical parameters and chlorophyll concentration of El Val reservoir (province of Zaragoza, Spain), together with its meteorological conditions, the water level, the stored volume and the flow rate of the effluent, the Queiles River, a few meters downstream of the dam. These data are useful to feed deterministic, data driven or hybrid hydrological models with different purposes, like the identification of the impact of meteorological conditions on the physicochemical properties of the reservoir, like the thermal stratification, as well as the assessment of different management strategies in the reservoir. The original data were collected by the Confederación Hidrográfica del Ebro (CHE) and were published in real time through the web page of the Ebro Automatic Water Quality Information System (SAICA Ebro by its initials in Spanish) and the Ebro Automatic Hydrographic Information System (SAIH Ebro by its initials in Spanish). Then, the CHE curated the data that are finally available to the citizens under request by variable and date. In order to facilitate their availability and reuse, these data have been gathered, pre-processed and packaged in the form of datasets. Specifically, they are structured in four data tables: vertical profiles of physicochemical data in the reservoir, meteorological data in the same basin, water level and stored water volume in the reservoir and water flow rate of the Queiles River downstream of the reservoir.
Phosphorus concentrations and flow data, Old Woman Creek, Ohio, 2015-2023
The Old Woman Creek National Estuarine Research Reserve is located in Huron, Ohio (USA), along the southern shore of Lake Erie. Old Woman Creek is a fourth order stream that flows through a 0.6 km² wetland complex during its last 2 stream km, and surface connectivity between the stream and lake is mediated by a barrier sand beach that can open and close depending on flow, wind, waves, and precipitation. The Reserve has been measuring water quality in Old Woman Creek since 1980. Data presented in this package represent a small part of this long-term monitoring used in the study by Anderson et al. (2024, http://dx.doi.org/10.2139/ssrn.4947733) titled "We know less about phosphorus retention in constructed wetlands than we think we do: A quantitative literature synthesis". This study aims to identify gaps in our collective understanding of structural wetland features, monitoring methods, and long-term trajectories in restored and constructed wetlands. It uses the Old Woman Creek data presented in this data package to test different sampling frequencies to determine how sampling approach affects observed trends in total phosphorus loading. The data in this package include total phosphorus concentrations collected at the Inlet and Outlet of Old Woman Creek between 2015 and 2023. Total phosphorus concentrations were collected between 1 and 3 times per day at the Inlet and once per day to once per week at the Outlet, depending on streamflow. Additionally, flow data measured at 15-minute intervals at the stream Outlet between 2020 and 2023 are also included. This Outlet flow data corresponds well with flow measurements made by the United States Geological Survey (USGS) at the stream Inlet. While the Inlet flow data is not included in this package, it was used in the study by Anderson et al. (2024) and can be obtained from USGS's website by searching for gauge number 04199155. Additional data from the Old Woman Creek National Estuarine Research Reserve long-term water qualit
Ecosystem-Scale Rainfall Manipulation in a Piñon-Juniper Forest at the Sevilleta National Wildlife Refuge, New Mexico: Sap Flow Data (2006-2013)
Climate models predict that water limited regions around the world will become drier and warmer in the near future, including southwestern North America. We developed a large-scale experimental system that allows testing of the ecosystem impacts of precipitation changes. Four treatments were applied to 1600 m2 plots (40 m × 40 m), each with three replicates in a piñon pine (Pinus edulis) and juniper (Juniper monosperma) ecosystem. These species have extensive root systems, requiring large-scale manipulation to effectively alter soil water availability.  Treatments consisted of: 1) irrigation plots that receive supplemental water additions, 2) drought plots that receive 55% of ambient rainfall, 3) cover-control plots that receive ambient precipitation, but allow determination of treatment infrastructure artifacts, and 4) ambient control plots. Our drought structures effectively reduced soil water potential and volumetric water content compared to the ambient, cover-control, and water addition plots. Drought and cover control plots experienced an average increase in maximum soil and air temperature at ground level of 1-4° C during the growing season compared to ambient plots, and concurrent short-term diurnal increases in maximum air temperature were also observed directly above and below plastic structures. Our drought and irrigation treatments significantly influenced tree predawn water potential, sap-flow, and net photosynthesis, with drought treatment trees exhibiting significant decreases in physiological function compared to ambient and irrigated trees.  Supplemental irrigation resulted in a significant increase in both plant water potential and xylem sap-flow compared to trees in the other treatments. This experimental design effectively allows manipulation of plant water stress at the ecosystem scale, permits a wide range of drought conditions, and provides prolonged drought conditions comparable to historical droughts in the past – drought events for w
RCP8.5-ECEARTH-RACMO-LARSIM_ME Climate Flow Projection Data for German Waterways
<p>The datasets provided here were produced as part of the IMPREX project for work package 4, task 4 „<em>Improving prediction on the climate scale</em>“ and work package 9, task 3 “<em>Case studies</em>”. Analysis of the datasets are published in Deliverable 4.4 „<em>Estimation of hazards based on improved representation of highly vulnerable water resources of strategic importance on the climate scale</em>“ (Falloon et al 2019). The aim was to study the impact of internal climate model variability and bias correction method on the climate change signal of relevant flow indicators for the German waterways Rhine, Elbe and Danube.</p> <p>To assess the impact of internal variability of the global climate model on future changes of flow, precipitation, temperature and global radiation of the 16-member ensemble generated with the RCM KNMI-RACMO2 driven by the GCM EC-EARTH 2.3 provided by WP3 of IMPREX were used. EC-EARTH was run 16 times from 1850 to 2100, each member starting from a slightly different initial state, under forcing of historical emissions until 2005 and the RCP8.5 greenhouse gas concentration pathway from 2006 onwards. Each of the EC-EARTH members was subsequently dynamically downscaled using KNMI-RACMO2 on a 0.11° (~12 km) resolved domain (Aalbers et al. 2018).</p> <p>To correct the systematic model biases of climate models different bias correction methods were applied: (1) no bias correction, (2) linear scaling (Lenderink et al. 2007) and (3) quantile-quantile mapping (Piani et al. 2010). Bias correction relationships were derived for five-day periods (for each variable and location, in total 73 bias correction relationships were derived) including 13 days before and after the considered five-day period (total window size was 31 days) from the observations and values of the regional climate simulations. The period used to estimate the bias correction relationships was 1971-2000.</p> <p>The hydrological model applied is called LARSIM-ME (ME – MittelEuropa = Central Europe) and is based in the model software LARSIM (Large Area Runoff SImulation Model) originally developed by Ludwig & Bremicker (2006). LARSIM-ME covers the catchments of the rivers Rhine, Elbe, Weser/Ems, Odra and Upper Danube. The total catchment size simulated by the model is approximately 800,000 km². The spatial resolution is 5 km x 5 km and the computational time-step is daily. As observed meteorological forcings, precipitation, air temperature and global radiation from the HYRAS data set (Rauthe et al. 2013) available for the 5 km x 5 km model grid and the period 1951-2015 were used. The hydrological model was calibrated using the automatic calibration scheme Shuffled Complex Evolution SCE-UA algorithm (Duan et al. 1994). For more details about the model see Meißner et al. (2017).</p> <p>The meteorological variables air temperature, precipitation and global radiation produced by the KNMI RACMO-EC-EARTH 16 member ensemble (period 1951-2100) were interpolated to a 25 km x 25 km grid and afterwards bias corrected with respect to the observation data (HYRAS) used for calibration of the hydrological model LARSIM. From this 25 km x 25 km grid the bias corrected variables were downscaled to the 5 km x 5 km model grid of LARSIM using monthly background climatology fields on the 5 km x 5 km target grid of the HYRAS dataset. The bias-corrected and downscaled data was then used as meteorological forcing of LARSIM to calculate flow projections for the rivers Rhine, Elbe and Upper Danube (up to the German/Austrian border).</p> <p><strong>Dataset Q_OBS_DE.nc:</strong></p> <p>Mean daily observed flow of the gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe for the period 1951–2017 stored as variable <em><strong>q_obs(time=24472, stations=8)</strong></em>.</p> <p>Data originate from the database of gauge measurements of the Federal Waterways and Shipping Administration (WSV). These data were quality checked and published by the gauge-operating WSV offices. Nevertheless, data errors and inconsistencies cannot be ruled out completely, so that neither the WSV nor the BfG do accept any liability for the correctness and completeness of the data. Data source: "German Federal Waterways and Shipping Administration (WSV)", provided by the German Federal Institute of Hydrology (BfG)</p> <pre><code>float q_obs(time=24472, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "observed streamflow"; :coordinates = "lat lon";</code></pre> <p><strong>Dataset Q_HYRAS_LME.nc:</strong></p> <p>Mean daily simulated flow of the hydrological model LARSIM-ME forced by observed meteorology from the HYRAS dataset stored as variable <em><strong>q_sim (time=23741, stations=8)</strong></em>. Period 1951-2015, Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe.</p> <pre><code>float q_sim(time=23741, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "simulated streamflow"; :coordinates = "lat lon";</code></pre> <p><strong>Q_RCP85_ECEARTH_RACMO_[bc]_LME.nc:</strong></p> <p>Mean daily projected flow of the hydrological model LARSIM-ME forced by 16 realizations of RCP8.5-ECEARTH-RACMO stored as variable <em><strong>q_sim(time=54787, realization=16, stations=8)</strong></em>, first dimension time, second dimension realization and third dimension stations. Bias correction of meteorological forcings [bc]: NOBC: no bias correction, LS: linear scaling, QQMAP Quantile-Quantile Mapping. Period 1951-2100, Gauges Kaub, Koeln, Ruhrort / Rhine, Pfelling, Hofkirchen / Danube, Desden, Magdeburg Strombruecke, Neu-Darchau / Elbe.</p> <pre><code>float q_sim(time=54787, realization=16, stations=8); :units = "m3/s"; :_FillValue = -9999.0f; // float :long_name = "projected streamflow"; :coordinates = "lat lon";</code></pre> <p><strong>Literature</strong></p> <p>Aalbers, E. E., G. Lenderink, E. van Meijgaard & B. J. J. M. van den Hurk (2018): Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability? Climate Dynamics 50(11), 4745-4766</p> <p>Duan, Q., S. Sorooshian & V. K. Gupta (1994): Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology 158(3–4), 265-284</p> <p>Falloon, P., K. Williams, J. Andreu, A. Solera, S. Suárez-Almiñana, B. Klein, D. Meissner, J. Hunink, J. Eekhout & J. de Vente (2019): Estimation of hazards based on improved representation of highly vulnerable water resources of strategic importance on the climate scale. Deliverable 4.4, IMPREX - Improving Predictions of Hydrological Extremes - Grant Agreement Number 641811, <a href="https://imprex.eu/system/files/generated/files/resource/imprex-deliverablereport-d4-4-final-1.pdf">https://imprex.eu/system/files/generated/files/resource/imprex-deliverablereport-d4-4-final-1.pdf</a></p> <p>Lenderink, G., A. Buishand & W. van Deursen (2007): Estimates of future discharges of the river Rhine using two scenario methodologies: direct versus delta approach. Hydrology and Earth System Sciences 11(3), 1143-1159</p> <p>Ludwig, K. & M. Bremicker (2006): The Water Balance Model LARSIM –Design, Content and Applications. 22. C. Leibundgut, S. Demuth and J. Lange (Eds), Freiburger Schriften zur Hydrologie, Institut für Hydrologie, Universität Freiburg im Breisgau, Freiburg, 141 pp.</p> <p>Meißner, D., B. Klein & M. Ionita (2017): Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe. Hydrol. Earth Syst. Sci. 21(12), 6401</p> <p>Piani, C., J. O. Haerter & E. Coppola (2010): Statistical bias correction for daily precipitation in regional climate models over Europe. Theoretical and Applied Climatology 99(1-2), 187-192</p> <p>Rauthe, M., H. Steiner, U. Riediger, A. Mazurkiewicz & A. Gratzki (2013): A Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift 22(3), 235-256</p>
Model data for "Flow Separation and Increased Drag Coefficient in Estuarine Channels with Curvature"
<p>These are the model data we generated using ROMS and analyzed for the journal article "Increased Drag Coefficient in Estuarine Channels with Curvature". Files include 8 sinuous channel models and 2 straight channels. sinuous_channel_1.nc and straight_channel_1.nc are the pair of models analyzed in section 3. sinuous_channel_1_avg.nc and straight_channel_1_avg.nc are the one-hour average result. sinuous_channel_2_avg.nc and straight_channel_2_avg.nc are the pair of deep channel models. sinuous_channel_3_avg.nc and others are the other different sinuous channel models.</p>
Five-minute average horizontal wind velocity data combined from both sensors (which has been corrected for air-flow distortion) from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4.
<p><strong>Dataset abstract</strong></p> <p>The horizontal wind velocity data from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4 has been corrected for air-flow distortion. The measurements from both the port and starboad side anemometer were averaged to five-minute resolution and have been combined via vector averaging of the data. The ten meter neutral wind speed (U10N) has been estimated using ERA-5 surface heat fluxes, which were interpolated onto the ship's track, and the COARE 3.5 drag coefficient. This data set provides a continous and high-resolution record of the wind speed and direction near to the ship's location.</p> <p><strong>Dataset contents</strong></p> <ul> <li>wind-observations-port-stbd-corrected-combined-5min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This five-minute averaged wind velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
One-minute average horizontal wind velocity data (which has been corrected for air-flow distortion) from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4.
<p><strong>Dataset abstract</strong></p> <p>One-minute average horizontal wind velocity data from the Antarctic Circumnavigation Expedition (ACE) 2016/2017 legs 0 to 4. The data has been filtered for spurious observations and the true wind correction has been redone using the quality checked one-minute ship track velocity data. The data has been corrected for air-flow distortion, which was caused by the ship's super structure.</p> <p><strong>Dataset contents</strong></p> <ul> <li>wind-observations-stbd-corrected-1min-legs0-4.csv, data file, comma-separated values</li> <li>wind-observations-port-corrected-1min-legs0-4.csv, data file, comma-separated values</li> <li>data_file_header, metadata, text format</li> <li>README.txt, metadata, text format</li> </ul> <p><strong>Dataset license</strong></p> <p>This one-minute averaged wind velocity dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
MarTREC Data Set for Report: Developing and Applying an Analysis Methodology to Identify Flow Generation Influences between Vessel and Truck Shipments
<p>Truck activity is logically connected to vessel activity at a port. In turn, vessel activity is also influenced by truck shipments. Although one might expect a direct and straightforward relation between these two types of shipments, that is rarely the case. For instance, many maritime containers carry consolidated cargos that have multiple and different final destinations. Also, different truck capacities, customs clearance and regulations play a critical role in determining the actual relation between these two types of shipments. This project aims at shedding light on the nuances of maritime and roadway flow relations by quantitatively analyzing the linkages between these two types of shipments.</p> <p>The study performed a statistical analysis to determine the probability distributions of vessel and truck activity, and then explore the correlation of each activity with the other. The analysis yielded coefficients that function as explanatory values for specific truck flows.</p> <p>The ultimate purpose of this study is to provide a clearer and quantitative understanding of the relationship between maritime and truck shipments, and by doing so, to provide tools to develop a system for managing trucks that maximizes efficiency for industry, while minimizing industry’s negative impacts on a region.</p> <p>For this purpose, the study selected the Port Freeport as a case study.</p>
Flow of Agricultural Nitrogen, version 2 (FANv2): Model input and output data
<p>This upload includes data associated with the manuscript "An improved mechanistic model for ammonia volatilization in Earth system models: Flow of Agricultural Nitrogen, version 2 (FANv2)" submitted to Geoscientific Model Development. The dataset includes an input file for use with the Community Land Model, and an output file with the simulated ammonia emissions for the agricultural sector. The emissions are monthly averages from the simulation for 2010-2015. Additional information is given in the readme file.</p>
Data from: Low coverage genomic data resolve the population divergence and gene flow history of an Australian rain forest fig wasp
Population divergence and gene flow are key processes in evolution and ecology. Model-based analysis of genome-wide datasets allows discrimination between alternative scenarios for these processes even in non-model taxa. We used two complementary approaches (one based on the blockwise site frequency spectrum (bSFS), the second on the Pairwise Sequentially Markovian Coalescent (PSMC)) to infer the divergence history of a fig wasp, Pleistodontes nigriventris. Pleistodontes nigriventris and its fig tree mutualist Ficus watkinsiana are restricted to rain forest patches along the eastern coast of Australia, and are separated into northern and southern populations by two dry forest corridors (the Burdekin and St. Lawrence Gaps). We generated whole genome sequence data for two haploid males per population and used the bSFS approach to infer the timing of divergence between northern and southern populations of P. nigriventris, and to discriminate between alternative isolation with migration (IM) and instantaneous admixture (ADM) models of post divergence gene flow. Pleistodontes nigriventris has low genetic diversity (π = 0.0008), to our knowledge one of the lowest estimates reported for a sexually reproducing arthropod. We find strongest support for an ADM model in which the two populations diverged ca. 196kya in the late Pleistocene, with almost 25% of northern lineages introduced from the south during an admixture event ca. 57kya. This divergence history is highly concordant with individual population demographies inferred from each pair of haploid males using PSMC. Our analysis illustrates the inferences possible with genome-level data for small population samples of tiny, non-model organisms and adds to a growing body of knowledge on the population structure of Australian rain forest taxa.
Data from: Assortative mating, sexual selection and their consequences for gene flow in Littorina
When divergent populations are connected by gene flow, the establishment of complete reproductive isolation usually requires the joint action of multiple barrier effects. One example where multiple barrier effects are coupled consists of a single trait that is under divergent natural selection and also mediates assortative mating. Such multiple-effect traits can strongly reduce gene flow. However, there are few cases where patterns of assortative mating have been described quantitatively and their impact on gene flow has been determined. Two ecotypes of the coastal marine snail, <i>Littorina saxatilis</i>, occur in North Atlantic rocky-shore habitats dominated by either crab predation or wave action. There is evidence for divergent natural selection acting on size, and size-assortative mating has previously been documented. Here, we analyze the mating pattern in <i>L. saxatilis</i> with respect to size in intensively-sampled transects across boundaries between the habitats. We show that the mating pattern is mostly conserved between ecotypes and that it generates both assortment and directional sexual selection for small male size. Using simulations, we show that the mating pattern can contribute to reproductive isolation between ecotypes but the barrier to gene flow is likely strengthened more by sexual selection than by assortment.
Data from: Effects of an experimental increase in flow intermittency on an alpine stream
<p>Flow intermittency occurs naturally in alpine streams. However, changing rainfall patterns and glacier retreat are predicted to increase the occurrence of flow intermittency in alpine catchments, with largely unknown effects on ecosystem structure and function. We conducted a flow manipulation experiment within a headwater stream of Val Roseg, a glacierized alpine catchment, to determine the effects of increased flow intermittency on aquatic macroinvertebrates, periphyton, benthic organic matter, and trophic structure. Compared to an adjacent reference channel, an increase in flow intermittency reduced macroinvertebrate density, taxa richness, and the proportion of rheophilic taxa. Density and richness remained low in the manipulated channel after resumption of natural flow. Flow intermittency did not affect organic matter standing stocks, but increased assimilation of periphyton by aquatic macroinvertebrates. Predation on aquatic invertebrates by riparian spiders also increased. We attribute many of these patterns to the timing of drying, which likely excluded summer-growing cohorts of rheophilic, aerial dispersers. This study suggests that reductions in summer glacial melt and rainfall events might increase flow intermittency and lead to fundamental changes in diversity and function of alpine fluvial networks.</p>
Dataset for Gelatinous zooplankton-mediated carbon flows in the global oceans: A data-driven modeling study
<p>Gridded dataset of gelatinous zooplankton (GZ) biomass (mg C m<sup>-3</sup>) and numeric density (individuals m<sup>-3</sup>), time-averaged, in a 1-degree grid. Data are separated by phyla: Cnidaria, Ctenophora, and Chordata (pelagic tunicates). Original data compiled as part of the Jellyfish Database Initiative Project (JeDI; Condon et al. 2015, doi:10.1575/1912/7191) and converted to carbon biomass units for Lucas et al. 2014.</p> <p>Cnidarian additions to this dataset include records from the northern California Current (Brodeur et al., 2014) and Gulf of Mexico (Robinson et al., 2015). Chordata additions include salps from the Bermuda Atlantic Time Series (BATS; Stone & Steinberg, 2014), Western Antarctic Peninsula (WAP; Steinberg et al., 2015), and Southern Ocean, from KRILLBASE (Atkinson et al., 2017). Note that we excluded the KRILLBASE records from the WAP region that to prevent double-counting. See Methods in Luo et al. (2020) for details on biometric conversions to carbon biomass.</p> <p>Data were averaged by time (season, then year), and then within each 1-degree grid cell.</p> <p> </p> <p> </p> <p>Code for the model using this dataset is available at: <a href="https://github.com/jessluo/gz_biogeochem_pub">https://github.com/jessluo/gz_biogeochem_pub</a></p> <p> </p> <p><strong>Luo, Jessica Y.</strong>, Condon, R. H., Stock, C. A., Duarte, C. M., Lucas, C. H., Pitt, K. A., & Cowen, R. K. (2020). Gelatinous zooplankton‐mediated carbon flows in the global oceans: A data‐driven modeling study. <em>Global Biogeochemical Cycles</em>, 34, e2020GB006704. <a href="https://doi.org/10.1029/2020GB006704">https://doi.org/10.1029/2020GB006704</a></p>
Supporting data for "A convolution method to assess subgrid-scale interactions between flow and patchy vegetation in biogeomorphic models"
<p>Dataset necessary to reproduce the results and analyses presented in the paper:</p> <p>Gourgue, O., van Belzen, J., Schwarz, C., Bouma, T.J., van de Koppel, J. & Temmerman, S. (2020) A convolution method to assess subgrid-scale interactions between flow and patchy vegetation in biogeomorphic models, Journal of Advances in Modeling Earth Systems, submitted.</p> <p>The dataset contains:</p> <ul> <li>Process-based model simulations, including their input files and the Python scripts to generate them (pre-processing), as well as the output files and Python scripts to post-process them.</li> <li>Flume experiment data processed for the model calibration.</li> <li>Python scripts to generate the figures and tables of the manuscript.</li> </ul>
Renormalisation of the energy-momentum tensor in three-dimensional scalar SU(N) theories using the Wilson flow -- data release
<p>This repository contains the lattice two-point function measurements required to reproduce the results of the paper "Renormalisation of the energy-momentum tensor in three-dimensional scalar SU(N) theories using the Wilson flow" (<a href="https://arxiv.org/abs/2009.14767">https://arxiv.org/abs/2009.14767</a>).</p> <p>The code required to perform the data analysis can be found in <a href="https://github.com/josephleekl/scalar_emt_analysis">https://github.com/josephleekl/scalar_emt_analysis</a>.</p> <p>For any questions please get in touch: joseph.lee@ed.ac.uk </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.