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.
2,308
datasets available to search
ShareScore release 0.9.0
Dataset results
2,308 results for “interaction data”
Lab disease outcomes data evaluating how antibiotic tolerant vs. non-tolerant cell-free supernatant from Pseudomonas aeruginosa affects the interaction between a fungal pathogen (Batrachochytrium dendrobatidis) and amphibian (Rana sylvaticus), 2022.
Microbes living on hosts and in the environment can play a key role in helping hosts to combat pathogens. However, antibiotic-induced alterations to microbial metabolite production could disrupt this dynamic. Here, we investigated whether antibiotic tolerance influences the anti-pathogenic properties of host-associated (living on the host; biofilms) and environmental (living in the soil of water column; planktonic) microbes in vitro and in vivo. For our model host and pathogen, we used the amphibian (Rana sylvatica)-Batrachochytrium dendrobatidis (Bd) system. For our model host-associated (biofilm) and environmental (planktonic) microbes, we used four strains of Pseudomonas aeruginosa that vary in their tolerance to antibiotics and their biofilm-forming capabilities: Planktonic, non-antibiotic tolerant (ΔsagS/VC); Planktonic, antibiotic tolerant (ΔsagS::sagS_L154A); Biofilm, non-antibiotic tolerant (ΔsagS::sagS_D105A); Biofilm, antibiotic tolerant (ΔsagS::sagS). We collected cell-free supernatants (CFS) from each strain to examine the effects of metabolites. We conducted four experiments. In our pathogen-only exposures to test direct effects of metabolites on Bd, we exposed Bd zoospores to each P. aeruginosa CFS at six concentrations. After 11 days of growth, we measured relative abundance of Bd across each treatment. In our host-only exposures to test effects of metabolites on host disease outcomes, we placed R. sylvatica tadpoles in individual units containing each P. aeruginosa CFS. After 48 hours, water was changed into clean well water (no CFS). Bd zoospores were immediately added to each experimental unit following the water change. After 5 days of Bd exposure, we measured snout-vent length (SVL), mass, developmental stage, and Bd quantification in the mouthparts using qPCR for each tadpole. In our host-pathogen exposures to test interactive effects of metabolites on hosts in the presence of the pathogen, we conducted the same experiment as above. However, ins
Data from: mPRIME Study - Interaction of Insulin Resistance with Cognition, Lifestyle, and Mental Health
<p>The presented datasets were collected within the <em>m</em>PRIME study, a prospective, observational study of the H2020 project Prevention and Remediation of Insulin Multimorbidity in Europe (PRIME) (grant No. 847879). The study investigates the interaction of insulin resistance with cognition, lifestyle, and mental health by combining traditional methods with ambulatory assessment and sensor-based data collection. Recruitment took place between March 2021 and March 2023 at the University Hospital Frankfurt, Germany.</p> <p>The eligibility criteria for the study were as follows: Age above 18 years, no intake of antidiabetic medication, insulin or glucocorticoids, no existing type 1 diabetes mellitus or gestational diabetes, no diagnoses of bipolar I disorder, schizophrenia, organically caused mental disorders and substance dependence, no severe neurological disorders, no current pregnancy or breastfeeding, no non-correctable visual impairments, no participation in medication-related studies within the last 6 months, no use of weight-reducing medications or a diet within the last 3 months, sufficient proficiency in German to complete questionnaires and neuropsychological tests.</p> <p>All participants in the <em>m</em>PRIME study provided written informed consent. The study protocol and procedures were approved by the local ethics committee.</p> <p><strong>Study Design</strong></p> <p>Individuals completed a baseline assessment and a one-week ambulatory assessment. The baseline assessment included: socio-demographic information, blood samples, anthropometric measures, neuropsychological tests, and several questionnaires. In addition, individuals were introduced to smartphone-based ecological momentary assessment (EMA), food protocols, and the use of sensors (continuous glucose monitor, accelerometer). Food protocols and EMA were conducted on three consecutive days, including two weekdays and one weekend day (Thursday to Saturday or Sunday to Tuesday). Several times a day, individuals were prompted via their smartphone to complete a working memory task and answer questions about stress, affect, and food intake. The continuous glucose monitor and accelerometer were worn continuously for 1 week.</p> <p> </p>
Data for "Measurement of the atom-surface van der Waals interaction by transmission spectroscopy in a wedged nano-cell"
<p>The data presented in publication <a href="http://arxiv.org/abs/1905.02783">"Measurement of the atom-surface van der Waals interaction by transmission spectroscopy in a wedged nano-cell"</a> . Published version: <a href="https://doi.org/10.1103/PhysRevA.100.022503">https://doi.org/10.1103/PhysRevA.100.022503</a></p> <p>The data are in HDF5 format, with associated metadata.</p> <p>To see examples of how to use the data, and the theoretical model for analysis, see <a href="https://github.com/thermal-vapours/TAS-Transmission-Atom-Surface">https://github.com/thermal-vapours/TAS-Transmission-Atom-Surface </a></p>
Supplemental data for characterization of alpha and beta interactions using the HeXe setup [Eur. Phys. J. C 82, 361]
<p>Repository with supplemental data to:<br> <strong>Characterization of alpha and beta interactions in liquid xenon</strong>. Jörg, F., Cichon, D., Eurin, G. <em>et al. Eur. Phys. J. C</em> <strong>82, </strong>361 (2022) <a href="https://doi.org/10.1140/epjc/s10052-022-10259-3">10.1140/epjc/s10052-022-10259-3</a><br> A pre-print of the article is available <em>on arXiv: </em><a href="http://arxiv.org/abs/2109.13735">2109.13735</a></p> <p><strong>Note: </strong>When re-using the data, please make sure to cite the article (and not only the dataset)</p> <p><br> The files contain the measured data points (as well as their statistical and systematic uncertainties) as shown in the publication.<br> All datasets are stored in the .csv format.</p> <ul> <li><strong>20210924_yields_hexe_kr83m.csv</strong><br> This file contains the normalized light and charge yields as a function of the applied field from the measurement with the <sup>83m</sup>Kr source. The data is shown in Figure 16 (dots) of the publication. Furthermore the file contains the LY ratio between the two Isomeric transitions of the <sup>83m</sup>Kr source, shown in Figure 17 of the article.</li> <li><strong>20210924_yields_hexe_rn222.csv</strong><br> This file contains the normalized light and charge yields as a function of the applied field from the measurement with the <sup>222</sup>Rn source. The data is shown in Figure 18 (blue-ish points) of the publication</li> <li><strong>20210924_drift_velocity_hexe_rn222.csv</strong><br> This file contains the measured electron drift velocity in liquid xenon at a temperature of 174.4 K in dependence of the field. The data was acquired using the <sup>222</sup>Rn source. Drift velocity is given in units of mm/µs and the datapoints are shown in Figure 20 (black dots) of the publication </li> <li><strong>20210924_drift_velocity_hexe_kr83m.csv</strong><br> This file contains the measured electron drift velocity in liquid xenon at a temperature of 174.4 K in dependence of the field. The data was acquired using the <sup>83m</sup>Kr source. Drift velocity is given in units of mm/µs and are not displayed in the publications due to visibility reasons.</li> </ul> <p><strong>Minimum working example to plot the drift velocity using the <sup>83m</sup>Kr data:</strong></p> <pre><code class="language-python"> 1 import numpy as np 2 import matplotlib.pyplot as plt 3 4 # load the data set 5 data = np.loadtxt("20220427_drift_velocity_hexe_kr83m.csv", delimiter=",") 6 7 # Plot the systematic uncertainty on the drift field 8 plt.errorbar(data[:,0], data[:,2], xerr=data[:,1], fmt="o", capsize=2, ecolor="darkgray", 9 alpha=0.7, elinewidth=3, color="black") 10 11 # Plot the actual data points 12 plt.errorbar(data[:,0], data[:,2], yerr=data[:,3], fmt="o", color="black") 13 14 # Label the axis and define the range 15 plt.ylabel("Drift Velocity [mm/µs]") 16 plt.xlabel("Drift Field [kV/cm]") 17 plt.xscale("log") 18 plt.xlim(0.006, 2) 19 plt.ylim(0, 2.4) 20 plt.show() </code></pre> <p> </p>
Raw Data for "RASER MRI: Magnetic Resonance Images formed Spontaneously exploiting Cooperative Nonlinear Interaction"
<p>This upload contains the raw data used for Fig. 3-5 in "RASER MRI: Magnetic Resonance Images formed Spontaneously exploiting Cooperative Nonlinear Interaction". Experimental conditions and details about the datasets are given in a "ReadMe.txt" file.</p>
How does Mg2+(aq.) interact with ATP(aq.)? Observations through the lens of liquid-jet photoelectron spectroscopy - data
<p>Dataset pertaining to the article "How does Mg2+(aq) interact with ATP(aq)? Biomolecular Structure through the Lens of Liquid-Jet Photoemission Spectroscopy", published in Journal of the American Chemical Society (<a href="https://doi.org/10.1021/jacs.4c03174" target="_blank" rel="noopener">doi: 10.1021/jacs.4c03174</a>). Here, we arrive at new information on the interaction of ATP with Mg under physiological conditions by interpreting photoelectron spectra and intermolecular Coulombic decay from a liquid microjet.</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.07, see<br>https://www.nexusformat.org/<br>https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br>NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br>* nexpy (distributed with python)<br>* https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br>1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data'). For ATP spectra, the ADP overview spectrum, and ADP/Mg2+ Mg 2s spectra, a binding energy correction shifting the liquid 1b1 feature to 11.33 eV is applied.<br>2. As-measured data ('raw').</p> <p>Files with extension .txt are comma-separated ascii-files.</p> <p><br>The following files are provided:</p> <p>Photoemission data pertaining to adenosine phosphate PES measurements:<br>atp-mg.h5 - ATP photoemission spectra in the presence of Mg2+ cations in varying concentration<br>adp-mg.h5 - ADP photoemission spectra in the presence of Mg2+ cations in varying concentration<br>amp-mg.h5 - AMP photoemission spectra in the presence of Mg2+ cations (a single concentration)<br>atp-adp-amp.h5 - ATP, ADP, AMP photoemission without Mg admixture<br>mg-only.h5 - Mg 2s core level spectra without ATP<br>tham-only.h5 - VB band measured with only THAM (tris(hydroxymethyl)aminomethane), used as buffer for pH stabilization<br>atp-icd.h5 - ATP photoemission spectra in the presence of Mg2+ cations, kinetic energy range of ICD features (publication is based on the last three entries).<br><br></p> <p>Numeric representations of the traces shown in the article's figures:<br>Figure_3-data.txt<br>Figure_5a-Mg2p.txt<br>Figure_5a-Mg2s.txt<br>Figure_5a-Mgonly.txt<br>Figure_5a-P2p.txt<br>Figure_5a-P2s.txt<br>Figure_5b.txt<br>Figure_5c.txt<br>Figure_6-ADP.txt<br>Figure_6-AMP.txt<br>Figure_6-ATP.txt<br>Figure_8a-data.txt<br>Figure_S2-Tris.txt<br>Figure_S2-Tris_with_Mg2+.txt<br>Figure_S4-data.txt.</p> <p>Version history<br>3: updated to reflect changes in Figure numbering between ArXiv-post and version published in JACS, additional Figure 5-data added<br>2: NeXus-data added<br>1: initial upload</p> <p>Contact person for questions regarding this data set: Uwe Hergenhahn, uhe@fhi.mpg.de . If you use these data for your scientific work we are curious to learn about it.</p>
Anthropomorphic Mechanisms for User Acceptance in Human-Robot Interaction - PRISMA pass data
<p>This is the data produced in the course of selecting relevant literature for the <em>"User Acceptance in Human-Robot Interaction"</em> literature review article.</p> <p><strong>Contents:</strong></p> <ul> <li>Initial pass records: <em>prisma0_wos.xlsx + prisma0_scopus.xlsx</em></li> <li>Initial pass eligibility assessment:<em><strong> </strong>prisma0_eval.xlsx</em></li> <li>Second pass records, filtering and coarse assessment:<em><strong> </strong>prisma1.xlsx</em></li> <li>Third pass records, filtering and coarse assessment:<em><strong> </strong>prisma2.xlsx</em></li> <li>Fine eligibility assessment of 2nd and 3rd pass: <em>prisma_avalanche_1_and_2_report_update_04_26.pdf</em></li> </ul> <p> </p>
Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions
<p>Files generated from the study described in <a href="https://doi.org/10.1101/2024.02.08.579534">Fernandes et. al (2024)</a> .</p> <p>The file "cvs_h2s.csv" comprises the coefficient of variation and the Cullis heritability for each environment.</p> <p>The file "all_predictions.csv" contains the predictions from all the models evaluated, in different cross-validation (CV) scenarios.</p> <p>The file "coincidence_index.csv" has the Coincidence Index (CI) for each CV and models evaluated in our study.</p> <p>Our study used the multi-environment maize yield trials data from the Genomes to Fields 2022 initiative (<a href="https://doi.org/10.1186/s13104-023-06421-z">Lima et. al 2024</a>).</p>
Drug Interaction Study Data from the Drug Approval Package for Epidiolex (Cannabidiol)
<p>Data from the drug interaction studies reported in the drug approval package for Epidiolex (cannabidil), U.S. Food and Drug Administration: https://www.accessdata.fda.gov/drugsatfda_docs/nda/2018/210365Orig1s000TOC.cfm.</p> <p>The data was manually extracted by a trained pharmacist from the PDF documents uploaded to drugs@fda for Epidolex drug approval package. The data extraction was reviewed for quality by an expert in pharamacology and natural product-drug interactions.</p>
Coherent vortex dynamics in a strongly-interacting superfluid on a silicon chip: Experimental and simulation data sets
<p>This data set collates the experimental and simulation data for the research paper "Coherent vortex dynamics in a strongly-interacting superfluid on a silicon chip".</p>
Bee Interaction Data from Global Biotic Interactions
<p>New versions of this dataset are found at: <a href="https://doi.org/10.5281/zenodo.16689326">https://doi.org/10.5281/zenodo.16689326</a></p> <p> </p> <p>This repository includes the following:</p> <ol> <li><strong>interactions-GloBI-September-14-2021.tsv.gz</strong>: a full version of the Global Biotic Interactions downloaded on September 14, 2021. No data transformations have occurred on this dataset after the download</li> <li><strong>globi_bee_data.sh</strong>: Shell script for extracting bee records using bee family names from the full version of Global Biotic Interactions</li> <li><strong>all_bee_data_unique.txt</strong>: a file that includes only bee interactions, based on extracting bee names from interactions-GloBI-September-14-2021.tsv.gz</li> </ol> <p>Global Biotic Interactions (GloBI - https://globalbioticinteractions.org) aims to simplify access to existing records of species interactions, such as predator-prey, plant-pollinator, and virus-host interactions. To achieve this, GloBI follows a process where existing, versioned datasets on species interactions are transformed into various aggregate formats, including tsv, csv, neo4j, rdf/nquad, and darwin core-ish archives, with applied name maps included for explicit taxonomic linking.</p> <p>GloBI owes its success to researchers, collections, projects, and institutions that openly share their datasets. Whenever you use this data, please credit the original data contributors, including citing the specific datasets used in derivative work. Each species interaction record in GloBI is linked to a reference and dataset citation. If you have any suggestions on how to make it easier to cite original datasets, you are welcome to join a discussion on https://globalbioticinteractions.org or related projects.</p> <p><strong>Introduction to Global Bee Interaction Data</strong></p> <p>The dataset available here includes all bee interactions recorded in the <a href="https://www.globalbioticinteractions.org/">Global Biotic Interactions</a> (GloBI; Poelen et al. 2014) index as of September 21, 2021. These interactions are gathered quarterly by the <a href="http://big-bee.net/">Big Bee Project </a>(Seltmann et al. 2021) from various sources, including natural history collections, community science observations (such as iNaturalist), and scientific literature. The dataset covers a wide range of bee interactions, including flower visitation, parasitic interactions (such as mite and viral interactions), and lecty, among others. The dataset is filtered for unique records based on interaction description and source citation to ensure accuracy and consistency. For other versions of the bee interaction dataset, please refer to <a href="https://zenodo.org/record/7315159">Seltmann, 2022</a>.</p> <p><strong>Data Description</strong><br>Please see the <a href="https://www.globalbioticinteractions.org/process">integration process page</a> to better understand how Global Biotic Interactions combines datasets from various sources. The complete interaction dataset for all species can be accessed via <a href="https://www.globalbioticinteractions.org/data">https://www.globalbioticinteractions.org/data</a> and the <a href="https://doi.org/10.5281/zenodo.3950589">GloBI Community Zenodo publication</a>.</p> <p><strong>Dataset column names</strong> definitions <a href="https://api.globalbioticinteractions.org/interactionFields">https://api.globalbioticinteractions.org/interactionFields</a> or <a href="https://api.globalbioticinteractions.org/interactionFields">https://api.globalbioticinteractions.org/interactionFields</a></p> <p><strong>References</strong></p> <p>Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. <a href="https://doi.org/10.1016/j.ecoinf.2014.08.005">https://doi.org/10.1016/j.ecoinf.2014.08.005</a></p> <p>Katja C. Seltmann. (2022). Global Bee Interaction Data (v2.02) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.7315159">https://doi.org/10.5281/zenodo.7315159</a></p> <p>Seltmann KC, Allen J, Brown BV, Carper A, Engel MS, Franz N, Gilbert E, Grinter C, Gonzalez VH, Horsley P, Lee S, Maier C, Miko I, Morris P, Oboyski P, Pierce NE, Poelen J, Scott VL, Smith M, Talamas EJ, Tsutsui ND, Tucker E (2021) Announcing Big-Bee: An initiative to promote understanding of bees through image and trait digitization. Biodiversity Information Science and Standards 5: e74037. <a href="https://doi.org/10.3897/biss.5.74037">https://doi.org/10.3897/biss.5.74037</a></p>
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-1 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-1 site automated weather station and associated soil substation at several temporal scales. Air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths. The nearest precipitation data is available from CSIS Block-2 site automated weather station located 309m distance.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-2 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-2 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-3 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-3 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-4 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-4 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-5 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-5 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-6 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-6 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-7 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-7 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-8 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-8 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
Meteorology and soil moisture data collected at multiple frequencies from the Cross-scale Interactions Study (CSIS) Block-9 site automated monitoring stations: Jornada Basin LTER, 2013 - ongoing
This dataset contains summary data collected at the Jornada Basin LTER program's Cross Scale Interactions Study (CSIS) Block-9 site automated weather station and associated soil substation at several temporal scales. Precipitation data are collected at 1-second frequency during rain events, air temperature and wind are summarized every 5-minutes, and all aboveground sensors are summarized at 30-minute, hourly and daily frequencies. Soil moisture is measured at a 30-minute frequency and summarized daily. Observed values include average/maximum/minimum air temperature, relative humidity, and wind speed; average wind direction; soil moisture, temperature and conductivity. Aboveground sensors are measured and calculated based on 1-second scan rate. Soil moisture is measured every 30-minutes near the weather station and approximately 30-meters distance at a nearby substation. Wind speed is measured at 37cm, 75 cm, 150 cm, and 300 cm, wind direction at approximately 3m, and air temperature and relative humidity at approximately 2.5m. Soil sensors are installed at 10, 20 and 30cm depths.
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.