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958 results for “Data quality”
Data: The effects of glucose addition and water table manipulation on peat quality of drained peatland forests with different management practices
<p>The file contain data on peat chemical quality and peat decomposition. We studied how glucose addition, water table and forest harvesting affect the chemical composition of peat and decomposition rate (carbon dioxide fluxes) and soil water quality. Experiments and results are presented in:</p> <p>Aaltonen H., Zhu X., Khatun R., Laurén A., Palviainen M., Könönen M., Peltomaa E., Berninger F., Köster K., Ojala A., Pumpanen J. 2022. The effects of glucose addition and water table manipulation on peat quality of drained peatland forests with different management practices. Soil Science Society of America Journal 86:1625–1638. <a href="https://doi.org/10.1002/saj2.20419">https://doi.org/10.1002/saj2.20419</a></p> <p> </p>
Data from: Impacts of organic matter amendments on urban soil carbon and soil quality: A meta-analysis
<p>Organic matter amendment application is an important avenue of beneficial waste diversion and is used to improve soil quality in agricultural and urban settings. In urban regions, amendments are used to support local food production, maintain vegetation for landscaping and recreational use, and reclaim disturbed soils. Urban regions generate large quantities of wasted organic resources for potential application aiding in creating a circular nutrient economy. There is a growing interest in understanding the effects of amendments such as compost, biosolids, and biochar on soil properties in agricultural settings. Gaps remain, however, in assessing their effects in urban land uses. We conducted a literature review to assess the effects of compost, biochar, and biosolids on soil carbon and soil quality of urban soils managed for gardening, landscaping, recreation, and reclamation. Application of organic matter amendments led to an average increase of 3.6 units of soil organic matter% (SOM%). Compost and biochar improved SOM% the most, by 3.1 and 6.5 units of SOM%, respectively. Biosolids resulted in the smallest increase in SOM% but had greater nutrient benefits than other amendments. Parameters related to chemical and physical soil quality improved with the application of amendments. Gaps in the literature remain, such as assessing urban gardens, soil to depths greater than 30 cm, and the persistence of SOM in amended soils. This meta-analysis proposes that organic matter amendments are a powerful means to improve soil quality in urban regions, provide vital cobenefits to surrounding communities, and increase soil carbon storage.</p>
Data for Autonomous Flow Routing for Near Real-Time Quality of Service Assurance
<p>Data of the journal paper:</p> <p>S. Barzegar, M. Ruiz and L. Velasco, "Autonomous Flow Routing for Near Real-Time Quality of Service Assurance," in IEEE Transactions on Network and Service Management, vol. 21, no. 2, pp. 2504-2514, April 2024, doi: 10.1109/TNSM.2023.3339201 (<a href="../records/10246061" target="_blank" rel="noopener">link to the paper</a>)</p> <p>This dataset has been generated within the framework of the European Commission thought the HORIZON SNS JU DESIRE6G (G.A. 101096466), the MINECO UNICO5G TIMING (TSI-063000-2021-145) and the MICINN IBON (PID2020-114135RB-I00) projects, and from the ICREA Institution. (2023-12-05).</p> <p>Additional details and updates can be checked in the following <a href="https://doi.org/10.34810/data1404" target="_blank" rel="noopener">link</a></p>
Data from "End-to-End Protocol for High-Quality QAOA Parameters with Few Shots"
<p>Data from the paper "End-to-End Protocol for High-Quality QAOA Parameters with Few Shots." The code for generating this dataset is available at <a href="https://github.com/jpmorganchase/End-to-End_Protocol_for_High-Quality_QAOA_Parameters">https://github.com/jpmorganchase/End-to-End_Protocol_for_High-Quality_QAOA_Parameters</a>.</p>
4G/LTE Channel Quality Reference Signal Traces Data Set
<p>Mobile networks, especially LTE networks are used more and more for high-bandwidth services like multimedia or video streams. The quality of the data connection plays a major role in the perceived quality of a service. Videos may be presented in a low quality or experience a lot of stalling events when the connection is to slow to buffer the next frames for playback. So far, no publicly available data set exists that has a larger number of LTE network traces and can be used for deeper analysis. In this data set, we provide 546 traces of 5 minutes each with a sample rate of 100 ms. Thereof 377 traces are pure LTE data. We furthermore provide an Android app to gather further traces as well as R scripts to clean, sort, and analyze the data. </p>
Quality check of river flow data worldwide
Quality characteristics for 21586 river flow time series from 13 datasets worldwide. The 13 datasets are: the Global Runoff Database from the Global Runoff Data Center (GRDC), the Global River Discharge Data (RIVDIS; Vörösmarty et al., 1998), Surface-Water Data from the United States Geological Survey (USGS), HYDAT from the Water Survey of Canada (WSC), WISKI from the Swedish Meteorological and Hydrological Institute (SMHI), Hidroweb from the Brazilian National Water Agency (ANA), National data from the Australian Bureau of Meteorology (BOM), Spanish river flow data from the Ecological Transition Ministry (Spain), R-ArcticNet v. 4.0 from the Pan-Arctic Project Consortium (R-ArcticNet), Russian River data (NCAR-UCAR; Bodo, 2000), Chinese river flow data from the China Hydrology Data Project (CHDP; Henck et al., 2010, 2011), the European Water Archive from GRDC - EURO-FRIEND-Water (EWA), and the GEWEX Asian Monsoon Experiment (GAME) – Tropics dataset provided by the Royal Irrigation Department of Thailand. Quality characteristics are based on availability, outliers, homogeneity and trends: overall availability (%), longest availability (%), continuity (%), monthly availability (%), outliers ratio (%), homogeneity of annual flows (number of statistical tests agreeing), trend in annual flows, trend in one month of the year. Bodo, B. (2000) Russian River Flow Data by Bodo. Boulder CO: Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Retrieved from http://rda.ucar.edu/datasets/ds553.1/ Henck, A. C., Huntington, K. W., Stone, J. O., Montgomery, D. R. & Hallet, B. (2011) Spatial controls on erosion in the Three Rivers Region, southeastern Tibet and southwestern China. Earth and Planetary Science Letters 303(1–2), 71–83. doi:10.1016/j.epsl.2010.12.038 Henck, A. C., Montgomery, David R., Huntington, K. W. & Liang, C. (2010) Monsoon control of effective discharge, Yunnan and Tibet. Geology 38(11), 975–978. doi:10.1130/G31444.1 Vörösmarty, C. J., Fekete, B. M. & Tucker, B. A. (1998) Global River Discharge, 1807-1991, V[ersion]. 1.1 (RivDIS). doi:10.3334/ornldaac/199
Experiment Data - 952 Assessments of 8 Vision Videos Regarding Overall Video Quality and 15 Individual Quality Characteristics
<p>In 2018, we conducted a within-subjects experiment to investigate how individual quality characteristics of vision videos relate to the overall quality of vision videos from a developer's point of view. 139 undergraduate students who had the role of a developer and actively developed software in projects with real customers at the time of the experiment participated in the experiment. The subjects can be considered as developers due to their experience at the time of the experiment. The subjects were put in the situation that they join an ongoing project in their familiar role as a developer. In this context, we showed the 8 vision videos (one after the other) always with the intent to share the vision of the particular project with the subjects. The undergraduate students subjectively assessed the overall quality and 15 individual quality characteristics of the 8 vision videos by completing an assessment form for each video. After data cleaning, the final data set contains 952 complete assessments of 119 subjects for the 8 vision videos.</p> <p>Each entry of the data set consists of:</p> <ul> <li>Entry ID: The ID of the entry in the dataset.</li> <li>Subject ID: The ID of the subject.</li> <li>Video ID: The ID of the vision video assessed.</li> <li>Overall quality: The subject's assessment of the overall quality of the vision video.</li> <li>Image quality: The subject's assessment of the visual quality of the image of the vision video.</li> <li>Sound quality: The subject's assessment of the auditory quality of the sound of the vision video.</li> <li>Video length [s]: The duration of the vision video in seconds.</li> <li>Focus: The subject's assessment of the compact representation of the vision which is presented in the vision video.</li> <li>Plot: The subject's assessment of the structured presentation of the content of the vision video.</li> <li>Prior knowledge: The subject's assessment of the presupposed prior knowledge to understand the content of the vision video.</li> <li>Clarity: The subject's assessment of the intelligibility of the aspired goals of the vision which is presented in the vision video.</li> <li>Essence: The subject's assessment of the amount of important core elements, e.g., persons, locations, and entities, which are to be presented in the vision video.</li> <li>Clutter: The subject's assessment of the amount of disrupting and distracting elements, e.g., background actions or noises, that can be inadvertently recorded in the vision video.</li> <li>Completeness: The subject's assessment of the coverage of the three contents of a vision which is presented in the vision video, i.e., the considered problem, the proposed solution, and the improvement of the problem due to the solution.</li> <li>Pleasure: The subject's assessment of the enjoyment of watching the vision video.</li> <li>Intention: The subject's assessment of how well the vision video is suitable for the intended purpose of the given scenario.</li> <li>Sense of responsibility: The subject's assessment of the compliance of the vision video with legal regulations.</li> <li>Support: The subject's assessment of his or her level of acceptance of the vision which is presented in the vision video.</li> <li>Stability: The subject's assessment of the consistency of the vision which is presented in the vision video.</li> </ul> <p>This dataset includes the following files:</p> <ul> <li>"Dataset_Assessments.xlsx" contains the anonymized 952 assessments of the 119 subjects for the 8 vision videos</li> <li>"Assessment_form.docx" contains the assessment form which was used to assess each of the 8 vision videos</li> <li>"Assessment_form.pdf" contains the assessment form which was used to assess each of the 8 vision videos</li> </ul> <p>The 8 vision videos are not included in this dataset since we do not have the explicit consent of the actors to distribute the vision videos.</p> <p>This experiment was designed, conducted, and analyzed by Oliver Karras (<a href="https://twitter.com/KarrasOliver">@KarrasOliver</a>), Kurt Schneider, and Samuel A. Fricker (<a href="https://twitter.com/samuelfricker">@samuelfricker</a>).</p>
Data for publication on the impact of two different nutrition education methods on the quality of life of children and adolescents with type 1 diabetes (randomized study)
<p>Data present changes in the quality of life 6 months after the educational intervention applied in the group of children and adolescents with type 1 diabetes.</p>
Energy-dependence of the response of X-ray multimeter for mammography- radiation qualities - Supplemental Data
<p>Supplementary data to the manuscript “Energy-dependence of the response of X-ray multimeter for mammography- radiation qualities” by Elisabeth Salomon and Paula Toroi</p>
Translanguaging experimental research: list of eligible studies and quality assessment data
Open the record for dataset details and reuse information.
Meteorological, hydrological and water quality data of the Bahe River
<p>This dataset includes climate data from 1951 to 2020, and monthly streamflow, sediment, total nitrogen (TN), and phosphorus (TP) concentrations data observed from 2016 to 2020 for Bahe River Basin. The data is intended for research on SWAT setup, calibration, and validation.</p>
Quality Assessment of YUNYAO GNSS-RO Refractivity Data in the Neutral Atmosphere
Open the record for dataset details and reuse information.
An Exploratory Study on Code Quality, Testing, Data Accuracy, and Practical Use Cases of IoT Wearables
<p>Data used in IoT Wearable Study</p>
Water Quality Data - Four Lakes in Kraków, Poland
<p>This dataset provides comprehensive water quality measurements from four lakes in Kraków, Poland: Staw Płaszowski, Zalew Nowohucki, the Pond in Park Lotników, and Staw Dąbski. It includes key parameters such as chlorophyll-a concentration, cyanobacteria levels, and turbidity. Additionally, Trophic State Index (TSI) values for each lake have been calculated based on the Carlson (1977) method.</p> <p> </p>
The streamflow and water quality data for two catchments in the Bavarian Forest National Park, Germany
<p>This dataset was used in a study to support modeling simulations of catchment runoff and nitrogen export in streams following forest dieback caused by bark beetles.</p> <p>Große Ohe data were provided by the Bavarian Environment Agency (LFU) (https://www.lfu.bayern.de/wasser/gewaesserqualitaet_fluesse/messnetze/index.htm).<br>The data are available from the Gewässerkundlicher Dienst:<br>For runoff:<br>https://www.gkd.bayern.de/en/rivers/discharge/passau/taferlruck-17413000<br>For runoff chemistry:<br>https://www.gkd.bayern.de/de/fluesse/chemie/passau/taferlruck-messstation-11801/gesamtzeitraum</p> <p>Forellenbach data were provided by the Federal Environment Agency (UBA).<br>The Forellenbach catchment is part of the Integrated Monitoring Programme under the UNECE Convention on Long-Range Transboundary Air Pollution (1979). https://www.umweltbundesamt.de/themen/luft/messenbeobachtenueberwachen/medienuebergreifendes-monitoring-in-der#icp-integrated-monitoring</p> <p>The main runoff and runoff chemistry data used in the study are shown in the file, and please see original data sources for more information.</p>
Data from: Measuring couple relationship quality in a rural African population: validation of a couple functionality assessment tool in Malawi
Available data suggest that individual and family well-being are linked to the quality of women's and men's couple relationships, but few tools exist to assess couple relationship functioning in low and middle-income countries. In response to this gap, Catholic Relief Services has developed a Couple Functionality Assessment Tool (CFAT) to capture valid and reliable data on various domains of relationship quality. This tool is designed to be used by interventions which aim to improve couple and family well-being as a means of measuring the effectiveness of these interventions, particularly related to couple relationship quality. We carried out a validation study of the CFAT among 401 married and cohabiting adults (203 women and 198 men) in rural Chikhwawa District, Malawi. Using psychometric scales, the CFAT addressed six domains of couple relationship quality (intimacy, partner support, sexual satisfaction, gender roles, decision-making, and communication and conflict management), and included questions on intimate partner violence. We used exploratory factor analysis to assess scale performance of each domain and produce a shortened Relationship Quality Index (RQI) composed of items from five relationship quality domains. This article reports the performance of the RQI. Internal reliability and validity of the RQI were found to be good. Regression analyses examined the relationship of the RQI to outcomes important to health and development: intra-household cooperation, positive health behaviors, intimate partner violence, and gender-equitable norms. We found many significant correlations between RQI scores and these couple- and family-level development issues. There is a need to further validate the tool with use in other populations as well as to continue to explore whether the observed linkages between couple functionality and development outcomes are causal relationships.
Data from: Individual quality and age but not environmental or social conditions modulate costs of reproduction in a capital breeder
Costs associated with reproduction are widely known to play a role in the evolution of reproductive tactics with consequences to population and eco-evolutionary dynamics. Evaluating these costs as they pertain to species in the wild remains an important goal of evolutionary ecology. Individual heterogeneity, including differences in individual quality (i.e., among-individual differences in traits associated with survival and reproduction) or state, and variation in environmental and social conditions can modulate the costs of reproduction; however, few studies have considered effects of these factors simultaneously. Taking advantage of a detailed, long-term dataset for a population of feral horses (Sable Island, Nova-Scotia, Canada), we address the question of how intrinsic (quality, age), environmental (winter severity, location), and social conditions (group size, composition, sex ratio, density) influence the costs of reproduction on subsequent reproduction. Individual quality was measured using a multivariate analysis on a combination of four static and dynamic traits expected to depict heterogeneity in individual performance. Female quality and age interacted with reproductive status of the previous year to determine current reproductive effort, while no effect of social or environmental covariates was found. High quality females showed higher probabilities of giving birth and weaning their foal regardless of their reproductive status the previous year, while those of lower quality showed lower probabilities of producing foals in successive years. Middle-aged (prime) females had the highest probability of giving birth when they had not reproduced the year before but no such relationship with age was found among females that had reproduced the previous year, indicating that prime-aged females bear higher costs of reproduction. We show that individual quality and age were key factors modulating the costs of reproduction in a capital breeder but that environmental or social conditions were not, highlighting the importance of considering multiple factors when studying costs of reproduction.
Data from: Asymmetric introgression between fishes in the Red River basin of Texas is associated with variation in water quality
When ecologically divergent taxa encounter one another, hybrid zones can form when reproductive isolation is incomplete. The location of such hybrid zones can be influenced by environmental variables, and an ecological context can provide unique insights into the mechanisms by which species diverge and are maintained. Two ecologically differentiated species of small benthic fishes, the endemic and imperiled prairie chub, Macrhybopsis australis, and the shoal chub, Macrhybopsis hyostoma, are locally sympatric within the upper Red River Basin of Texas. We integrated population genomic data and environmental data to investigate species divergence and the maintenance of species boundaries in these two species. We found evidence of advanced-generation asymmetric hybridization and introgression, with shoal chub alleles introgressing more frequently into prairie chubs than the reciprocal. Using a Bayesian Genomic Cline framework, patterns of genomic introgression were revealed to be quite heterogeneous, yet shoal chub alleles were found to have likely selectively introgressed across species boundaries significantly more often than prairie chub alleles, potentially explaining some of the observed asymmetry in hybridization. These patterns were remarkably consistent across two sampled geographic regions of hybridization. Several environmental variables were found to significantly predict individual admixture, suggesting ecological isolation might maintain species boundaries.
Poor quality monitoring data underestimate the impact of Australia's megafires on a critically endangered songbird
<p>Aim: Catastrophic events such as south-eastern Australia's 2019/20 megafires are predicted to increase in frequency and severity under climate change. Rapid, well-informed conservation prioritisation will become increasingly crucial for minimising biodiversity losses resulting from megafires. However, such assessments are susceptible to bias, because the quality of monitoring data underpinning knowledge of species' distributions is highly variable and they fail to account for differences in life-history traits such as aggregative breeding. We aimed to assess how impact estimates of the 2019/20 megafires on the critically endangered regent honeyeater <i>Anthochaera phrygia </i>varied according to the quality of available input data and assessment methodology.</p> <p>Innovation: Using Google Earth Engine Burnt Area Mapping, we estimated the impact of the megafires on the regent honeyeater using six monitoring datasets that differ in quality and temporal span. These datasets are representative of the variable quality of monitoring data available for assessing fire impact on 326 other threatened species; most are poorly monitored and few have standardised, species-specific monitoring programs. We found that assessments based on Area of Occupancy (AOO), Extent of Occurrence (EOO) and public sightings underestimated the fire impact relative to recent, targeted monitoring datasets; a MaxEnt model, sightings from a national monitoring program and nest locations since 2015. Using an impact threshold of 30% of habitat burned, regent honeyeaters would not meet this criteria using estimates derived from EOO, AOO or public sightings, but would exceed the cut-off based on estimates derived from the targeted monitoring data that account for population density.</p> <p>Main conclusions: To ensure that conservation prioritisation has the greatest capacity to minimise biodiversity losses, we highlight the need to improve targeted, threatened species monitoring. We demonstrate the importance of using recent, standardised monitoring data to estimate accurately the impact of major ecological disturbances, particularly for declining, nomadic species undergoing range contractions.</p>
Air Quality Forecasts Improved by Combining Data Assimilation and Machine Learning with Satellite AOD
<p>Input data for random forest model. </p> <p> </p> <p>1) UM_RDAPS.egg file: It provides analysis and forecast products four times a day (00, 06, 12, 18 UTC) in 12 km x 12 km spatial resolution. In this study, analysis products were only considered as the input variables (i.e., 2m temperature and dew-point temperature, relative humidity (RH), maximum wind speed, visibility at height above the ground, planetary boundary layer height (PBLH), and surface pressure). The accumulated maximum wind speed during 1, 3, 5, 7 days were also used in this study.</p> <p>2) data_1.zip file: GOCI Aerosol product, MODIS Land cover, MODIS NDVI, Population density, Road density, SRTM_DEM. </p> <p> </p> <p>The detailed information of input variables is written in the supporting information of the paper.</p> <p> </p> <p> </p> <p> </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.