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88 results for “Data quality assessment”
Supporting data for the manuscript "Protein quality assessment with graph convolution guided by a loss function designed for high quality decoys"
<p>This dataset provides the predictions of the protein quality<br> assessment method Q_epsilon with respect to CASP13 and CASP14, as well<br> as a snapshot of the github repository providing the code for the<br> method.<br> The format of the file is as follows: The first column represents the<br> target and decoy names in the format <target name>_<decoy name>. The<br> second column is the true GDTTS, and the third column represents the<br> predicted GDTTS by Q_epsilon.</p>
Training Data for "Creating Quality FAIR assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS"
<p>Training Data for "Training Data for "Creating Quality FAIR assessment reports and draft of Data Papers from EML metadata with MetaShRIMPS""</p>
Assessment of the quality of water for human consumption in the Laguna Verde area of Valparaiso in Central Chile (DATA)
<p>Data set paper Assessment of the quality of water for human consumption in the Laguna Verde area of Valparaiso in Central Chile .</p>
Data Sets: An Assessment of Water Trusts: Drinking Water Quality and Provision in Six Low-income, Peri-urban Communities of Lusaka, Zambia
<p>Data set associated with the manuscript published in GeoHealth titled An Assessment of Water Trusts: Drinking Water Quality and Provision in Six Low-income, Peri-urban Communities of Lusaka, Zambia. This includes bacterial, nitrate, specific conductance, and Water Trust survey data collected from Lusaka, Zambia in 2013, 2014, 2016, an 2019.</p>
Questionnaires and Raw Data for the Paper "Operationalised Product Quality Models and Assessment: The Quamoco Approach"
<p>This paper contains the quantitative data from several interviews along with a used questionnaire for empirically investigating the software quality models created in the project Quamoco.</p>
Linked Data Quality Assessment for Datasets on the LOD Cloud
<p><strong>For more up to date quality metadata, please visit https://w3id.org/lodquator</strong></p> <p>This dataset is a collection of TRiG files with quality metadata for different datasets on the LOD cloud. Each dataset was assessed for</p> <ol> <li>The length of URIs</li> <li>Usage of RDF primitives</li> <li>Re-use of existing terms</li> <li>Usage of undefined terms</li> <li>Usage of blank nodes</li> <li>Indication for different serialisation formats</li> <li>Usage of multiple languages</li> </ol> <p>This data dump is part of the empirical study conducted for the paper "Are LOD Cloud Datasets Well Represented? A Data Representation Quality Survey."</p> <p>For more information visit http://jerdeb.github.io/lodqa</p>
Data from: Freshwater ecological quality assessment of the gold mining Mashcon watershed, Cajamarca - Peru
<p>These data were generated to investigate the aquatic community gradients across different types of anthropogenic impacts (reference, mining, rural and urban) and Andean environmental gradients (headwaters, midstream and downstream) in the Mashcon watershed. </p> <p>The macroinvertebrates' taxa abundance and abundance of traits modalities serve as biological values. The latter in combination with abiotic measurements of the freshwater habitats (i.e. physicochemical water quality and hydromorphology) constitute the ecological data.</p> <p>The values were obtained from river sediments (macroinvertebrates collection), water samples for laboratory analyses, field protocols and in-situ water quality measurements at 40 sites, wherein 6 were downstream of the gold mine's artificially recharged headwaters, 8 sites at near-pristine headwaters tributary streams, 14 sites at midstream rural areas and 12 sites at downstream urban areas (sample grouping information is shown in the Field_protocol.xlsx file).</p>
Fig. 3 in Assessing the quality of biogeochemical coastal data: a step-wise procedure Abstract
Fig. 3: Workflow of the quality control procedure and quality flag (QF) attribution.
Air quality data from the article "Typhoon-associated air quality over the Guangdong–Hong Kong–Macao Greater Bay Area, China: machine-learning-based prediction and assessment"
<p>This dataset consists of 26 files. The descriptions of the files are as follows:</p> <ul> <li>aqi_TY.csv, pm25_TY.csv, pm10_TY.csv, so2_TY.csv, no2_TY.csv and o3_TY.csv are the observed values of AQI and concentrations of PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub> and O<sub>3</sub> of 36 monitoring stations used in model establish stage on TY days. The time range is June 2014 to December 2020.</li> <li>aqi_NTY.csv, pm25_NTY.csv, pm10_NTY.csv, so2_NTY.csv, no2_NTY.csv and o3_NTY.csv are the observed values of AQI and concentrations of PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub> and O<sub>3</sub> of 36 monitoring stations used in model establish stage on NTY days. The time range is June 2014 to December 2020.</li> <li>station_info.csv is the detailed information of the 36 monitoring stations used in model establish stage, including station number, city, longitude and latitude.</li> <li>aqi_TY_testing.csv, pm25_TY_testing.csv, pm10_TY_testing.csv, so2_TY_testing.csv, no2_TY_testing.csv and o3_TY_testing.csv are the observed values of AQI and concentrations of PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub> and O<sub>3</sub> of 3 monitoring stations used for testing the model on TY days. The time range is June 2014 to December 2020.</li> <li>aqi_NTY_testing.csv, pm25_NTY_testing.csv, pm10_NTY_testing.csv, so2_NTY_testing.csv, no2_NTY_testing.csv and o3_NTY_testing.csv are the observed values of AQI and concentrations of PM<sub>2.5</sub>, PM<sub>10</sub>, SO<sub>2</sub>, NO<sub>2</sub> and O<sub>3</sub> of 3 monitoring stations used for testing the model on NTY days. The time range is June 2014 to December 2020.</li> <li>sta_testing.csv is the detailed information of the 3 monitoring stations used for testing the model, including station number, city, longitude and latitude.</li> </ul>
Data from: Validation of Quality-of-Life assessment tool for Ethiopian old age people
<p><strong>Background</strong>: Reliable quality of life assessment is critical for identifying health issues, evaluating health interventions, and establishing the best health policies and care packages. The World Health Organization Quality of Life-Old Module is a tool for assessing the subjective quality of life in old age people. It's validated and available in more than 20 languages, except Amharic. Hence, this study was intended to translate it into Amharic language and validate it among old age people in Ethiopia.</p> <p><strong>Methods</strong>: A cross-sectional study was conducted among 180 community-dwelling old age people in Ethiopia, from January 16 to March 13, 2021. Psychometric validation was achieved through Cronbach's alpha of the internal consistency reliability test, and construct validity from confirmatory factor analysis.</p> <p><strong>Results</strong>: The study participants aged from 60 to 90 years old with a mean age of 69.44. Females made up 61.7% of the population, and 40% of them could not read and write. The results showed a relatively low level of quality of life, with the total transformed score of 58.58 ± 23.15. The Amharic version of the World Health Organization Quality of Life-Old Module showed a Cronbach's Alpha value of 0.96 and corrected item-total correlations of more than 0.74. Confirmatory factor analysis confirmed the six-factor model with a chi-square (X2) of 341.98 with a p-value less than 0.001. The comparative fit index (CFI) was 0.98, Tucker-Lewis's index (TCL) was 0.97, and the root mean square error of approximation (RMSEA) was 0.046.</p> <p><strong>Conclusion</strong>: The Amharic version of the World Health Organization Quality of Life-Old Module indicated good internal consistency reliability and construct validity. The tool can be utilized to provide care to Ethiopian community-dwelling old age people.</p>
Flow virometry for water-quality assessment: Protocol optimization for a model virus and automation of data analysis
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Data from: Freshwater ecological quality assessment of the gold mining Mashcon watershed, Cajamarca - Peru
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Data from: Validation of Quality-of-Life assessment tool for Ethiopian old age people
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Analysis of laboratory reporting practices using a quality assessment of a 'virtual patient'. (data)
<p>Dataset for paper Analysis of laboratory reporting practices using a quality assessment of a ‘virtual patient', published in Genetics in Medicine.</p> <p>This dataset consists of the FASTQ, BAM, and VCF for the virtual patients as described in the paper.<br> </p>
Data from: Development of a simple, practice-based tool to assess quality of paediatric emergency care delivery in resource-limited settings: identifying critical actions via a Delphi study
Objective: Provision of timely, high-quality care for the initial management of critically ill children in African hospitals remains a challenge. Monitoring the completion of critical actions during resuscitations can inform efforts to reduce variability and improve outcomes. We sought to develop a practice-based tool based on contextually relevant actions identified via a Delphi process. Our goal was to develop a tool that could identify gaps in care, facilitate identification of training and standardized assessment to support quality improvement efforts. Design: Six sentinel conditions were selected based on disease epidemiology and mortality at rural and urban African emergency departments. Potential critical actions were identified through focused literature review. These actions were evaluated within a three-round modified Delphi process. A set of logistical filters was applied to the candidate list to derive a practice-based tool. Setting and participants: Attendees at an international emergency medicine conference comprised an expert panel of 25 participants, with 84% working primarily in African settings. Consensus rounds allowing novel responses were conducted via online and in-person surveys. Results: The expert panel generated 199 actions that apply to six conditions in emergently ill children. Application of appropriateness criteria refined this to 92 candidate actions across seven categories: core skills, active seizure, altered mental status, diarrheal illness, febrile illness, respiratory distress, polytrauma. From these, we identified 28 actions for inclusion in a practice-based tool contextually relevant to the initial management of critically ill children in Africa. Conclusions: A group consensus process identified critical actions for severely ill children with select sentinel conditions in emergency paediatric care in an African setting. Absence of these actions during resuscitation might reflect modifiable gaps in quality of care. The resulting practice-based tool is context-relevant and can serve as a foundation for training and quality improvement efforts in African hospitals and emergency departments.
Replication Package for Data Quality Assessment in the Wild: Findings from GitHub
<p>This contains the data and code used in the EASE 2014 paper "Data Quality Assessment in the Wild: Findings from GitHub."</p>
An evidence map of research assessing the effects of timber harvesting on water quality, biotic and biodiversity indicators in running waters: Data and R code
<p>These are the data and R code that accompany the Forest Ecology and Management publication titled "An evidence map of research assessing the effects of timber harvesting on water quality, biotic and biodiversity indicators in running waters". </p>
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>
Translanguaging experimental research: list of eligible studies and quality assessment data
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Quality Assessment of YUNYAO GNSS-RO Refractivity Data in the Neutral Atmosphere
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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.