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533 results for “quality evaluation”
EOSC Task Force on FAIR Metrics and Data Quality: FAIR Evaluation community survey 2023
<p>The EOSC-A FAIR Metrics and Data Quality Task Force (TF) supported the European Open Science Cloud Association (EOSC-A) by providing strategic directions on FAIRness (Findable, Accessible, Interoperable, and Reusable) and data quality. The Task Force conducted a survey using the <a href="https://ec.europa.eu/eusurvey/">EUsurvey tool</a> between 15.11.2022 and 18.01.2023, targeting both developers and users of FAIR assessment tools. The survey aimed at supporting the harmonisation of FAIR assessments, in terms of what it evaluated and how, across existing (and future) tools and services, as well as explore if and how a community-driven governance on these FAIR assessments would look like. The survey received 78 responses, mainly from academia, representing various domains and organisational roles. This is the anonymised survey dataset in csv format; most open-ended answers have been dropped. The codebook contains variable names, labels, and frequencies.</p>
Modified WRF/Chem source code, output data, and post-processing scripts for the GMD manuscript "Evaluation of WRF/Chem model (v3.9.1.1) real-time air quality forecasts over the Eastern Mediterranean"
<p>Here you will find the modified WRF/Chem code used in the simulations, the scripts used for post-processing and the model output data used in the manuscript. </p> <p>Two modifications have been made in module_aerosols_soa_vbs.F:</p> <ol> <li>ch_dust is set to1.0D-9*0.36</li> <li>The model is set not to initialize during restarts</li> </ol> <p>The model data directory includes:</p> <ol> <li>Two csv files (Winter and Summer) with the hourly concentrations of atmospheric pollutants at the locations of the ground stations. These data were used to produce Figures 4-8 in the manuscript as well as all the metrics.</li> <li>Two netcdf files (Winter and Summer) with the average ground concentrations of atmospheric pollutants over Cyprus. These data were use to produce Figure 3 in the manuscript. </li> </ol>
Quality evaluation criteria, best practices, and assessment systems for Institutional Publishing Service Providers (IPSPs): dataset
<p>The dataset contains tabular information on the elements of best practice in scholarly publishing found in a set of documents (high-level recommendations and principles, indexation criteria and specific assessment guidelines used on the national and institutional levels). The set of documents subject to analysis (58 items) were identified by the DIAMAS project team members (bibliographic metadata are provided in IPSP-best-practice-documents.xml and IPSP-best-practice-documents.ris).</p> <p>The dataset was compiled by the DIAMAS project team using an analysis matrix that included the general information about the documents (title, issuing entity, scope and purpose, etc.) and the the seven core components of scholarly publishing identified in the Diamond Open Access Action Plan (2022) and revised by the DIAMAS project team.</p> <p>More information about the data collection methodology can be found in the report D3.1 IPSP Best Practices Quality evaluation criteria, best practices, and assessment systems for Institutional Publishing Service Providers (IPSPs) (<a href="https://doi.org/10.5281/zenodo.7859172">https://doi.org/10.5281/zenodo.7859172</a>), which is based on this dataset.</p> <p> </p> <p><strong>****Dataset contents****</strong></p> <p>IPSPs_best-practices-overview.csv</p> <p>IPSPs_best-practices-overview.ods</p> <p>IPSP-best-practice-documents.xml</p> <p>IPSP-best-practice-documents.ris</p> <p>README.txt</p> <p> </p> <p><strong>****Column headers and field types***</strong></p> <p>Title (original) (text)</p> <p>Title (English) (text)</p> <p>Publication date (date, DD/MM/YY)</p> <p>Last accessed (date, DD/MM/YY)</p> <p>URL (text-web address)</p> <p>Scope (text, controlled)</p> <p>Type of document (text, controlled)</p> <p>Original language (text)</p> <p>Other languages (text)</p> <p>Entity issuing the document (text)</p> <p>Entity responsible for the assessment (text)</p> <p>Scope of the assessment (text, controlled)</p> <p>Scope of assessment: region or country (text)</p> <p>Disciplines’ coverage (text)</p> <p>Periodicity of the assessment (text)</p> <p>Reassessment frequency? If yes: periodicity (text)</p> <p>Benefits linked to the assessment (text)</p> <p>(1) Funding (text)</p> <p>(2) Ownership and governance (text)</p> <p>(3) Open science practices (text)</p> <p>(4) Editorial quality, editorial management and research integrity (text)</p> <p>(5) Technical service efficiency (text)</p> <p>(6) Visibility (including indexation), communication, marketing and impact (text)</p> <p>(7) Diversity, Equity and Inclusion (text)</p>
Monitoring feedback to authors on the quality of trials evaluating interventions aimed at preventing and treating COVID-19
<p>We aimed to assess transparency of reporting and risk of bias of randomized trials evaluating interventions aimed at preventing and treating COVID-19.</p> <p>This review is part of a larger project: the COVID-NMA project (Boutron 2020a). The COVID-NMA project aims to provide decision-makers with a complete, high-quality and up-to-date synthesis of evidence on interventions for the prevention and treatment of COVID 19. For this purpose, we perform a living mapping of all registered randomized controlled trials and a living evidence synthesis of data from RCTs. We developed a master protocol on the effect of all interventions for the prevention and treatment of COVID-19 (first published on April 8, 2020; an update on May 11, 2020, June 17, 2020, and September 8, 2020) (Boutron 2020b). We set-up a platform (<a href="https://covid-nma.com/">https://covid-nma.com</a>) where all our results are made available and updated weekly.</p>
CVD2014 - A database for evaluating no-reference video quality assessment algorithms
<p>The CVD video database is developed to provide an useful tool for researchers in the validation and developing processes of no-reference (NR) objective video quality assessment (VQA) algorithms. It consists of 234 videos from five different scenes captured by 78 different cameras (mobile phones, compact camera, video camera, SLR). The subjective experiments are conducted following the Single-Stimulus (SS) procedure to collect ratings of video quality.</p> <p><strong>Setup</strong></p> <p>We implement our experiments according to the Single Stimulus methodology using VQone MATLAB toolboxon high quality monitors (Eizo ColorEdge CG241W) with 1920x1200 pixel resolution in a dark room (ambient light < 20 lux). Video stimuli were displayed at their original size of VGA (640 x 480) or HD (1280 x 720). The subjects viewing distance (80 cm) was controlled by a string hanging from a ceiling and they were instructed to keep their head steady next to it. The monitors were calibrated to according to sRGB (target values were: 6500 K, 80 lux, and gamma 2.2) using EyeOne Pro calibrator (X-rite co.). The laboratory setup is showed in the figure below.</p> <p><strong>Subjects</strong></p> <p>Subjects (n = 30, 30, 28, 33, 30, 32 and 27 for Tests 1 - 7 respectively) were naïve in a sense that they did not study or work with image quality or related fields. They were recruited through student mailing lists consisting mainly humanities and behavioral science students. Subjects’ vision was controlled for the near visual acuity, near contrast vision (near F.A.C.T.) and color vision (Farnsworth D15) before the participation. They received movie tickets as a reward.</p> <p><strong>Procedure</strong></p> <p>Subjects evaluated one video sample at a time and all video samples of one scene were presented in a row. The order of video samples and scenes was randomized. Subjects had the option to view video samples again as many times as they wanted.</p> <p><strong>Data</strong></p> <p>The results are processed and reported in the form of Mean Opinion Score (MOS) for the tested video samples. In addition, we provide the whole raw data from the subjective experiments instead of just pre-calculated mean opinion scores from each video sample. This allows further analyses to be made by those who wish to use this database and gives them better opportunity to utilize the data to its full potential.</p> <p>Realignment study (test 7) contains the data from the additional study in which the mappings from the test and scene specific quality scales (test 1-6) to the global quality scale were formed. The global scale is valuable when studying and developing VQA algorithms. With the global scale, all of the samples (234 video samples in the case of the CVD2014) are in the same scale, and the performance analysis for algorithms can be conducted with a high number of samples.</p> <p><strong>If you use this database in your research, we kindly ask that you follow The Copyright notice below and cite the following paper:</strong></p> <p> </p> <p>M. Nuutinen, T. Virtanen, M. Vaahteranoksa, T. Vuori, P. Oittinen and J. Häkkinen, "CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms," in <em>IEEE Transactions on Image Processing</em>, vol. 25, no. 7, pp. 3073-3086, July 2016. doi: 10.1109/TIP.2016.2562513</p> <p> </p> <p> </p> <p>-----------COPYRIGHT NOTICE STARTS WITH THIS LINE------------</p> <p>Copyright (c) 2014 The University of Helsinki<br> All rights reserved.</p> <p>Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute this database (the videos, the images, the results and the source files) and its documentation for any purpose, provided that the copyright notice in its entirely appear in all copies of this database, and the original source of this database,Visual Cognition research group (www.helsinki.fi/psychology/groups/visualcognition/index.htm) and the Institute of Behavioral Science (www.helsinki.fi/ibs/index.html) at the University of Helsinki (www.helsinki.fi/university/), is acknowledged in any publication that reports research using this database. Individual videos and images may not be used outside the scope of this database (e.g. in marketing purposes) without prior permission.</p> <p>The database and our paper are to be cited in the bibliography as: M. Nuutinen, T. Virtanen, M. Vaahteranoksa, T. Vuori, P. Oittinen and J. Häkkinen, "CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms," in <em>IEEE Transactions on Image Processing</em>, vol. 25, no. 7, pp. 3073-3086, July 2016.<br> doi: 10.1109/TIP.2016.2562513</p> <p>-----------------------------------------------------------------------------</p> <p>LIMITATION OF LIABILITY</p> <p>UNIVERSITY OF HELSINKI SHALL IN NO CASE BE LIABLE IN CONTRACT, TORT OR OTHERWISE FOR ANY LOSS OF REVENUE, PROFIT, BUSINESS OR GOODWILL OR ANY DIRECT, INDIRECT, SPECIAL, CONSEQUENTIAL, INCIDENTAL OR PUNITIVE COST, DAMAGES OR EXPENSE OF ANY KIND HOWEVER CAUSED OR HOWEVER ARISING UNDER OR IN CONNECTION WITH THE USE OF THIS DATABASE.</p> <p>THE UNIVERSITY OF HELSINKI SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE DATABASE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE UNIVERSITY OF HELSINKI HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS.</p> <p>THIS AGREEMENT SHALL BE CONSTRUED AND INTERPRETED IN ACCORDANCE WITH THE LAWS OF FINLAND, EXCLUDING ITS RULES FOR CHOICE OF LAW.</p> <p>-----------COPYRIGHT NOTICE ENDS WITH THIS LINE------------</p>
Dataset created in the context of the project "Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field"
<p>The project "Stable methodologies to evaluate and measure quality, interoperability, blockchain and reuse of open data in the agricultural field", whose website is https://datause.es/, is a project funded by the Ministry of Science and Innovation - State Research Agency, with reference PID2019-105708RB-C22.</p> <p>Within the framework of the project, a bibliographic search is carried out in all thematic categories of the Web of Science (WoS) related to agriculture and related areas. The search equation included the following categories:</p> <p><strong>WC </strong>= (FOOD SCIENCE TECHNOLOGY OR PLANT SCIENCES OR FORESTRY OR AGRICULTURAL ENGINEERING OR AGRONOMY OR HORTICULTURE OR AGRICULTURE DAIRY ANIMAL SCIENCE OR AGRICULTURE MULTIDISCIPLINARY OR AGRICULTURAL ECONOMICS POLICY) </p> <p>This data set shows the distribution of journals and the quartile they occupy in each of the thematic categories in 2019, with the aim of serving researchers in this area and for future data mining.</p>
Data from: Evaluating staging habitat quality to advance the conservation of a declining migratory shorebird, Red Knot Calidris canutus
<p>Identifying where and when population "bottlenecks" occur is critical to the conservation of migratory species, many of which are declining precipitously worldwide. Especially challenging is the evaluation of changes to staging sites. These sites are indispensable links in the migratory cycle but are typically used only briefly.</p> <p>We devised a field-based approach to assess the quality and carrying capacity of a critical staging site in Nanpu, China, for the declining, migratory Red Knot (Calidris canutus rogersi & C. c. piersmai) during northward migration. The Nanpu tidal flat supports 50,000-100,000 Red Knots annually, and while there, the knots feed almost exclusively on the bivalve Potamocorbula laevis. We simultaneously monitored changes in the abundance of Red Knots and bivalves across the entire staging site in spring 2018.</p> <p>After taking into account potential competition with other shorebird species, we estimated that the Nanpu tidal flat was capable of supporting approximately 1.46-1.70 times the current observed level of usage of the site by Red Knots, and therefore is operating below, but close, to carrying capacity with respect to food resources for Red Knots. This result suggests that any further development of this site could harm the EAAF Red Knot population.</p> <p>Synthesis and applications: Quantitative monitoring and evaluation of habitat quality of staging sites are essential to successfully conserve declining migratory species. In particular, researchers and conservation practitioners should incorporate both population size and staging duration in order to more accurately assess the importance of different sites and to quantify how changes in staging habitat quality may translate into changes in migrant population sizes at both local and global scales.</p>
Software product quality evaluation questionnaire for IoT LCDP&MDE
<p>This dataset contains the questionnaire used to assess the quality of LCDP and MDE tools in line with the ISO/IEC 25010:2011 product quality standard.</p>
Replication Package for "Evaluating the layout quality of UML class diagrams using machine learning"
<p>Open Science material including dataset and replication instructions accompanying the article "Evaluating the layout quality of UML class diagrams using machine learning."</p>
Evaluating the summer landscapes of predation risk and forage quality for elk (Cervus canadensis)
<p>These data accompany the paper "Evaluating the summer landscapes of predation risk and forage quality for elk (<em>Cervus canadensis</em>)", and are the unscaled version of the second- and third-order resource selection data sets for elk. Each data set consists of 6 columns: elkid (a unique identifier for every individual), used (an indicator: 0 = available sample, 1 = used sample), year, de (modeled digestible energy), lion (predicted relative probability of selection for mountain lions) and wolf (predicted relative probability of selection for wolves).</p>
Raw Datasets of: "Evaluating the Cost-Effectiveness of Plastic Surgery Based on the Satisfaction with Quality of Life and Nasolabial Appearance in Thai Preteens with Cleft Lip and Palate"
<p>A cross-sectional study with 30 Thai preteen CLP patients aged between 8 to 12-year-old was undertaken between 2017 and 2019 at Tawanchai center. Their satisfaction with QoL was reflected through an interview and a questionnaire with the cooperation of their parents as their caregivers while satisfaction with their nasolabial appearance was from the evaluation of five experts who compared their photos with those of normal faces to determine correlation values of the nasolabial appearance from 5-rating scales using Fleiss’s kappa coefficient scores.</p>
Multi-domain evaluation of a latest generation combustion engine: focusing on sound quality perception
<p>Dataset for conference paper "Multi-domain evaluation of a latest generation combustion engine: focusing on sound quality perception"</p>
Evaluation datasets and results of the paper "A Framework for Measuring the Quality of Business Process Simulation Models"
<p>Datasets and files used in the evaluation of the publication entitled "A Framework for Measuring the Quality of Business Process Simulation Models", where:</p> <ul> <li><strong><em>BPS-models/</em></strong>: folder containing the BPS models used in the evaluation (the BPS models discovered by ServiceMiner are not included due to privacy reasons). <ul> <li>The BPS models discovered by SIMOD are composed of <em>i)</em> a BPMN file with the process model structure, and <em>ii)</em> a JSON file with the parameters of the simulation. These files correspond to the format of Prosimos simulation engine (<a href="https://prosimos.cloud.ut.ee/">https://prosimos.cloud.ut.ee/</a>).</li> <li>The BPS models of the Loan Application and Procure to Pay processes are composed of a BPMN file with both the process model structure and parameters, corresponding to the format of the BIMP simulator used in APROMORE (<a href="https://apromore.com/">https://apromore.com/</a>).</li> </ul> </li> <li><em><strong>measures/</strong></em>: folder containing the distance values of each measure reported in the paper.</li> <li><em><strong>original-event-logs/</strong></em>: folder containing the (train and test) event logs used in the evaluation.</li> <li><em><strong>simulated-logs/</strong></em>: folder containing the simulated logs evaluated in the paper (synthetic, SIMOD, and ServiceMiner).</li> <li><em><strong>ComputeLogDistance.py</strong></em>: script to compute the distance measures proposed in the paper.</li> </ul> <p> </p> <p>To evaluate the distance measures of a set of simulated event logs in the folder <em>simulated_logs/</em> against the test log <em>test_event_log.csv.gz</em>, run:<br><em> python ComputeLogDistance.py -cfld test_event_log.csv.gz simulated_logs/</em></p> <p>*The flag <em>-cfld</em> is optional, due to the high computational complexity of the CFLD measure.</p> <p><strong>WARNING</strong>: set the column names of each log accordingly (where <em>log_1_ids</em> are the IDs of the test log, and <em>log_2_ids</em> the IDs of the simulated logs). Examples:</p> <pre><code># Column IDs for the (train/test) real-life logs, and the SIMOD simulated logs. EventLogIDs( case='case_id', activity='activity', start_time='start_time', end_time='end_time', resource='resource' ) # Column IDs for the Loan Application and Procure to Pay simulated logs. EventLogIDs( case='case_id', activity='activity', start_time='Start_Time', end_time='End_Time', resource='resource' ) # Column IDs for the ServiceMiner simulated logs. EventLogIDs( case='case_id', activity='Activity', start_time='start_time', end_time='end_time', resource='Resource' )</code></pre> <p> </p>
Figure 2 in Evaluation of some nutritional quality criteria of seventeen Moroccan dates varieties and clones, fruits of date palm (Phoenix dactylifera L.)
Figure 2. Representation of dates varieties and clones according to their quality characteristics. (a) Representation of variables according to PCA. (b) Segregation of 17 dates varieties and clones according to their quality attributes.
Fig. 3 in Performance improvement through quality evaluations of sterile cactus moths, Cactoblastis cactorum (Lepidoptera: Pyralidae), mass-reared at two insectaries
Fig. 3. The mean percentage increase in mating of Cactoblastis cactorum females in mating cage bioassays as influenced by the insectary (DPI or TIF) and the trial conducted before (trial 1) and afer (trial 2) quality improvements were made to the rearing and handling protocols at the DPI insectary. Vertical bars denote 0.95 confidence intervals.
Fig. 6 in Performance improvement through quality evaluations of sterile cactus moths, Cactoblastis cactorum (Lepidoptera: Pyralidae), mass-reared at two insectaries
Fig. 6. The mean distance (m) from the field release site that Cactoblastis cactorum males were recaptured was significantly influenced by the insectary (DPI or TIF), the day that released males were recaptured, and the trial conducted before (trial 1) and afer (trial 2) quality improvements were made to the rearing and handling protocols at the DPI insectary. Vertical bars denote 0.95 confidence intervals.
Fig. 2 in Performance improvement through quality evaluations of sterile cactus moths, Cactoblastis cactorum (Lepidoptera: Pyralidae), mass-reared at two insectaries
Fig. 2. The mean percentage of Cactoblastis cactorum females that were mated at time of collection from the insectaries (DPI or TIF) and the trial conducted before (trial 1) and afer (trial 2) quality improvements were made to the rearing and handling protocols at the DPI insectary. Vertical bars denote 0.95 confidence intervals.
Fig. 5 in Performance improvement through quality evaluations of sterile cactus moths, Cactoblastis cactorum (Lepidoptera: Pyralidae), mass-reared at two insectaries
Fig. 5. The relationship between the mean percentage recapture of Cactoblastis cactorum males released in the field as influenced by the day that released males were recaptured. Males recaptured include individuals from both DPI and TIF insectaries. Vertical bars denote 0.95 confidence intervals.
Fig. 4 in Performance improvement through quality evaluations of sterile cactus moths, Cactoblastis cactorum (Lepidoptera: Pyralidae), mass-reared at two insectaries
Fig. 4. The mean percentage recapture of Cactoblastis cactorum males released in the field as influenced by the insectary (DPI or TIF) and the trial conducted before (trial 1) and afer (trial 2) quality improvements were made to the rearing and handling protocols at the DPI insectary. Vertical bars denote 0.95 confidence intervals.
Quality Attributes Assessment in Self-Adaptive Systems: An Empirical Evaluation
<p>Self-adaptive Systems (SAS) can monitor themselves and their context. They can detect changes and react to unexpected conditions with minimal human supervision during their execution. One of the challenges behind developing SAS is dealing with the decision-making process while analyzing the tradeoff points among the multiple quality attributes (QA). In Software Engineering, a widely accepted method of evaluating QA goals in software projects is the Architecture Tradeoff Analysis Method (ATAM). However, despite its importance and wide acceptance, there are few reports of empirical studies on analyzing QA tradeoffs in SAS. In this sense, the present investigation proposes an adapted version of ATAM called ATAM-4SAS to deal with the particularities of SAS. To achieve the research goal, we employed the UPPAAL SMC (statistical verification model) to analyze a set of QA. To evaluate the feasibility of the proposed method, we performed an empirical study on the execution of the ATAM-4SAS in a SAS developed according to the MAPE-K model. This model encompasses the Monitoring, Analysis, Planning, and Execution phases. Such steps share a knowledge base (K), which is fundamental in supporting decision-making. We complemented the empirical evaluation by conducting a focus group, which sought to assess the perceived ease of use and the perceived usefulness of the ATAM-4SAS to support the strategic choice of QA in a SAS. As a result, we observed that most participants agreed that ATAM-4SAS provides adequate support for the strategic choice of QA in SAS.</p>
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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.