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317 results for “Experts”
Conceptual Assessment Questions with Experts - OntoTurnover
<p><strong>Objective: </strong>To describe the questions and alternatives used in the conceptual evaluation with experts carried out in the OntoTurnover engineering process.</p>
Social vulnerability to flooding in Ecuador : input variables, PCA vs Expert composite indices
<p><strong>Social vulnerability indices are used to better understand and predict the consequences of disasters, and support the development of improved disaster management policies. This research specifically supports the Ecuadorian Red Cross in generating a flood-specific social vulnerability index to inform flash flood early action protocol.</strong></p> <p>The dataset presents the results from the analysis of the social vulnerability to flooding in Ecuador, from individual input variables to the composite indices outputs. The results are available at the Parroquia level in Ecuador (admin level 3), for 1032 Parroquia excluding the Galapagos Islands.</p> <ul> <li>The dataset comprises, for each Parroquia, the estimation of <strong>15 variables characterizing the social vulnerability to flooding specific to Ecuador context</strong>. The variables are selected from literature review and consultation with Ecuadorian Red Cross disaster practitioners : <em>Disability, Poverty incidence, Gini Index, Agricultural labor share, Vectorborne disease incidence, Waterborne disease incidence, Social Security affiliation, Education level, Sanitation, Driking water access, Power access, Road travel time, Wall structure, Mobile access and Internet access.</em> All variables are normalized from 0 to 1, directed toward increasing vulnerability, and renamed accordingly.</li> <li>In addition, the <strong>Administrative level names, PCODE, calculated Area, population density,</strong> as well as related <strong>sub-regions</strong> are also referenced.</li> <li>Individual variables are integrated into <strong>composite vulnerability indices</strong>, using two different approaches: i) the Principal Component Analysis approach, using the first component <strong>PCA(n=1) </strong>and the first 5 components <strong>PCA(n=5)</strong> separately ; ii) the <strong>expert judgement weighting</strong> of the variables. The output composite indices, normalized from 0 to 1 are presented in 3 separated columns.</li> </ul> <p> </p>
Expert opinion survey on habitat-threat parameters for the PEM-Sul ocean zoning project
<p>This is an ongoing dataset.</p> <p> </p>
Results of the evaluation about the expert interviews regarding the benefits of a digital procurement workspace.
<p>The paper "A next-generation Digital Procurement Workspace focusing on Information Integration, Automation, Analytics, and Sustainability" evaluates the set requirements and discovers the benefits of the Digital Procurement Workspace. For that, expert interviews in a qualitative and quantitative manner were conducted. The qualitative evaluation results are summarized here based on Mayring's (Mayring, 2000) methods.</p>
Perception and appreciation of plant biodiversity among experts and laypeople
<p>Main dataset for the paper „Perception and appreciation of plant biodiversity among experts and laypeople”, by Eva Breitschopf and Kari Anne Bråthen</p>
Replication Package: An Expert Survey on the Use of Informal Models in the Automotive Industry
<p>This repository contains the replication package for the paper <em>An Expert Survey on the Use of Informal Models in the Automotive Industry</em> by <a href="https://orcid.org/0000-0001-6410-6769">Dominik Fuchß</a>, <a href="https://orcid.org/0000-0001-7312-2891">Thomas Kühn</a>, <a href="https://orcid.org/0000-0002-8953-1064">Jérôme Pfeiffer</a>, <a href="https://orcid.org/0000-0003-3534-253X">Andreas Wortmann</a>, and <a href="https://orcid.org/0000-0002-1593-3394">Anne Koziolek</a>. The paper has been accepted at the <a href="https://www.iese.fraunhofer.de/en/twinarch.html">TwinArch 2023: The 2nd International Workshop on Digital Twin Architecture</a> co-located with <a href="https://conf.researchr.org/home/ecsa-2023">ECSA 2023</a>.</p>
The Awareness Assessment Model (expert panel evaluation)
<p>The dataset of the expert panel evaluation, described in the paper "The Awareness Assessment Model: Measuring Awareness and Collaboration Support Over Participant's Perspective"</p>
Data and code for: Veterinary Expert System for Outcome (VESOP) Prediction
<p>Timely detection and understanding of causes for population decline are essential for effective wildlife management and conservation. Assessing trends in population size has been the standard approach but we propose that monitoring population health could prove more effective. We collated data from seven bottlenose dolphin (<em>Tursiops</em> <em>truncatus</em>) populations in the southeastern U.S. to develop the Veterinary Expert System for Outcome Prediction (VESOP), which estimates survival probability using a suite of health measures identified by experts as indices for inflammatory, metabolic, pulmonary, and neuroendocrine systems. VESOP was implemented using logistic regression within a Bayesian analysis framework, and parameters were fit using records from five of the sites that had robust stranding network and frequent photographic identification (photo-ID) surveys to document definitive survival outcomes. We also conducted capture-mark-recapture (CMR) analyses of photo-ID data to obtain separate estimates of population survival rates for comparison with VESOP survival estimates. VESOP analyses found multiple measures of health, particularly markers of inflammation, were predictive of 1- and 2-year individual survival. The highest mortality risk one year following health assessment related to low alkaline phosphatase, with an odds ratio of 10.2 (95% CI 3.41–26.8), while 2-year mortality was most influenced by elevated globulin (9.60; 95% CI 3.88–22.4); both are markers of inflammation. The VESOP model predicted population-level survival rates that correlated with estimated survival rates from CMR analyses for the same populations (1-year Pearson's r=0.99; p=1.52e<sup>-05</sup>, 2-year r=0.94; p=0.001). While our proposed approach will not detect acute mortality threats that are largely independent of animal health, such as harmful algal blooms, it is applicable for detecting chronic health conditions that increase mortality risk. Random sampling of the population is important and advancement in remote sampling methods could facilitate more random selection of subjects, obtainment of larger sample sizes, and extension of the approach to other wildlife species.</p>
Images of daphnids (control and exposed to NMs) over multiple generations, scored by experts as toxic or non-toxic and the resulting deepDaph predictions
<p>Background</p> <p>This study showcases a pioneering application of deep learning methodologies in ecotoxicology, aimed at facilitating hazard assessment and safer design of engineered nanomaterials (ENMs). The research hinges on a high-quality dataset comprising microscopic images of Daphnia magna exposed to various ENMs, collected systematically under controlled conditions.</p> <p>The Dataset: A Cornerstone of Nanoinformatics</p> <p>Our dataset, which will be openly accessible on Zenodo, serves as a foundational resource for the ecotoxicology community. It contains high-resolution images tagged with intricate details like malformations, tail lengths, lipid concentrations, and lipid deposit shapes. Researchers can use this exhaustive dataset to train a variety of predictive models for diverse applications.</p> <p>Methodology</p> <p>We employ two different deep learning architectures to process the dataset. These architectures automatically detect malformations and assess the impact of ENMs on D. magna by classifying various biological structures based on lipid densities.</p> <p>Results and Validation</p> <p>The developed models demonstrate high statistical validation, confirming their prediction accuracy on external D. magna images. Our dataset and the associated models not only accelerate manual procedures but also pave the way for automated, high-throughput analyses in ecotoxicology.</p> <p>Future Prospects</p> <p>The dataset holds the potential to extend investigations into predicting the impacts on future generations from parental exposures, thus reducing the time and cost of multi-generational toxicity assays.</p>
Does the tail show when the nose knows? AI-enhanced analysis of tail kinematics outperforms human experts at predicting when detection dogs find their target odor
Open the record for dataset details and reuse information.
Data and code for: Veterinary Expert System for Outcome (VESOP) Prediction
Open the record for dataset details and reuse information.
Expert surveys on high-end climate change
<p>Data from two surveys conducted on the back of the Adaptation Futures conferences held in 2016 and 2018 and analysed for an article in Climatic Change.</p>
Teleoperation with Baxter robot and haptic device: testing with experts user.
<p>In this video you can see the experiment with expert users developed by Robotics Group of the Universidad de León, as part of a research project that aims to demonstrate the effectiveness of the use of haptic devices in teleoperation environments.</p>
Datasets for Effective Distributed Representations for Academic Expert Search
<p>Dataset for the "Effective Distributed Representations for Academic Expert Search" paper published at the <a href="https://ornlcda.github.io/SDProc/ ">SDP 2020 workshop</a> of the EMNLP conference.</p> <p>Two .zip archives are provided:</p> <p>1)<em><strong> papers_and_authors_source_csvs.zip : </strong></em>Contains <em>papers.csv </em>and <em>authors.csv</em>, which are CSV files with the source metadata for all the ~130k papers and ~68k authors used in the final version of the system.</p> <p>2) <em><strong>faiss_indexes.zip : </strong></em>Contains all the pre-populated FAISS indexes with all the embedding variations we used in our research.</p>
Expert AR Detector Counts
<p>Global atmospheric river (AR) counts, contributed by a set of 8 experts in atmospheric science. Each contributor was presented with meteorological information in a graphical user interface and were asked to manually identify AR locations. Contributors counted ARs in at least 30 independent meteorological fields.</p> <p>Information from each contributor is stored in a separate netCDF file. The information includes: AR counts, approximate AR location, the corresponding integrated vapor transport field, and the associated timestamp. Each contributor is assigned a number, following the convention described by O'Brien et al., (2020, GMD).</p> <p>This dataset was used by O'Brien et al. (2020, GMD) to train a Bayesian AR Detector.</p> <p>O'Brien, T. A., Risser, M. D., Loring, B., Elbashandy, A. A., Krishnan, H., Johnson, J., Patricola, C. M., O'Brien, J. P., Mahesh, A., Prabhat, Arriaga Ramirez, S., Rhoades, A. M., Charn, A., Inda Díaz, H., and Collins, W. D.: Detection of Atmospheric Rivers with Inline Uncertainty Quantification: TECA-BARD v1.0, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-55, Accepted, 2020.</p>
Data for: Susceptibility of domain experts to color manipula-tion indicate a need for design principles in data visualization (PLoS one)
<p>This data set accompanies the paper "<strong>Susceptibility of domain experts to color manipulation indicate a need for design principles in data visualization</strong>" by Markus Christen, Peter Brugger<span> </span>and Sara Irina Fabrikant, revision submitted to PLoS One. The paper will be open access, further information will be available there.</p>
Data from: Towards automated annotation of benthic survey images: variability of human experts and operational modes of automation
Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.
Classification of word levels with usage frequency, expert opinions and machine learning
<p>This dataset includes classification of English words according to CEFR language levels. It can be used in various educational applications including determining levels of text that is appropriate for students learning English. </p> <p>For each word, part-of-speech, the word lemma and usage frequency is provided. For words that have no survey results, a machine learning based methodology is used to predict levels. These predictions are also included as a separate file. This data is released as part of the submission process to British Journal of Educational Technology Special Issue on Open Data.</p> <p>The included readme.pdf file contains a detailed description of data. </p>
Transcripts of expert interviews with writing center directors in the USA in 2012
<p>This document contains transcripts of interviews with 16 writing center directors in different writing centers in the USA, conducted in 2012. The overall research question for the interviews was how writing center directors deal with challenges in writing center work and how they conduct institutional work for their writing centers.</p> <p>The interviews belong to the habilitation thesis <em>“Strategien für die Institutionalisierung von Schreibzentren an Hochschulen. Eine qualitative Analyse der Institutionalisierungsarbeit von Leitungspersonen in Schreibzentren“</em>, as proposed to the <em>Fakultätsrat der Kultur-, Sozial- und Bildungswissenschaftlichen Fakultät</em> of the Humboldt University Berlin, April 1st 2016. The study has been accepted as habilitation by the <em>Fakultätsrat</em> at February 15<sup>th</sup> 2017.</p> <p>The results of the study will be published as open access publication (e-book) and in print by W.Bertelsmann Verlag (wbv) Bielefeld in October 2017. The study contains a description of demographic details and other details of the interviews and explains the methodology, which clarifies why the interview transcripts eventually change to part-transcriptions due to theoretical saturation.</p> <p> </p>
Supplementary data on learning about German farmers' willingness to cooperate from public goods games and expert predictions
<p>Supplemental files on learning about German farmers' willingness to cooperate from public goods games and expert predictions. </p>
ScienceDex guides
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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.