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.
726
datasets available to search
ShareScore release 0.9.0
Dataset results
726 results for “model evaluation”
Input data for performing a model evaluation of the sectional aerosol module SALSA embedded to PALM model system 6.0
<p>This dataset includes the input information applied to perform a model evaluation study of the PALM model system together with the sectional aerosol module SALSA. </p> <p>The content:</p> <ul> <li>PIDS_STATIC: building height and leaf area density data</li> <li>PIDS_AERO_<simulation time>_<number of aerosol size bins>: aerosol emission data as size bin specific surface emissions (level of detail 2) and aerosol background concentrations</li> <li>PIDS_CHEM_<simulation time>: emission data and background concentrations of gaseous compounds</li> </ul> <p>PIDS_STATIC contains static data and is therefore the same for all simulations.</p> <p>See the model documentation https://palm.muk.uni-hannover.de/trac/wiki/doc for further details.</p>
Evaluating the role of the nuclear microenvironment in gene function by population-based modeling
<p>This repository accompanies the manuscript "<strong>Evaluating the role of the nuclear microenvironment in gene function by population-based modeling</strong>", available in <em>Nature Structural & Molecular Biology</em>.</p> <p>It contains the files for the population of 3D structures for GM12878 in 200-kb resolution generated using IGM (https://github.com/alberlab/igm) and the derived structural features. Please see README.txt for more information.</p> <p>For any inquiries please reach out to Dr. Frank Alber (falber@g.ucla.edu).</p>
Reuse of Model Transformations for Propagating Variability Annotations in Annotative Software Product Lines - Evaluation Data
<p>This package contains all data that was produced for and used in the doctoral thesis for evaluating commutativity of propagating annotations in model-driven product lines.<br> This includes the implementation that conducts the evaluation, the measured results, and the input subjects.</p>
A Policy and Infrastructure Evaluation Model of Commodity Flows through Inland Waterway Ports (Dataset)
<p>The purpose of this project is to guide strategic investment into port capacity through the development of a policy and infrastructure evaluation model of inland waterway commodity flows. A multi-stage stochastic optimization model will be developed to evaluate tradeoffs in strategic, long-term port infrastructure investment with mid-term capacity expansion decisions and provision of complementary highway infrastructure made by public and private stakeholders, and shorter-term operational practices made by shippers and carriers. This work builds on prior MarTREC projects which developed a Multi-Commodity Assignment Problem to estimate annual commodity flows through inland waterway ports from truck Global Positioning System (GPS), marine Automatic Identification System (AIS), and the Lock Performance Management System (LPMS). The proposed project will explore critical extensions of the assignment model: 1) disaggregation of the temporal scope to reflect monthly seasonality among commodities, 2) incorporation of uncertainty related to observed vehicle and vessel movement data, and 3) inclusion of transportation costs. With these extensions the team expects to increase the accuracy and resolution of the commodity-based port throughput estimates and to allow the model to be used to not only describe the current system but to prescribe policy and project investment strategies for public and private sector transportation decision makers. Calibration and validation of the multi-stage optimization model will be done through two case studies. The regional-based study will use historical truck GPS, marine AIS, and LPMS datasets. The national-based study will use data from the Billion Ton Study led by the US Department of Energy. This will ensure a feasible and realistic base-case on which to compare future policy scenarios. This project aligns with MarTREC’s research focus area in Maritime and Multimodal Logistics Management by modeling commodity flows through ports that serve as critical connections for the multimodal freight supply chain.</p>
Dataset and evaluation for HTR models for Latin and French Medieval Documentary Manuscripts
<p><strong>1. Dataset presentation.</strong></p> <p>This is the dataset used to produce the HTR models applied to documentary Latin and French manuscripts presented in the paper: Sergio Torres Aguilar, Vincent Jolivet. <strong>Handwritten Text Recognition for Documentary Medieval<br> Manuscripts. </strong>2022. https://hal.science/hal-03892163</p> <p>The dataset contains mostly charters and registers from the Late-medieval period (12th-15th). The training and evaluation, entailing 1855 pages, 120k lines of text and almost 1M tokens, were conducted using three freely available ground-truth corpora :</p> <p><strong>The Alcar-HOME database </strong>: https://zenodo.org/record/5600884</p> <p><strong>The e-NDP corpus </strong>: https://github.com/chartes/e-NDP_HTR</p> <p><strong>The Himanis project </strong>: https://zenodo.org/record/5535306</p> <p>The final model operates in a multilingual environment (Latin and French) and it is able to recognize several Latin script families (mostly <em>Textualis</em> and <em>Cursiva</em>) in documents produced in ca. 12th - 15th centuries. During the evaluation the models shows an accuracy of <strong>94.01%</strong> on the validation set and a CER (character error ratio) of about <strong>0.12</strong> to <strong>0.17</strong> on four external unseen datasets. A fine-tuning exercise using 10 ground-truth pages can raise these results to a CER between <strong>0.06</strong> to <strong>0.10</strong> respectively.</p> <p> </p> <p><strong>2. Dataset contents .</strong></p> <p>a) <em>GT_list : </em>List containing the GT file names which constitute the training, evaluation and test sets. The images and transcriptions can be downloaded from their original repositories.</p> <p>b) <em>Training :</em> Contains the training and testing results (evaluation and prediction files) presented in the original paper for the two training phases: Regular (Textualis and Cursiva separated training) and Quartiles (mixed training by quartiles).</p> <p>c) <em>Useful_scripts :</em> Scripts to produce the HTR metrics (CER, WER, SER) and plot the model's accuracy.</p> <p>d) <em>Best_model :</em> Contains the best multilingual and multi-script model.</p>
(Dataset) Evaluating tomotectonic plate reconstructions using geodynamic models with data assimilation, the case for North America
<p>Dataset for the paper:</p> <p>Evaluating tomotectonic plate reconstructions using geodynamic models with data assimilation, the case for North America</p> <p>For more infomation, please look into the README file or contact ljliu@illinois.edu, thank you!</p>
scMARK an 'MNIST' like benchmark to evaluate and optimize models for unifying scRNA data
<p>Here we present a novel benchmark dataset (scMARK.v2), that consists of 11 published cancer scRNA-seq studies, for which we standardized cell-type author labels and gene identifiers. scMARK.v2 can be used to ask how well models integrate data from different scRNA studies. We also provide a 12th standardized study (Wu et al 2021) that we held-out for evaluation of alignment of data "never seen" before, and a 13th study of newly generated in-vitro scRNA-seq data from cancer and fibroblast cells.</p> <ul> <li>Data is provided as aData *h5ad files that can be read with Python's library <a href="https://scanpy.readthedocs.io/en/stable/">Scanpy</a>.</li> <li>Studies inclided in scMARK.v2 were downsampled to 10,000 cells per study.</li> <li>The difference between <a href="https://zenodo.org/record/5765804">scMARK.v1</a> and scMARK.v2, is that in v2, we provide at least two studies for each cancer type and each cell type; whereas in v1 a handfull of cell types were present only in one study.</li> </ul>
NUMAC: Description of the Nested Unified Model with Aerosols and Chemistry, and evaluation with KORUS-AQ data: supporting data
<p>Simulated data presented in manuscript with title above, generated with the Met Office Unified Model, together with observations from KORUS-AQ and MODIS that are used in the model evaluation.</p> <p>The Terra/MODIS aerosol datasets were acquired from the Level-1 and Atmosphere Archive & Distribution<br> System (LAADS) Distributed Active Archive Center (DAAC), located in the Goddard Space Flight Center in Greenbelt, Maryland https://ladsweb.nascom.nasa.gov/. All surface and aircraft observation data is freely and publicly available at https://www-air.larc.nasa.gov/cgi-bin/ArcView/korusaq, last access 10 June 2022.</p>
Proactive Conflict Detection for Collaborative Model-driven Software Engineering (Evaluation Data)
<p>Results of the evaluation for the paper "Proactive Conflict Detection for Collaborative Model-driven Software Engineering"</p>
A Conceptual Model to Support Teaching of Software Engineering Controlled (Quasi-)Experiments - Evaluation of the Concept Model
<p>A Conceptual Model to Support Teaching of Software Engineering Controlled (Quasi-)Experiments - Evaluation of the Concept Model</p>
Evaluating a poroelastic model via pore pressure signals in seafloor sediments [data set]
<p>The csv files consist of pressure data collected off the coast of Camp Pendleton between 10 February 2021 and 25 February 2021, and include both pore pressure data from two instrumented surrogates and pressure data from a Nortek Signature. Timestamps are in posix time; pressure is in kPa. The time series for Surrogate A are prefixed "surrA"; those for Surrogate B are prefixed "surrB". The Nortek Signature time series is prefixed "Sig1000".</p>
AGREE: a New Benchmark for the Evaluation of Semantic Models of Ancient Greek
<p>AGREE (Ancient Greek Relatedness Embeddings Evaluation) is a benchmark for the evaluation of semantic models of Ancient Greek created at the University of Groningen (The Netherlands). More information about it can be found in the following publication:</p> <p>Silvia Stopponi, Saskia Peels-Matthey, Malvina Nissim, AGREE: a new benchmark for the evaluation of distributional semantic models of ancient Greek, <em>Digital Scholarship in the Humanities</em>, Volume 39, Issue 1, April 2024, Pages 373–392, <a href="https://doi.org/10.1093/llc/fqad087">https://doi.org/10.1093/llc/fqad087</a></p> <p> </p> <p><strong>1. Overview of the repository</strong></p> <p>This benchmark was created from a mix of expert judgements about relatedness between Ancient Greek words and model outputs validated by human experts. The evaluation items are pairs of Ancient Greek lemmas with a high semantic relatedness.</p> <p>The human judgements were collected via two questionnaires, proposing two different tasks to the experts. The evaluation items included in the AGREE benchmark are a selection of the most strictly related pairs of lemmas obtained from the two tasks. Here an overview of the contents of the repository:</p> <ul> <li><strong>1_agree_task1.json</strong> includes all the data collected with the first task. The following labels are used: <ul> <li>'pair': two Ancient Greek lemmas;</li> <li>'frequency': the number of times that the pair was suggested as related by an expert;</li> <li>'POS1': part-of-speech of the first lemma;</li> <li>'POS2': part-of-speech of the second lemma;</li> <li>'benchmark': inclusion of the pair in the AGREE benchmark ('yes'/'no').</li> </ul> </li> <li><strong>2_agree_task2.json </strong>includes all the data collected with the second task. The following labels are used: <ul> <li>'pair': two Ancient Greek lemmas;</li> <li>'origin': <ul> <li>'common_pair' = one of the two pairs proposed to all participants in the second task;</li> <li>'task1' = pairs proposed by experts in the first task;</li> <li>'models_easy_rel' = output of word2vec models, pair considered as strictly related;</li> <li>'models_task1' = pairs proposed by experts in the first task and also output by word2vec models;</li> <li>'models' = output of word2vec language models;</li> <li>'unrelated' = made up pairs of unrelated lemmas (control pairs);</li> </ul> </li> <li>'respondents': number of experts evaluating a pair;</li> <li>'score': average relatedness score given by the experts on a 0-100 scale;</li> <li>'agreement': inter-annotated agreement between all experts who evaluated the block of pairs to which the current pair belongs (when available, i.e. when the block of pairs was presented to more than one participant);</li> <li>'benchmark': inclusion of the pair in the AGREE benchmark ('yes'/'no').</li> </ul> </li> <li><strong>3_agree_final_benchmark.json </strong>includes the final selection of items that constitutes AGREE. The following labels are used: <ul> <li>'pair': two Ancient Greek lemmas;</li> <li>'origin': <ul> <li>'task1': pair either proposed more than once in the first task or proposed only once, but scored >= 70 in the second task;</li> <li>'task2': pair scored by more than one respondent in the second task and with average score >= 70.</li> </ul> </li> </ul> </li> </ul> <p> </p> <p>This updated version of the repository includes the individual answers to the two questionnaires (see files 'answers_Task1_postprocessed.xlsx' and 'raw_answers_Task2.xlsx').</p> <p> </p> <p><strong>2. Acknowledgements</strong></p> <div>This work was partially supported by the Young Academy Groningen through the PhD scholarship of Silvia Stopponi.<br> <br>We acknowledge the financial support of Anchoring Innovation. Anchoring Innovation is the Gravitation Grant research agenda of the Dutch National Research School in Classical Studies, OIKOS. It is financially supported by the Dutch ministry of Education, Culture and Science (NWO project number 024.003.012). For more information about the research programme and its results, see the website <a href="https://www.anchoringinnovation.nl">www.anchoringinnovation.nl</a>.<br> <br>We want to thank the experts of Ancient Greek around the world who shared their knowledge of Ancient Greek semantics and donated some of their precious time. Without them the creation of this benchmark would not have been possible.<br> <br>We also want to thank the many colleagues from the University of Groningen, the National Research School OIKOS, and other Universities abroad who contributed to this work with discussion and advice.</div> <div> </div> <div> <br><strong>3. Citation</strong><br>Silvia Stopponi, Saskia Peels-Matthey, Malvina Nissim, AGREE: a new benchmark for the evaluation of distributional semantic models of ancient Greek, <em>Digital Scholarship in the Humanities</em>, Volume 39, Issue 1, April 2024, Pages 373–392, <a href="https://doi.org/10.1093/llc/fqad087">https://doi.org/10.1093/llc/fqad087</a></div> <div> </div> <div> </div> <div> </div> <div> </div> <div> </div> <div> </div>
Data from: Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models
<ol> <li>Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics.</li> <li>We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth.</li> <li>We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction.</li> <li>Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%.</li> <li>Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.</li> </ol>
Data, scripts, and figures of the article: Evaluation of oregano essential oil in broilers challenged with a mixed Eimeria spp. and high dietary protein model of subclinical coccidiosis
<p>Data, scripts, and figures of the article "Evaluation of oregano essential oil in broilers challenged with a mixed Eimeria spp. and high dietary protein model of subclinical coccidiosis" to be published in the journal Animal - Open Space. </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 set: Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022
<p><strong>Version 2:</strong></p> <p><strong>Updates from version 1: Monthly, daily, and hourly dist-PDD and uni-PDD outputs have been added.</strong></p> <p><strong>https://doi.org/10.5194/tc-17-3667-2023</strong></p> <p> </p> <p>Version 1:</p> <p>This dataset accompanies Zheng et al. (2023): Statistically parameterizing and evaluating a positive degree-day<br> model to estimate surface melt in Antarctica from 1979 to 2022, The Cryosphere.</p> <p>This dataset contains annual PDD model output.</p>
A dynamic von Mises-based model to evaluate the impact of urbanization and climate change on flood timing in Yangtze and Huaihe River Basins, China
<p>The daily streamflow data extracted from 8 selected stations from the Huaihe and Yangtze River Basins, China.</p>
Graphic representation of data set for the project "IRI model performance evaluation for the Mexican region"
<p>Here, we illustrate the modeling and experimental results for vertical Total Electron Content (TEC) over Mexico during the five year period 2018-2022. The results were obtained for the UCOE GNSS receiver station (geographic coordinates: 19.6°N; 101.68°W ). The calculations were made each two hours during the whole period under considerations. The modeling results were obtained using the "International Reference Ionosphere (IRI)" model, which is an empirical climatological model based on ground and space observations of the ionosphere [Bilitza et al., 2022].</p>
Isotope mixing scenarios for: To what extent are the source mixing models accurate: evaluation of the model accuracy and guidelines for the site-specific model selection
<p><span>We selected 10 types of distinct isotope signatures that can be found in the samples of natural water. Every 3–10 types of hypothetical isotope signatures were conceptually grouped together. There would be 968 possible combinations based on combinatorics theory. However, we needed distinct mixing polygons to facilitate our determination of model capacity in dealing with uncertainties. Therefore, we </span><span>kept </span><span>only 240 such groups in </span><span>the </span><span>final</span><span> analysis</span><span>. Each group was designated with a </span><span>predefined</span><span> mixing ratio. After that, we ran all the examined models through these mixing scenarios to </span><span>obtain</span><span> the model estimation of the mixing ratios.</span></p>
Evaluation of an Enhanced Delivery Model for Go NAPSACC
ClinicalTrials.gov study NCT03938103. IPD Sharing: YES. Countries: 1. Publications: 5.
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.