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117 results for “research article”
Data for "Researchers and their data. A study based on the use of the word data in scholarly articles"
<p><em>Data</em> is one of the most used terms in scientific vocabulary. This article focusses on the relationship between data and research by analyzing the contexts of occurrence of the word <em>data</em> in a corpus of 72,471 research articles (1980-2012) from two distinct fields (Social sciences, Physical sciences). The aim is to shed light on the issues raised by research on data, namely the difficulty of defining what is considered as data, the transformations that data undergo during the research process and how they gain value for researchers who hold them. Relying on the distribution of occurrences throughout the texts and over time, it demonstrates that the word <em>data </em>mostly occurs at the beginning and at the end of research articles. Adjectives and verbs accompanying the noun <em>data</em> turn out to be even more important than <em>data</em> itself in specifying data. The increase in the use of possessive pronouns at the end of the articles reveals that authors tend to claim ownership of their data at the very end of the research process. Our research demonstrates that even if data handling operations are increasingly frequent, they are still described with imprecise verbs that do not reflect the complexity of these transformations.</p>
Data for research article "Privacy Explanations – A Means to End-User Trust"
<p>Research data for article "<strong>Privacy Explanations – A Means to End-User Trust</strong>". This package includes the survey and its results.</p>
Research Management Systems: Systematic Mapping of Literature (2007-2017) - Number of articles included during the search and qualitative evaluation process of the study
<p>This image is uploaded as an integrated part of systematic mapping of literature "Research Management Systems: Systematic Mapping of Literature (2007-2017)". This image will be cited across all future publications related to this project as Attribution-NonCommercial-NoDerivatives 4.0 International image.</p>
Research Management Systems: Systematic Mapping of Literature (2007-2017) - Topics covered in the analyzed articles
<p>This image is uploaded as an integrated part of systematic mapping of literature "Research Management Systems: Systematic Mapping of Literature (2007-2017)". This image will be cited across all future publications related to this project as Attribution-NonCommercial-NoDerivatives 4.0 International image.</p>
Research data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach"
<div><strong>Research Data related to the article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em></strong></div> <div> </div> <div>Dear reader,</div> <div> </div> <div>reasearch data are provided for the research article "Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach" by Seibert et al. (2024) published in <em>Advances in Water Resources</em> (https://doi.org/10.1016/j.advwatres.2024.104763). The authors hope that the research data allows for a better understanding of the modeling workflow. The research data covers the following files:</div> <div> <ul> <li>Python scripts to create the models <ul> <li>Model scripts using FloPy (Bakker et al., 2016) are stored as .py files in './model_data/flopy_scripts/', named 'model_variant_vXYZ.py', where 'XYZ' is a wildcard for the model number. </li> <li>--> Note that model numbers correspond to the different model variants as referred to in the article, see overview below.</li> <li>The model scripts require postfix files, stored in './model_data/flopy_scripts/postfix/', a PHREEQC database file, stored in './model_data/flopy_scripts/template_database/', as well as spreadsheets that contain the initial concentrations as well as reaction rate parameters needed by PHT3D, stored as .xlsx files in './model_data/flopy_scripts/', to create the models.</li> <li>Note that the .xlsx files are used by PHT3D-FSP in the model scripts to generate relevant PHT3D input files (compare https://doi.org/10.5281/zenodo.7559750 for more details).</li> </ul> </li> <li>SEAWAT/PHT3D input files <ul> <li>Original SEAWAT and PHT3D input files, which were created with the corresponding model scripts previously (see step before).</li> <li>Input files are stored in './model_data/model_files/vXYZ/model_files/' for each model variant, where 'XYZ' is a wildcard for the model number.</li> <li>SEAWAT/PHT3D executables can directly run the model files files. Thus, the files don't need to be re-created via the previous step.</li> </ul> </li> <li>Model outputs <ul> <li>Model output data is stored as NumPy arrays in './model_data/model_files/vXYZ/npy_arrays/', where 'XYZ' is a wildcard for the model number.</li> <li>The script './model_data/flopy_scripts/template_output/pht3d_output_hpc_v006.py' was used to generate the output files.</li> <li>2-D species concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/species/', where 'XYZ' is a wildcard for the model number.</li> <li>Species min./max. concentration arrays are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/min_max/', where 'XYZ' is a wildcard for the model number.</li> <li>2-D water budget arrays (CH & WEL boundaries) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/budgets/', where 'XYZ' is a wildcard for the model number.</li> <li>Model discretization information (ncol, nrow, nlay etc.) are stored in the subfolder './model_data/model_files/vXYZ/npy_arrays/discretization/', where 'XYZ' is a wildcard for the model number.</li> </ul> </li> <li>Figure files <ul> <li>Original figure files as well as the corresponding Python scripts to create the figures are stored in the subfolder'./figures'.</li> </ul> </li> </ul> <p>Numbering of the model variants is as follows:<br><br>v401 --> VAR-conservative<br>v402 --> VAR-OM<br>v403 --> VAR-C/I<br>v404 --> VAR-C/I/S<br>v405 --> VAR-C/I/P<br>v406 --> VAR-C/I/P/H<br>v407 --> VAR-C/I/P/V<br>v408 --> VAR-C/I/P-Co<br>v409 --> VAR-all<br>v410 --> VAR-all (no C)</p> </div> <div> </div> <div>Literature:</div> <div> </div> <div>Bakker, M., Post, V., Langevin, C.D., Hughes, J.D., White, J.T., Starn, J.J. and Fienen, M.N., 2016. Scripting MODFLOW model development using Python and FloPy. Groundwater, 54(5), pp.733-739. https://doi.org/10.1111/gwat.12413</div> <div> </div> <div>Seibert, S.L., Massmann, G., Meyer, R., Post, V.E.A., Greskowiak, J., 2024. Impact of mineral reactions and surface complexation on the transport of dissolved species in a subterranean estuary: Application of a comprehensive reactive transport modeling approach. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2024.104763</div> <div> </div> <div><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Vincent E.A. Post (vincent@edinsi.nl), Rena Meyer (rena.meyer@uol.de) or Gudrun Massmann (gudrun.massmann@uol.de)</div>
Research data related to the article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems"
<p><strong>Research Data related to the article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems" by Seibert et al. (2024) published in <em>Earth's Future</em></strong></p> <p>Dear reader,</p> <p>reasearch data are provided for the research article "Understanding Climate Change and Anthropogenic Impacts on the Salinization of Low-lying Coastal Groundwater Systems" by Seibert et al. (2024) published in <em>Earth's Future</em>. The authors hope that the research data allows for a better understanding of the modeling workflow. Questions regarding the modeling approach etc. can be directed to the authors, see contact details below.</p> <p>The research data covers the following files:</p> <ul> <li>iMOD-Python (Visser and Bootsma, 2019) scripts to create the iMOD-WQ (Verkaik et al., 2021) input files for the n=566 model variants. Subfolders for each model variant and corresponding files are stored in the subfolder 'model_variants'. An overview regarding the set-up of the model variants is presented in the .xlsx spreadsheet 'model_variants_overview.xlsx' in the folder 'model_variants'.</li> <li>Base data files, used as input files to iMOD-WQ (Verkaik et al., 2021), stored in the subfolder 'imod_input'. However, in most cases no consent for re-distribution of these data sets exists, and they cannot be made freely available through this publication. Please, consider the corresponding meta-data files and/or get in touch with one of the authors for further information.</li> <li>Post-processed model output data, which was further used for model evaluation, stored in the subfolder 'model_output'.</li> <li>Figure files and the corresponding .py scripts, stored in the subfolder 'figures'.</li> </ul> <p>Meta-data files are provided with data files in the different subfolders for clarification.</p> <p>iMOD-WQ (Verkaik et al., 2021) input and .run-files were executed on the University Oldenburg High-Performance Cluster 'Rosa', funded by DFG through its Major Research Instrumentation Program, INST 184/225-1 FUGG, and the Ministry of Science and Culture (MWK) of the Lower Saxony State.</p> <p>Further information on the iMOD suite can be found here: https://deltares.github.io/iMOD-Documentation/</p> <p>The DFG is thanked for SALTSA project funding (DFG project number MA 3274/9-1) within the Priority Programme ‘Regional Sea Level Change and Society (SeaLevel)’. Research related to this article further benefited from funding of the projects WAKOS (BMBF; support code 01LR2003E) and the DFG research unit FOR 5094: The dynamic deep subsurface of high-energy beaches (DynaDeep).</p> <p>Literature:</p> <p>Verkaik, J., Hughes, J. D., van Walsum, P. E. V., Oude Essink, G. H. P., Lin, H. X., & Bierkens, M. F. P. (2021). Distributed memory parallel groundwater modeling for the Netherlands Hydrological Instrument. Environmental Modelling & Software, 143, p.105092.</p> <p>Visser, M., & Bootsma, H. (2019). iMOD-Python: Work with iMOD MODFLOW models in Python. Retrieved from https://imod.xyz/</p> <p>Seibert, S. L., Greskowiak, J., Oude Essink, G. H. P., & Massmann, G. (2024). Understanding climate change and anthropogenic impacts on the salinization of low‐lying coastal groundwater systems. Earth's Future, 12, e2024EF004737. https://doi.org/10.1029/2024EF004737<br><br><strong>Contact one of the authors if you have further questions</strong>: Stephan L. Seibert (stephan.seibert@uol.de), Janek Greskowiak (janek.greskowiak@uol.de), Gualbert H.P. Oude Essink (Gualbert.OudeEssink@deltares.nl) or Gudrun Massmann (gudrun.massmann@uol.de)</p>
Supplementary material for research article "Quantifying the risk mitigation efficiency of changing silvicultural systems under storm risk throughout history"
<p>This public repository contains mainly datasets generated and analyzed during the current study, closely linked to the research article "Quantifying the risk mitigation efficiency of changing silvicultural systems under storm risk throughout history". Furthermore, the repository contains additional figures and deep dives on the methodological background the research article was built on.</p>
Raw data of the research article
<p>All the raw data of the research article has been give that is freely accessible to readers, reviewers and so on.</p>
Research Data for the Journal Article: Metal-free catalytic systems based on imidazolium chloride and strong bases for selective oxidative esterification of furfural to methyl furoate
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Research Data for the Journal Article: Insertion of CO2 to 2-methyl furoate promoted by a cobalt hypercrosslinked polymer catalyst to obtain a monomer of CO2-based biopolyesters
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Research Data for the Journal Article: Hypercrosslinked porous polymer as catalyst for efficient biodiesel production
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Research Data for the Journal Article: Efficient DMF-assisted synthesis of formamides from amines using CO2 catalyzed by heterogeneous metal-free imidazolium-hypercrosslinked polymers
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Data related to research article: Towards mouse genetic-specific RNA-sequencing read mapping
<p>This dataset contains data related to the research article: "Towards mouse genetic-specific RNA-sequencing read mapping".</p>
Research data from the two surveys on IoT implementation for Article "User and Professional Aspects for Sustainable Computing Based on the Internet of Things in Europe"
<p>The file includes data collected through two online surveys linked to the article "User and Professional Aspects for Sustainable Computing Based on the nternet of Things in Europe" published by journal Sensors in January 2023:</p> <ul> <li>Survey on factors that inlfuence IoT Adoption by non technical users</li> <li>Survey on recommended profile focused on IoT implementation for two professional roles in the context of Smart Cities (SC) projects: SC engineer and SC technician.</li> </ul>
Topic Modeling for Multi-label Research Articles
<p>The abstract and title for a set of research articles, and their assigned topics. The research article abstracts and titles are sourced from the following 6 topics:</p> <ol> <li> <p>Computer Science</p> </li> <li> <p>Physics</p> </li> <li> <p>Mathematics</p> </li> <li> <p>Statistics</p> </li> <li> <p>Quantitative Biology</p> </li> <li> <p>Quantitative Finance</p> </li> </ol> <p>Note that a research article can possibly have more than 1 topic. For more details check out the paper of :</p> <p>"Evaluation of SVM Transformations for Multi-Label Research Article Classification"</p>
Codes and data related to the article: Renard et al. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. Journal of Geophysical Research - Atmospheres.
<p>This package contains R codes and data related to the article:</p> <p>B. Renard, D. McInerney, S. Westra, M. Leonard, D. Kavetski, M. Thyer and J.-P. Vidal. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. <em>Journal of Geophysical Research - Atmospheres</em>. DOI: <a href="https://doi.org/10.1029/2022JD037908">10.1029/2022JD037908</a></p> <p><strong>Analyses</strong></p> <p>This folder contains the R scripts used to set up models, analyse results and prepare figures. See README file for details.</p> <p><strong>ShinyApp</strong></p> <p>This folder contains an interactive Shiny App to explore the data and the results from the article.</p> <p>An online version can be found at <a href="https://hydroapps.recover.inrae.fr/HEGS-paper">https://hydroapps.recover.inrae.fr/HEGS-paper</a></p> <p> </p>
Dataset of article: Investigating Developers' Perception on Success Factors for Research Software Development
<p>This dataset is an addendum to the article "Investigating Developers' Perception on Success Factors for Research Software Development" to provide information regarding the anonymously collected data.</p> <p> </p> <p> </p> <p> </p>
Research Data for article "Clava: C/C++ source-to-source compilation using LARA"
<p>Setup and results for the Section "4. Impact" of the article "Clava: C/C++ source-to-source compilation using LARA"</p> <p>#4.1. Stress Test</p> <p>Instruments several large programs so that they produce a call graph when the program executes.</p> <p>To run the test use the command: clava -c stress_test.clava</p> <p>Some examples (e.g., gcc.c) will only parse sucessfully on a Linux machine.</p> <p>## Files</p> <p>'stats-raw_data.zip' - Raw results taken for the article.</p> <p>'processed_stats.json' - Processed results that are presented in the article.</p> <p><br> #4.3. OpsCounter</p> <p>Instruments the NAS benchmark set so that it counts the number of source code operations executed by the kernels.</p> <p>To run the test use the command: clava -c ops_counter.clava</p> <p>## Files</p> <p>'OpsCounterNAS_S_W_A.json' - Raw results taken for the article.</p> <p>'Results.xlsx' - Processed results that are presented in the article.</p>
Raw data for the research article "Rasch analysis of the Listening Effort Questionnaire - Cochlear Implant (LEQ-CI)"
<p>These are the raw data for the paper entitled "Rasch analysis of the Listening Effort Questionnaire - Cochlear Implant (LEQ-CI)" that is currently under revision in Ear and Hearing.</p>
Dataset for article: Changes in evidence for studies assessing interventions for COVID-19 reported in preprints: meta-research study. BMC Med 18, 402 (2020).
<p>This dataset was used in the analyses reported in Oikonomidi, T., Boutron, I., Pierre, O. et al. Changes in evidence for studies assessing interventions for COVID-19 reported in preprints: meta-research study. BMC Med 18, 402 (2020). https://doi.org/10.1186/s12916-020-01880-8. </p> <p>This project is ancillary to the COVID-NMA Living systematic review and network meta-analysis of Covid-19 trials: https://covid-nma.com/</p> <p>The first spreadsheet entitled "key" includes the full description of the dataset.</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.