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69 results for “public assessments”
Codes and dataset of the publication "Effectiveness of Sentinel-1 and Sentinel-2 for Flood Detection Assessment in Europe"
<p>The folder contains the codes, input and output of the analysis carried out for supporting the publication of the paper:</p> <p>Tarpanelli A., Mondini A., Camici S.:Effectiveness of Sentinel-1 and Sentinel-2 for Flood Detection Assessment in Europe, Natural Hazards and Earth System Sciences, https://doi.org/10.5194/nhess-2022-63, 2022.</p> <p> </p> <p>The codes should be run in order A1-A7 to generate all the figures of the paper.</p> <p>For details please send an email to:</p> <p>angelica.tarpanelli@irpi.cnr.it</p> <p> </p>
GERDAT011 Literature search for publication - Geriatric assessment in the management of older patients with cancer – a systematic review (update).xlsx
<p>Search data belonging to the publication Geriatric assessment in the management of older patients with cancer – a systematic review (update)</p>
Dataset: Publication cultures and Dutch research output: a quantitative assessment
<p>Dataset belonging to the report: <a href="https://doi.org/10.5281/zenodo.2643360">Publication cultures and Dutch research output: a quantitative assessment</a></p> <p> </p> <p>On the report:</p> <p>Research into publication cultures commissioned by VSNU and carried out by Utrecht University Library has detailed university output beyond just journal articles, as well as the possibilities to assess open access levels of these other output types. For all four main fields reported on, the use of publication types other than journal articles is indeed substantial. For Social Sciences and Arts & Humanities in particular (with over 40% and over 60% of output respectively not being regular journal articles) looking at journal articles only ignores a significant share of their contribution to research and society. This is not only about books and book chapters, either: book reviews, conference papers, reports, case notes (in law) and all kinds of web publications are also significant parts of university output.</p> <p>Analyzing all these publication forms and especially determining to what extent they are open access is currently not easy. Even combining some the largest citation databases (Web of Science, Scopus and Dimensions) leaves out a lot of non-article content and in some fields even journal articles are only partly covered. Lacking metadata like affiliations and DOIs (either in the original documents or in the scholarly search engines) makes it even harder to analyze open access levels by institution and field. Using repository-harvesting databases like BASE and NARCIS in addition to the main citation databases improves understanding of open access of non-article output, but these routes also have limitations. The report has recommendations for stakeholders, mostly to improve metadata and coverage and apply persistent identifiers.</p>
Dataset for publication "Assessing the techno-economic benefits of LEMs for different grid topologies and prosumer shares"
<p>This dataset contains all the results and scenarios for this paper. Each region has two files in which you can find all the scenarios for the market design with and without the local energy market. The folders within these files contain the results for one scenario for a given share of PV, EVs, and heat pumps (HPs). The results folders can also be used to rerun the scenarios. To do so, place the respective scenario in the tool's scenario folder.</p> <p>USE CASE:<br>If you do not want to check all the files of the results or want to rerun the scenarios, use this version. If you want to download the relevant files for the analysis and figure creation of the paper, use the <a href="https://zenodo.org/records/13907329" target="_blank" rel="noopener">compact version</a>.</p> <p>TOOL:<br><a href="https://github.com/TUM-Doepfert/lemlab/tree/doepfert2024_lem">lemlab</a></p>
Compact version: Dataset for publication "Assessing the techno-economic benefits of LEMs for different grid topologies and prosumer shares"
<p>This is the compact version of the results. They contain only the relevant files for the analysis and figure creation of the paper.</p> <p>USE CASE:<br>If you do not want to access every single file of the results or rerun the scenarios, you should use the compact version.</p> <p>TOOL:<br><a href="https://github.com/TUM-Doepfert/lemlab/tree/doepfert2024_lem">lemlab</a></p>
Dataset linking to the publication "An assessment of data sources, data quality and changes in national forest monitoring capacities in the Global Forest Resources Assessment 2005–2020"
<p>This dataset links to the study “An assessment of data sources, data quality and changes in national forest monitoring capacities in the Global Forest Resources Assessment 2005–2020”. This study is published in the journal “Environmental Research Letters” which can be found at <a href="https://iopscience.iop.org/article/10.1088/1748-9326/abd81b">https://iopscience.iop.org/article/10.1088/1748-9326/abd81b</a>. The dataset contains two files, one csv file, and one shape file. The two files contain the same data to meet the different users' needs. The dataset contains variables for assessing national forest monitoring data sources i.e., RS and/or NFI. Separate indicators namely 'Use of RS', and 'Use of NFI' were used to analyze the two data sources (RS and NFI). The description of each variable for these two indicators contained in the dataset is given in the Table below.</p> <table> <caption><strong>The description of the variables in the datase</strong>t <strong>for country capacity assessment</strong></caption> <tbody> <tr> <td><strong>Variables Name</strong></td> <td><strong>Description of the variables</strong></td> </tr> <tr> <td>Country</td> <td>Country</td> </tr> <tr> <td>ISO_A3_CODE</td> <td>ISO A3 Code for country</td> </tr> <tr> <td>ADM0_CODE</td> <td>ADMO Code for country</td> </tr> <tr> <td>CONTINENT</td> <td>Continent</td> </tr> <tr> <td>Region</td> <td>Region</td> </tr> <tr> <td>RSInd_05</td> <td>Use of remote sensing (RS) for forest area (change) monitoring 2005 Indicator</td> </tr> <tr> <td>RSSc_05</td> <td>Use of RS for forest area (change) monitoring 2005 Score</td> </tr> <tr> <td>RSInd _10</td> <td>Use of RS for forest area (change) monitoring 2010 Indicator</td> </tr> <tr> <td>RSSc _10</td> <td>Use of RS for forest area (change) monitoring 2010 Score</td> </tr> <tr> <td>RSInd_15</td> <td>Use of RS for forest area (change) monitoring 2015 Indicator</td> </tr> <tr> <td>RSSc _15</td> <td>Use of RS for forest area (change) monitoring 2015 Score</td> </tr> <tr> <td>RSInd_20</td> <td>Use of RS for forest area (change) monitoring 2020 Indicator</td> </tr> <tr> <td>RSSc _20</td> <td>Use of RS for forest area (change) monitoring 2020 Score</td> </tr> <tr> <td>DRS05_20</td> <td>Difference ‘use of RS’ 2005-2020</td> </tr> <tr> <td>NFIInd_05</td> <td>Use of national forest inventories (NFI) for forest monitoring 2005 Indicator</td> </tr> <tr> <td>NFISc_05</td> <td>Use of NFI for forest monitoring 2005 Score</td> </tr> <tr> <td>NFIInd _10</td> <td>Use of NFI for forest monitoring 2010 Indicator</td> </tr> <tr> <td>NFISc _10</td> <td>Use of NFI for forest monitoring 2010 Score</td> </tr> <tr> <td>NFIInd_15</td> <td>Use of NFI for forest monitoring 2015 Indicator</td> </tr> <tr> <td>NFISc _15</td> <td>Use of NFI for forest monitoring 2015 Score</td> </tr> <tr> <td>NFIInd_20</td> <td>Use of NFI for forest monitoring 2020 Indicator</td> </tr> <tr> <td>NFISc _20</td> <td>Use of NFI for forest monitoring 2020 Score</td> </tr> <tr> <td>DNFI05_20</td> <td>Difference ‘Use of NFI’ 2005-2020</td> </tr> </tbody> </table> <p>Indicators and Scores in the above Table for showing the use of RS and NFI data for forest monitoring in Figure 1 (1a, 1b, and 2a, 2b) are related in the following way.</p> <table> <caption><strong>The indicator values and scores of the country capacity assessment</strong></caption> <tbody> <tr> <td><strong>Indicator</strong></td> <td><strong>Score</strong></td> </tr> <tr> <td>Low</td> <td>0</td> </tr> <tr> <td>Limited</td> <td>1</td> </tr> <tr> <td>Intermediate</td> <td>2</td> </tr> <tr> <td>Good</td> <td>3</td> </tr> <tr> <td>Very Good</td> <td>4</td> </tr> </tbody> </table> <p>The capacity changes from 2005 to 2020 in Figure 1 (1c & 2c) are related in the following way.</p> <table> <caption><strong>The indicator values and levels for country capacity changes</strong></caption> <tbody> <tr> <td><strong>Capacity change values</strong></td> <td><strong>Capacity change levels</strong></td> </tr> <tr> <td>1,2,3,4</td> <td>Increase</td> </tr> <tr> <td>0</td> <td>No change</td> </tr> <tr> <td>-1,-2,-3,-4</td> <td>Decrease</td> </tr> </tbody> </table> <p> </p>
Data to support the publication "Unknown risk: assessing refugee camp flood risk in Ethiopia"
<p>This dataset supports the publication "Unknown risk: assessing refugee camp flood risk in Ethiopia". This dataset contains the delineated boundaries for 24 refugee camps in Ethiopia. Also included are refugee camp building footprint data (where available). All datasets are in shapefile format.</p>
Code and data for publication "Assessing carbon cycle projections from complex and simple models under SSP scenarios" published in "Climatic Change"
<p>Data and scripts for the article "Assessing carbon cycle projections from complex and simple models under SSP scenarios" by I. Melnikova, P. Ciais, O. Boucher and K. Tanaka was accepted for publication in Climatic Change (https://doi.org/10.1007/s10584-023-03639-5)</p><p> </p><p>We use bash, CDO, and python.</p><p>SSP2.xlsx contains preprocessed annual estimates of climate and carbon cycle variables from ESMs and SCMs used in the paper.</p><p>Two bash scripts contain preprocessing cdo commands for ESM output.s SCMs were preprocessed directly in python.</p><p>Jupyter notebook (python) contains preprocessing of data and plotting of all figures of the manuscript. The folder "additional" contains some more Excel files needed to run Jupyter-Notebook. Please adapt the folder names.</p><p>If you have any questions, please contact the corresponding author Irina MELNIKOVA at melnikova . irina@nies.go.jp</p><p> </p>
Regional Assessment of buildings' Material Intensities (RASMI): Version 20230905: first public release B - data only
<p><strong>Version 20230905: first public release of RASMI (Regional Assessment of buildings' Material Intensities).</strong></p> <p>This Zenodo version contains two files:</p> <ul> <li><code>MI_ranges_20230905.xlsx</code> is the dataset of the estimated MI ranges. <em><strong>This is probably the file you're looking for.</strong></em></li> <li><code>MI_data_20230905.xlsx</code> is the raw pools of MI used to create the MI ranges. This is mostly for reproducability.</li> </ul> <p>Please refer to the GitHub readme.md in <a href="https://github.com/TomerFishman/MaterialIntensityEstimator">https://github.com/TomerFishman/MaterialIntensityEstimator</a> for details and how to use.</p> <p>Please cite both the Data Descriptor and the specific data version used:</p> <p>Data Descriptor: Tomer Fishman, Alessio Mastrucci, Yoav Peled, Shoshanna Saxe, Bas van Ruijven. <em>RASMI: Global Ranges of Building Material Intensities Differentiated by Region, Structure, and Function</em>. Scientific Data 2024, 11 (1), 418. <a href="https://doi.org/10.1038/s41597-024-03190-7" rel="nofollow">https://doi.org/10.1038/s41597-024-03190-7</a>.</p> <p>Data version: preferably use the DOI of the Zeonodo release. Refer to the release number (on the right)</p> <p>This work was conducted with support by the IIASA-Israel program, and by the Israel Science Foundation project RUSTY (grant no. 2706/19). Funding was also provided by the Horizon Europe research and innovation programme under grant agreement no. 101056868 (CIRCOMOD) for TF and grant agreement No 101056810 (CircEUlar) for AM. Opinions are those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for this. BvR and AM have been supported by the Energy Demand changes Induced by Technological and Social innovations (EDITS) project, which is an initiative coordinated by the Research Institute of Innovative Technology for the Earth (RITE) and the International Institute for Applied Systems Analysis (IIASA), and funded by the Ministry of Economy, Trade, and Industry (METI), Japan. SS was supported by the Canada Research Chair in Sustainable Infrastructure, Grant Number: 232970.</p>
Data and code for publication: Advancing Maternal Transfer of Organic Pollutants across Reptiles for Conservation and Risk Assessment Purposes
<p>Dataset and r code to prepare the dataset, in support of the publication:</p> <p>"Advancing maternal transfer of organic pollutants across reptiles for conservation and risk assessment purposes"</p> <p>Munoz, C.C., Charles, S., Vermeiren, P. (2024) Environmental Science and Technology, https://doi.org/10.1021/acs.est.4c04668</p> <p>contact email: munozc.cynthia@gmail.com</p>
Dataset for the publication entitled: "Assessment of lithium ion battery ageing by combined impedance spectroscopy, functional microscopy and finite element modelling""
<p>Related to the publication: <a href="https://doi.org/10.1016/j.jpowsour.2021.230459">https://doi.org/10.1016/j.jpowsour.2021.230459</a></p> <p>Datasets for the following Figures:</p> <p>Figure 2.</p> <p>Figure 3.</p> <p>Figure 5.</p> <p>Figure 7.</p>
Data to support the publication "The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment" https://doi.org/10.3390/land10090964
<p>Underlying data of soil measurements and analysis by TUC team for the publication “The Impact of Soil-Improving Cropping Practices on Erosion Rates: A Stakeholder-Oriented Field Experiment Assessment” <a href="https://doi.org/10.3390/land10090964">https://doi.org/10.3390/land10090964</a> from the SoilCare project study sites in Crete. </p> <p>Abstract:</p> <p>The risk of erosion is particularly high in Mediterranean areas, especially in areas that are subject to a not so effective agricultural management–or with some omissions–, land abandonment or wildfires. Soils on Crete are under imminent threat of desertification, characterized by loss of vegetation, water erosion, and subsequently, loss of soil. Several large-scale studies have estimated average soil erosion on the island between 6 and 8 Mg/ha/year, but more localized investigations assess soil losses one order of magnitude higher. An experiment initiated in 2017, under the framework of the SoilCare H2020 EU project, aimed to evaluate the effect of different management practices on the soil erosion. The experiment was set up in control versus treatment experimental design including different sets of treatments, targeting the most important cultivations on Crete (olive orchards, vineyards, fruit orchards). The minimum-to-no tillage practice was adopted as an erosion mitigation practice for the olive orchard study site, while for the vineyard site, the cover crop practice was used. For the fruit orchard field, the crop-type change procedure (orange to avocado) was used. The experiment demonstrated that soil-improving cropping techniques have an important impact on soil erosion, and as a result, on soil water conservation that is of primary importance, especially for the Mediterranean dry regions. The demonstration of the findings is of practical use to most stakeholders, especially those that live and work with the local land.</p>
Data for the publication "Assessing the potential for simplification in global climate model cloud microphysics"
<p>This repository contains the data for the paper:</p> <p>Authors: Ulrike Proske, Sylvaine Ferrachat, David Neubauer, Martin Staab, and Ulrike Lohmann<br> Titel: Assessing the potential for simplification in global climate model cloud microphysics<br> Date: 2022</p> <p>Note that the scripts can be found in the accompanying package (https://doi.org/10.5281/zenodo.5506588)</p>
Model fields supporting the publication "Integrated Assessment of the Risks to Ocean Acidification in the Northern High Latitudes: Regional Comparison of Exposure, Sensitivity and Adaptive Capacity of Pelagic Calcifiers"
<p>These are the model outputs supporting the described manuscript. They include monthly averaged output of aragonite saturation state for each year during the 10-year hindcast. Also included is the particle tracking output, for both the Bering Sea and the Gulf of Alaska, as described in the manuscript.</p>
EUROMALT Briefing note No. 2 Ochratoxin A - Additional document from EUROMALT supporting the comments submitted during the public consultation on the Risk assessment of ochratoxin A in food
<p>This document has been submitted by EUROMALT as additional document supporting the comments submitted during the public consultation organised by the European Food Safety Authority in relation to the draft scientific opinion on the Risk assessment of ochratoxin A in food. The text of the comments is published in the Technical report of the public consultation - see related identifiers section, http://doi.org/10.2903/sp.efsa.2020.1845</p> <p> </p> <p>EUROMALT has agreed by email submitted to EFSA to disclose this confidential document and to have it published on Zenodo.</p> <p>.</p>
data for publication "Benefits of biobased fertilizers as substitutes for synthetic nitrogen fertilizers: Field assessment combining minirhizotron and UAV-based spectrum sensing technologies"
<p>Dataset for the scientific publication "Benefits of biobased fertilizers as substitutes for synthetic nitrogen fertilizers: Field assessment combining minirhizotron and UAV-based spectrum sensing technologies" in the Journal Frontiers of Environmental Science. </p><p><a href="https://doi.org/10.3389/fenvs.2022.988932">https://doi.org/10.3389/fenvs.2022.988932</a></p>
Results and analysis script from a discrete choice experiment assessing public preferences for rewilding in the Oder Delta
<p>1. Rewilding is an emerging paradigm in restoration science, and is increasingly gaining popularity as a cost-effective ecosystem restoration option. A rewilding framework was recently proposed that contains three integral components: restoring trophic complexity, allowing for stochastic disturbances, and enhancing species' potential to disperse. However, as of yet, there has been limited quantitative analysis looking at public preference for rewilding and each of its elements.</p> <p>2. We used a discrete choice experiment approach to determine public preference for rewilding in the Oder Delta. The unique geographical context of the Oder Delta, spreading evenly across two countries, allowed us to analyze differences between the German (n = 1,005) and Polish (n = 1,066) samples.</p> <p>3. In both countries, we found respondents were willing to pay for rewilding interventions when compared against a status quo option. Notably, preferences were strongest for restoring trophic complexity through promoting the comeback of large mammals.</p> <p>4. In addition, we found respondents living locally to the study region had significantly different preferences than the nationwide samples, exhibiting negative willingness to pay for the restoration of natural flooding regimes and the presence of large predator species.</p>
Dataset related to the publication "Procedure for automated low uncertainty assessment of empty cavity mode frequencies in Fabry-Pérot cavity based refractometry"
<p>The data set consists of; The published paper, all figures that present measurement or simulation data in .png and .fig format and the underlying data plotted in the figures in text format. The published plots were generated from the fig files. The text files were generated by reading the plotted data from the fig files. The files are named Fig_XX were XX corresponds to the figure number in the publication. The format of the text file is as follows. Before every data set there is a header consisting of; The number of the subplot where the data is plotted (Plot: XX), the number of the data set in the sub plot (DataSet: XX), and the color of the line or marker in the plot (Color: XX). The description of what each color represents can be found in the publication.</p>
Dataset related to the publication "An Invar-based dual Fabry–Perot cavity refractometer for assessment of pressure with a pressure independent uncertainty in the sub-mPa region"
<p>The data set consists of; The published paper, all figures that present measurement or simulation data in .png and .fig format and the underlying data plotted in the figures in text format.<span> </span>The published plots were generated from the fig files. The text files were generated by reading the plotted data from the fig files. The files are named Fig_XX were XX corresponds to the figure number in the publication.<span> </span>The format of the text file is as follows. Before every data set there is a header consisting of; The number of the subplot where the data is plotted (Plot: XX), the number of the data set in the sub plot (DataSet: XX), and the color of the line or marker in the plot (Color: XX). The description of what each color represents can be found in the publication.</p>
Bibliography on criteria for assessing the quality of scientific publications
<p>The data deposited here consist of references to literature that was evaluated during the development of a qualitative survey and an online questionnaire on the qualitative perception of scientific publications.</p> <p>In preparation for these qualitative interviews and the online survey, a literature study on the qualitative perceptions of scientific literature was conducted in January and February 2018. The focus was on the question which internal characteristics, i.e. in the narrower sense content-related factors, influence the perception of a publication as qualitatively valuable or poor. External characteristics as citation counts should not be at the centre of the research - knowing that they control qualitative perception - since their effect on the perception of the quality of a publication is sufficiently discussed (see e.g. Dong, Loh, & Mondry, 2005).<br> The literature study was based on the results of a search in the databases Web of Science, Scopus, Library, Information Science & Technology Abstracts and the search engine Google Scholar.</p> <p>VisOA_full_results.bib includes references that were considered valuable in principle, VisOA.bib only those that have been considered in the development of the survey instruments.</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.