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.
761
datasets available to search
ShareScore release 0.7.1
Dataset results
761 results for “impact assessment”
IPBES Invasive Alien Species Assessment, database for Chapter 4. Impact Evidence Database
<p>This is a database described in the data management report for chapter 4 of IPBES thematic assessment on invasive alien species and their control.</p> <p>Data were gathered on direct observations of impacts from published literature, including grey literature, in order to form a database on the evidence to which invasive alien species impact, negatively and positively, nature, nature's contributions to people and good quality of life for Chapter 4 of IPBES thematic assessment of invasive alien species and their control. The criteria for inclusion were a published direct evidence of an impact on native species, a change in ecosystem properties, nature's contributions to people and the extent to which humans were affected through changes in their constituents of well-being.</p> <p> </p> <p>Updates to version 3:</p> <p>1) Assessor “EAM” has been replaced by “Ester Mostert”,</p> <p>2) There were 50 Unique IDs that were paired. These are now differentiated by adding an a and b to the end of these to make them truly unique,</p> <p>3) Removed 40 duplicates</p> <p>4) RowID were re-numbered to reflect the unique number of rows</p> <p> </p>
Looking in the medicine cabinet: methods for using real-world data to assess the impact of measles, mumps and rubella (MMR) and recombinant adjuvanted varicella-zoster vaccines on coronavirus disease 2019 (COVID-19) prevention and case fatality
<p>Supplementary File S1. 20210712_vx_off_target_pubdraft_S1 (Tables, Graphs and scripts associated with publication)</p> <p>Data file 1. Basic_Analysis.R (descriptive analysis script in R, for use with cleaned data files 3, 4 and 6)<br> Data file 2. Cleaning (Script demonstrating how Cerner data was cleaned upon download)<br> Data file 3. COVID_all_cleaned (CSV file with all COVID+ subjects in Cerner institutions)<br> Data file 4. COVID_mmr_data_cleaned (CSV file with COVID+ patients between 25-64 years old, including institution id, age category, gender, whether patient is in emergency department or inpatient, flu vaccine history, MMR vaccine history and mortality outcomes)<br> Data file 5. COVID_mmr_data_matched (CSV file matching MMR vaccine-exposed cases to controls based on propensity scores)<br> Data file 6. COVID_zoster_data_cleaned (CSV file with COVID+ patients above 50 years old, including institution id, age category, gender, whether patient is in emergency department or inpatient, flu vaccine history, zoster vaccine history and mortality outcomes)<br> Data file 7. COVID_zoster_data_matched (CSV file matching zoster vaccine-exposed cases to controls based on propensity scores)<br> Data file 8. General_25_64_data_cleaned (CSV file, all patients in Cerner institutions between 25 – 64 years old, including institution id, age category, gender, whether patient is in emergency department or inpatient, flu vaccine history, MMR vaccine history, SARS-CoV-2 infection and COVID-19 mortality outcomes ).<br> Data file 9. General_over50_data_cleaned (CSV file, all patients in Cerner institutions above 50 years old, including institution id, age category, gender, whether patient is in emergency department or inpatient, flu vaccine history, zoster vaccine history, SARS-CoV-2 infection and COVID-19 mortality outcomes).<br> Data file 10. Included_tenants (CSV file, institution IDs whose contributed cases comprise at least 0.5% of the aggregate sample size).<br> Data file 11. MMR_ps (R script to run for MMR-related files analysis)<br> Data file 12. Zoster_ps (R script to run for zoster-related files analysis)</p>
Dataset for Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix into the Future
<p>This data repository feeds into the meta-repository setup for post-processing of GCAM-SAM outputs. GitHub link of meta-repository is: <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">https://github.com/JGCRI/Kyle-etal_2022_EF</a> <br> <br> Folders: <br> <strong>model/</strong> is the static version of the model used to simulate 8 scenarios. See the <a href="https://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GitHub GCAM-SAM repository</a> to follow active development of this model. <br> <strong>inputs/</strong> folder contains input datasets and scripts used to prepare files while postprocessing. This is to be used with <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">GitHub post-processing meta-repository</a>. <br> <strong>outdata/</strong> contains <a href="http://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GCAM-SAM</a> output and <a href="http://github.com/JGCRI/Kyle-etal_2022_EF">post-processed</a> output files used to plot figures. <br> <br> Key files: <br> <em><strong>SAM-matrix.dat</strong></em> is the consolidated GCAM-SAM output. Use <em>proj_load.R</em> in the <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">metarepo</a> to read the file. <br> <em><strong>region_vals.csv</strong></em> has all 8 indicators in all 8 scenarios for years 2020 till 2100 on a 10 year time step. <br> <br> Short introduction to the study:</p> <p>In this paper sustainable agriculture matrix (SAM) is estimated to 2100 using Global Change Analysis Model (GCAM). We model combinatorial variations of yield intensification, dietary shift, and greenhouse gas mitigation scenarios. Findings include scenarios having significant tradeoffs across multiple environmental, economic, and social dimensions. Assessment of these multi-dimensional tradeoffs in a consistent framework improves the quality of information for decision-making.<br> <br> Should you have any questions, feel free to reach out Page Kyle at <a href="mailto:pkyle@pnnl.gov">pkyle@pnnl.gov</a>. </p>
Use of geolocators for investigating breeding ecology of a rock crevice-nesting seabird: method validation and impact assessment
<p>1: Investigating ecology of marine animals, imposes a continuous challenge due to their temporal and/or spatial unavailability. Light-based geolocators (GLS) are animal-borne devices that provide relatively cheap and efficient method to track seabird movement and are commonly used to study migration. Here we explore the potential of GLS data to establish individual behaviour during the breeding period in a rock crevice-nesting seabird, the Little Auk, Alle alle. 2: By deploying GLS on 12 breeding pairs, we developed a methodological workflow to extract birds' behaviour from GLS data (nest attendance, colony attendance and foraging activity), and validated its accuracy using behaviour extracted from a well-established method based on video recordings. We also compared breeding outcome, as well as behavioural patterns of logged individuals with a control group treated similarly in all aspects except for the deployment of a logger, to assess short-term logger effects on fitness and behaviour. 3: We found a high accuracy of GLS-established behavioural patterns, especially during the incubation and early chick rearing period (when birds spend relatively long time in the nest). We observed no apparent effect of logger deployment on breeding outcome of logged pairs, but recorded some behavioural changes in logged individuals (longer incubation bouts and shorter foraging trips). 4: Our study provides a useful framework for establishing behavioural patterns (nest attendance and foraging) of a crevice-nesting seabird from GLS data (light and conductivity), especially during incubation and early chick rearing period. Given that GLS deployment does not seem to affect the breeding outcome of logged individuals but does affect fine-scale behaviour, our framework is likely to be applicable to a variety of crevice/burrow nesting seabirds, even though precautions should be taken to reduce deployment effect. Finally, because each species may have its own behavioural and ecological specificity, we recommend performing a pilot study before implementing the method in a new study system.</p>
Assessing Future Hydrological Impacts of Climate Change on High-Mountain Central Asia: Insights from a Stochastic Soil Moisture Water Balance Model
<p>Dataset accompanying the publication "Assessing Future Hydrological Impacts of Climate Change on High-Mountain Central Asia: Insights from a Stochastic Soil Moisture Water Balance Model"</p> <p> </p>
Data from: Integrating ecological niche and hydrological connectivity models to assess the impacts of hydropower plants on an endemic and imperiled freshwater turtle
<p>We built this dataset to assess the impacts of hydropower plants on the distribution of an endemic and imperiled freshwater turtle with very unique ecological requirements, the Williams' side-necked turtle (<em>Phrynops</em> <em>williamsi</em>). To prevent and mitigate impacts, we prioritized sites for species conservation by classifying planned HPP locations according to their predicted adverse effects on species distribution. The dataset has two files: i) species occurrence records and ii) hydropower plant data. The first dataset was fully built by the authors and the second was modified from the Brazilian Electricity Regulatory Agency (ANEEL) georeferenced data system.</p>
Scripts, inputs and outputs of Module 4 ANOVA test regarding Deliverable D6.3 "Performance and Impact assessment" in the IP4MaaS project
<p>All the materials, inputs, models, and scripts that are used in the performance assessment toolbox (IP4MaaS project, Deliverable D6.3 Performance and Impact Assessment) are available in the attached folder. </p> <p>The attached folder contains the following:</p> <p>Module 4_Calculation of ANOVA test (the input, formulation, macros, and scripts of ANOVA test per each IP4MaaS demo site).</p> <p>The scripts have been designed for easy adoption in other projects with similar end goals. While the scripts operate on the codified representation of the traveller profiles, functionalities, and service providers, there is no restriction on the type of codification used. The only factor that the scripts assume is the order of the variables introduced for codification. That is the traveller profile variable (wherever applicable), followed by the Functionality variable, followed by the Service Provider variable. As long as the order is maintained, the scripts self-analyze the number of variables representing the traveller profiles, functionalities, and service providers, and perform calculations (USI, Effectiveness) and analysis (Regression and BN), Hence, in a similar framework, the scripts may be used for performing data analysis on a large data set with no restriction on the number of functionalities, service providers or subsets of traveller profiles. Documented Scripts can be found in a downloadable ZIP file here. </p>
Scripts, inputs and outputs of Module 5 USI travellers, TSPs and Effectiveness regarding Deliverable D6.3 "Performance and Impact assessment" in the IP4MaaS project
<p>All the materials, inputs, models, and scripts that are used in the performance assessment toolbox (IP4MaaS project, Deliverable D6.3 Performance and Impact Assessment) are available in the attached folder. </p> <p>The attached folder contains the following:</p> <p>Module 5_Results and outputs of USI Travellers, USI TSPs, Effectiveness (Travellers & TSPs) and the average of Effectiveness of all functionalities individually across all 6 demo sites (inputs, calculation, formulation, scripts of USI travellers, TSPs and Effectiveness per each IP4MaaS demo site).</p> <p>The scripts have been designed for easy adoption in other projects with similar end goals. While the scripts operate on the codified representation of the traveller profiles, functionalities, and service providers, there is no restriction on the type of codification used. The only factor that the scripts assume is the order of the variables introduced for codification. That is the traveller profile variable (wherever applicable), followed by the Functionality variable, followed by the Service Provider variable. As long as the order is maintained, the scripts self-analyze the number of variables representing the traveller profiles, functionalities, and service providers, and perform calculations (USI, Effectiveness) and analysis (Regression and BN), Hence, in a similar framework, the scripts may be used for performing data analysis on a large data set with no restriction on the number of functionalities, service providers or subsets of traveller profiles. Documented Scripts can be found in a downloadable ZIP file here. </p>
Scripts, inputs and outputs of Module 1 AHP analysis regarding Deliverable D6.3 "Performance and Impact assessment" in the IP4MaaS project
<p>All the materials, inputs, models, and scripts that are used in the performance assessment toolbox (IP4MaaS project, Deliverable D6.3 Performance and Impact Assessment) are available in the attached folder. </p> <p>The attached folder contains the following:</p> <p>Module 1_AHP and Pairwise comparison matrix calculation_IP4MaaS II (formulations and calculations of pairwise comparison matrix per each IP4MaaS demo site).</p> <p>The scripts have been designed for easy adoption in other projects with similar end goals. While the scripts operate on the codified representation of the traveller profiles, functionalities, and service providers, there is no restriction on the type of codification used. The only factor that the scripts assume is the order of the variables introduced for codification. That is the traveller profile variable (wherever applicable), followed by the Functionality variable, followed by the Service Provider variable. As long as the order is maintained, the scripts self-analyze the number of variables representing the traveller profiles, functionalities, and service providers, and perform calculations (USI, Effectiveness) and analysis (Regression and BN), Hence, in a similar framework, the scripts may be used for performing data analysis on a large data set with no restriction on the number of functionalities, service providers or subsets of traveller profiles. Documented Scripts can be found in a downloadable ZIP file here. </p>
Scripts, inputs and outputs of Module 2 Regression analysis regarding Deliverable D6.3 "Performance and Impact assessment" in the IP4MaaS project
<p>All the materials, inputs, models, and scripts that are used in the performance assessment toolbox (IP4MaaS project, Deliverable D6.3 Performance and Impact Assessment) are available in the attached folder. </p> <p>The attached folder contains the following:</p> <p>Module 2_Regression analysis (inputs, scripts, and formulations of regression analysis per each IP4MaaS demo site).</p> <p>The scripts have been designed for easy adoption in other projects with similar end goals. While the scripts operate on the codified representation of the traveller profiles, functionalities, and service providers, there is no restriction on the type of codification used. The only factor that the scripts assume is the order of the variables introduced for codification. That is the traveller profile variable (wherever applicable), followed by the Functionality variable, followed by the Service Provider variable. As long as the order is maintained, the scripts self-analyze the number of variables representing the traveller profiles, functionalities, and service providers, and perform calculations (USI, Effectiveness) and analysis (Regression and BN), Hence, in a similar framework, the scripts may be used for performing data analysis on a large data set with no restriction on the number of functionalities, service providers or subsets of traveller profiles. Documented Scripts can be found in a downloadable ZIP file here. </p>
Protecting the resource: an assessment of mitigation methods used to protect large trees from African elephant impact in a savanna system
<p>African elephants (<em>Loxodonta africana</em>) can alter the structural components of savanna ecosystems, often through the reduction of the large tree (>5 m height) cover component. Elephant impact can be amplified in small, protected areas, or areas where water is readily available to elephants. One management option is to protect large trees directly using applied mitigation methods to limit elephant impact. In this paper, we assessed and compared the effectiveness and logistical requirements of four mitigation methods that have been applied to protect large trees from elephant impact in South Africa's Greater Kruger National Park - namely African honeybees (<em>Apis mellifera scutellata</em>) in beehives; creosote oil in glass jars, concrete pyramids arranged in circles around trees, as well as wire-netting the trees' main stems. For each method, elephant impact levels and tree mortality rates were measured over a 2–5-year period depending on the method in use. Sample sizes ranged from 43 to 59 trees per mitigation method, with a comparable control, which was a tree of the same species and morphological dimensions but lacking any mitigation application. Beehives were the most effective method at reducing tree loss, significantly reducing tree mortality from 34% (6.8%/year) in control trees to only 10% (2%/year) over the five-year experimental period. However, beehives were the most expensive method to apply to a tree, although this cost can be compensated through honey sales. Concrete pyramids reduced tree loss when the combined pyramid radius was >1.5 m in length, whilst wire-netting was effective against bark-stripping by elephants but was still vulnerable to heavier forms of impact such as uprooting and stem snapping. Creosote jars did not prevent elephants from impacting treated trees. Our results provide managers with a toolkit for protecting large trees against elephant impact, commenting on both the efficacy and the logistical constraints for each method.</p>
Trial to Assess the Impact of PrEP to Tenofovir Gel on the Efficacy of Tenofovir-containing ART on Viral Suppression
ClinicalTrials.gov study NCT01387022. IPD Sharing: Not stated. Countries: 1. Publications: 7.
Assess and Adapt to the Impact of COVID-19 on CVD Self-Management and Prevention Care in Adults Living With HIV
ClinicalTrials.gov study NCT04661813. IPD Sharing: YES. Countries: 1. Publications: 1.
Assessing the Impact of Lipoprotein (a) Lowering With Pelacarsen (TQJ230) on Major Cardiovascular Events in Patients With CVD
ClinicalTrials.gov study NCT04023552. IPD Sharing: YES. Countries: 43. Publications: 8.
A Phase 4 Study to Assess the Impact of Patient Support Program on Health Related Quality of Life and Adherence in Subjects With Relapsing-Remitting Multiple Sclerosis Administered Rebif® With the Reb
ClinicalTrials.gov study NCT01791244. IPD Sharing: Not stated. Countries: 2. Publications: 1.
Assessing the Impact of VR-Based Observational Mindfulness Meditation on Stress Reduction in Adults
ClinicalTrials.gov study NCT06704282. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Assessing the Impact of Calcium Channel Blockers on COGnitive Function in the Very Elderly (AI-COG)
ClinicalTrials.gov study NCT01868165. IPD Sharing: NO. Countries: 1. Publications: 1.
Cluster Randomized Trial of Hospitals to Assess Impact of Targeted Versus Universal Strategies to Reduce Methicillin-resistant Staphylococcus Aureus (MRSA) in Intensive Care Units (ICUs)
ClinicalTrials.gov study NCT00980980. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Study to Evaluate the Impact of FeNO Assessments on Asthma Management Decisions in Subject 7 to 60 Years of Age
ClinicalTrials.gov study NCT01729247. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Assessing the Impact of a Social Media-Based Educational Intervention Using WhatsApp Video Messages on Dental Caries Prevention Knowledge, Oral Hygiene Practices, and Attitudes Toward Dental Health Am
ClinicalTrials.gov study NCT07363317. IPD Sharing: NO. Countries: 1. Publications: 3.
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.