Find research datasets worth reusing

opencc-by-4.0Apr 2020View details →

Data relating to Clyne et al. Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study

Data relating to the study reported in the paper "Quality, scope and reporting standards of randomised controlled trials in Irish Health Research: an observational study".

opencc-by-4.0May 2020View details →

Experimental data of the paper "Trial-based Heuristic Tree Search for MDPs with Factored Action Spaces"

This data set contains the code of our planner and of the planner that was used as baseline, the benchmark set that was used to perform experiments as well as the parsed values and basic reports that are reported in the paper. More information can be found in the README that is also included.

opencc-by-4.0Jan 2024View details →

Kuopio gait dataset: motion capture, inertial measurement and video-based sagittal-plane keypoint data from walking trials

This dataset contains motion capture (3D marker trajectories, ground reaction forces and moments), inertial measurement unit (wearable Movella Xsens MTw Awinda sensors on the pelvis, both thighs, both shanks, and both feet), and sagittal-plane video (anatomical keypoints identified with the OpenPose human pose estimation algorithm) data. The data is from 51 willing participants and collected in the HUMEA laboratory in the University of Eastern Finland, Kuopio, Finland, between 2022 and 2023. All trials were conducted barefoot. The file structure contains an Excel file containing information of the participants, data folders under each subject (numbered 01 to 51), and a MATLAB script. The Excel file has the following data for the participants: <ul> <li>ID: ID of the participants from 1 to 51</li> <li>Age: age of the participant in years</li> <li>Gender: biological sex as M for male, F for female</li> <li>Leg: the participant's dominant leg, identified by asking which foot the participant would use to kick a football; R for right, L for left</li> <li>Height: height of the participant in centimeters</li> <li>Invalid_trials: list of invalid trials in the motion capture data (MOCAP) data, usually classified as such because the participant did not properly step on the middle force plate</li> <li>IAD: inter-asis distance in millimeters, the distance between palpated left and right anterior superior iliac spine, measured with a caliper</li> <li>Left_knee_width: width of the left knee from medial epicondyle to lateral epicondyle in millimeters, palpated and measured with a caliper</li> <li>Right_knee_width: same as above for the right knee</li> <li>Left_ankle width: width of the left ankle from medial malleolus to lateral malleolus in millimeters, palpated and measured with a caliper</li> <li>Right_ankle_width: same as above for the right ankle</li> <li>Left_thigh_length: the distance between the greater trochanter of the left femur and the lateral epicondyle of the left femur in millimeters, palpated and measured with a measuring tape</li> <li>Right_thigh_length: same as above for the right thigh</li> <li>Left_shank_length: the distance between the medial epicondyle of the femur and the medial malleolus of the tibia in millimeters, palpated and measured with a measuring tape</li> <li>Right_shank_length: same as above for the right shank</li> <li>Mass: mass in kilograms, measured on a force plate just before the walking measurements</li> <li>ICD: inter-condylar distance of the knee of the dominant leg, measured from low-field MRI</li> <li>Left_knee_width_mocap: distance between reflective MOCAP markers on the medial and lateral epicondyles of the knee in millimeters, measured from a static standing trial; -1 for missing (subject did not have those markers)</li> <li>Right_knee_width_mocap: same as above for the right knee</li> </ul> The folders under each subject (folders numbered 01 to 51) are as follows: <ul> <li>imu: "Raw" inertial measurement unit (IMU) data files that can be read with Xsens Device API (included in Xsens MT Manager 4.6, which may be unavailable these days, not sure). You won't need this if you use the data in the imu_extracted folder.</li> <li>imu_extracted: IMU data extracted from those data files using the Xsens Device API, so you don't have to. <ul> <li>The data is saved as MATLAB structs where the fields are named as a sensor ID (e.g., "B42D48"). The sensor IDs and their corresponding IMU locations are as follows: <ul> <li>pelvis IMU: B42DA3</li> <li>right femur IMU: B42DA2</li> <li>left femur IMU: B42D4D</li> <li>right tibia IMU: B42DAE</li> <li>left tibia IMU: B42D53</li> <li>right foot IMU: B42D48</li> <li>left foot IMU: B42D51 (except for subjects 01 and 02, where left foot IMU has the ID B42D4E)</li> </ul> </li> <li>Some of the data are just zeros as they couldn't be read from these sensors, but under each sensor, the fields "calibratedAcceleration", "freeAcceleration", "time", "rotationMatrix", and "quaternion" contain usable data. <ul> <li>time: Contains time stamps of the measurement at each frame recorded at 100 Hz, so if you remove the first value from all values in the time vector and divide the result by 100, you will get the time in seconds from the beginning of the walking trial.</li> <li>calibratedAcceleration and freeAcceleration: Contain triaxial acceleration data from the accelerometers of the IMU. freeAcceleration is just calibratedAcceleration without the effect of Earth's gravitational acceleration.</li> <li>rotationMatrix: Orientations of the IMU as rotation matrices.</li> <li>quaternion: Orientations of the IMU as quaternions.</li> </ul> </li> </ul> </li> <li>openpose: Trajectories of the keypoints identified from sagittal plane video frames, saved as json files. <ul> <li>The keypoints are from the BODY_25 model of OpenPose (https://cmu-perceptual-computing-lab.github.io/openpose/web/html/doc/md_doc_02_output.html).</li> <li>Each frame in the video has its own json file.</li> <li>You can use the function in the script "OpenPose_to_keypoint_table.m" in the root folder to read the keypoint trajectories and confidences of all frames in a walking trial into MATLAB tables. The function takes as argument the path to the folder containing the json files of the walking trial.</li> </ul> </li> <li>Note that some subjects (11, 14, 37, 49) do not have keypoint and IMU data.</li> </ul> The folders under each subject are divided into three ZIP archives with 17 subjects each. The script "OpenPose_to_keypoint_table.m" is a MATLAB script for extracting keypoint trajectories and confidences from JSON files into tables in MATLAB. Publication in Data in Brief: <a href="https://doi.org/10.1016/j.dib.2024.110841" target="_blank" rel="noopener">https://doi.org/10.1016/j.dib.2024.110841</a> Contact: Jere Lavikainen, jere.lavikainen@uef.fi

Data from 18 fungicide trials on potato late blight in UK and Ireland 2013-2017

The data set comprises records of disease incidence, crop growth stage and yield from untreated and treated plots. The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file. The field trials were conducted by Corteva Agriscience, Germany.

Data from 168 fungicide trials in wheat fields across Europe 2014-2018

Data from 56 fungicide trials in wheat fields across Europe 2017-2019

The data set comprises records of disease incidence and yield from untreated and treated plots. The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file. The field trials were conducted by BASF, Germany.

Data from 89 fungicide trials on apple scab across Europe 2008-2018

The data set comprises records of disease incidence and yield from untreated and treated plots. Assessments The disease infection was expressed as the intensity of attack (=severity) and/or the frequency of attack. Two assessment methods were used: 1.    Visual assessment: •    P%INF: intensity of attack was obtained as a visual estimation of the percentage of each plant part (leaves or fruits) affected by disease •    P%FREQ: frequency of attack was represented by the number of infected leaves or fruits. The frequency is expressed as a percentage of the number sampled. 2.    Class assessment The level of the attack (intensity and frequency) was evaluated and calculated by classing plants into different severity categories ranging from no disease to severe attack. •    BEFHKT: frequency of disease attack expressed as a percentage, considering 4 damage classes •    BEFWER: intensity of attack expressed as a percentage, considering 4 damage classes. BEFHKT = 100*(cl2 + cl3 + cl4)/(cl1 + cl2 + cl3 + cl4) BEFWER = 100*(cl2 + 2*cl3 + 3*cl4)/(3*N)  (the Townsend-Heuberger intensity of attck) Table of measures Measure        Description P%FREQ        Estimated frequency of attack % P%INF        Estimated severy of attack % %ANTK1        Class 1 (%) %ANTK2        Class 2 (%) %ANTK3        Class 3 (%) %ANTK4        Class 4 (%) BEFHKT        Frequency of attack BEFWER        Index of attack INFECT        Infection (F); Infestation (F) KR%ABB        Diseased (%) WIRKGR        Percent of untreated Data format and source The data is provided as both a tab-separated text file and a binary R data file. The R files provides code to read and plot the data. The plot produced is also provided as a PNG file. The field trials were conducted by BASF, Germany.

opencc-by-4.0Sep 2022View details →

Data from randomized control trials released hatchery salmon treated with anti-parasitic treatment

Data used in the article "Parasite spillback from fish farms reduce return rate of wild salmon"   Each release group has been used as a randomized control trials (RCT) of hatchery reared salmon smolts where half of the fish has been treated with an antiparasitic drug. Description of this method has been given in various other publications (Vollset et al. 2014, Vollset et al 2016, Skilbrei et al. 2013). The method involves rearing salmon eggs originating from the national Gene Bank to smolt size in hatchery facilities during one year, and then treating the salmon smolts with fish feed pellets coated with emamectin benzoate (SLICE®). These fish are then released into the river or transported in tanks or mobile net pens further out in the fjord before release. The fish are tagged with either coded-wire-tags (CWT; years 2000-2017) or Passive Integrated Transponders (PIT; 2015-2019) so that it is possible to identify them as they are recaptured or registered on an antenna upon their return as adults. In a few trials, another antiparasitic treatment (Substance EX) has been used, but in most cases the EB has been the only available treatment. Releases of hatchery reared salmon in freshwater have not been successful in this system, i.e. very few fish have returned from any group released in the river, lakes or estuary of Vosso. Since the release groups are also a part of a restoration effort of the Vosso salmon, some years fish have only been released in the fjord. There has been some variation in the release sites in the fjords, but for the purpose of this study we group the release groups in either group that has been released in the outer fjord (70-105 km from the river mouth) and the inner fjord (15-70 km from the river mouth), and freshwater (approx -10 to 15 km from the river mouth). The two most prevalent locations are at Manger (WGS84; 60.63918, 4.92149) and Arna (WGS84; 60.50812, 5.37777).   Sea lice surveillance   Sea lice surveillance on sea trout has been conducted at Herdla, the northern peninsula of the island Askøy (WGS84; 60.568972, 4.963010) since 2009. Here, trout have been caught using a trap net that has been developed specifically to capture and treat trout while minimizing sea lice loss during handling (Barlup et al. 2013). From an earlier study by Vollset et al. (2018), it has been shown that the lice numbers on sea trout on this site correlate with the infestation pressure of fish farms in the outer region of the fjord. This area is also one of the largest fish farm zones with coordinated production and fallowing in the outer fjord system where all the released salmon smolts must migrate (see Vollset et al. 2018). This is also the area where surface salinity layers permit salmon lice to overlap with out-migrating salmon smolts (Vollset et al. 2016).   The number of trout caught during the monitoring season has varied with weather conditions, sampling intensity, and number of traps operated. The way that trout are handled is described in more detail in Vollset et al. (2018), but in brief, the trap chambers are checked daily, and individual trout are transferred from the trap using a hand held dip net and are either euthanized and placed in zip-lock bag or transported in a large bucket with aerated water to land. Euthanized samples are kept cold and frozen when at land, and later thawed and counted in the lab, while live samples are counted after being sedated with half dose (0.05 g/L) of MS222 and then assessed for salmon lice in a high-contrast bucket using a headlamp by trained personnel. Since 2015 the sea lice surveillance at Herdla is also operated as a part of the Norwegian national sea lice monitoring program. We aimed to use a standardized time period from which to assess sea lice numbers on sea trout that can be representative of the lice infestation pressure from when the tagged hatchery salmon smolts are released. When counting sea lice on sea trout, the most observable lice are large chalimus and mobile stages, while recently attached copepods are more likely to be missed. Therefore, we use total lice counts on sea trout from Julian day 135 to 165 as an assessment of the infestation pressure the salmon smolts must experience. This corresponds to approximately 15 May to 15 of June, and is based on a study on progression rate of salmon smolts from hatchery smolt in this area (Vollset et al. 2016). To account for the fact that larger fish will attract more parasites, we use parasites per gram fish per individual and average data to get one index per year. This method is expected to provide a fair index of interannual variation of the infestation pressure.   Table 1 Description of column names in csv file <table> <tbody> <tr> <td>Name</td> <td>Description</td> </tr> <tr> <td>release_year</td> <td>Year of release as smolts</td> </tr> <tr> <td>release_place</td> <td>Name of release place location</td> </tr> <tr> <td>release_date</td> <td>Date of release as smolts</td> </tr> <tr> <td>Released</td> <td>Number of hatchery smolt released</td> </tr> <tr> <td>Recaptured</td> <td>Number of hatchery smolt recaptured as adults</td> </tr> <tr> <td>treat</td> <td>Treatment (either treatment or control)</td> </tr> <tr> <td>tag</td> <td>Tag type (either CWT or PIT)</td> </tr> <tr> <td>release_category</td> <td>Release place (either river, outer fjord or inner fjord)</td> </tr> <tr> <td>lpg</td> <td>Lice per gram fish on trout during surveillance from 15 of May to 15 of June the year of release</td> </tr> <tr> <td>pr</td> <td>Percent (%) recaptures as adults</td> </tr> </tbody> </table>

opencc-by-4.0Dec 2017View details →

Data and analysis supplement for: Functional imagery training versus motivational interviewing for weight loss: a randomised controlled trial of brief individual interventions for overweight and obesity.

This submission provides the data and code for analyses reported in our publication.

opencc-by-4.0Mar 2024View details →

Data and supplementary files of the publication: "What Goes Around Should Not Move Around: Immobilizing Microplastics as a New Approach for Analytical Ring Trials"

Accompanying materials for the publication: <a href="https://doi.org/10.1021/acs.est.4c09427">https://doi.org/10.1021/acs.est.4c09427</a>

opencc-by-4.0Dec 2022View details →

Witchcraft trials in the Czech lands: Data on persons, places, charges, punishments, and material substances

This is the most comprehensive digital dataset of witchcraft trials in the Czech lands since the earliest case in 1491 until as late as 1785. The dataset covers 257 cases. It records the year, the suspects' names, their sex, places of residence (including geographic coordinates), charges, results of the trial, places of interrogation (including geographic coordinates), and the material substances they were charged of using to perform magic. The dataset allows researchers to conduct systematic and quantitative research into early modern withcraft trials, crime and punishment, as well as the imagery of magic and evil-doing. It also allows to include the Czech lands in broader quantitative studies of European witchcraft trials on a large temporal and geographic scale. Five B.A. theses have been written at Masaryk University, Brno, Czech Republic on the basis of this dataset. The dataset does not cover all known trials. Based on data availability, we did our best to cover what was published and reasonably accessible, but we did not perform original archival research. Our very rough estimate is that up to 100 further specific witchcraft trials in the Czech lands could be identified in published material, and archival work could reveal further ca. 250-800 cases.

opencc-by-4.0Dec 2022View details →

Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial'

Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial' (trial registered at clinicaltrials.gov (<a href="https://clinicaltrials.gov/ct2/show/NCT04996654">NCT04996654</a>; date of registration: 11 July 2021), consisting of: (1) the original and complete data set for all primary outcomes ('Data_Primary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx'); (2) the original and complete data set for all secondary outcomes ('Data_Secondary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx'); (3) the original and complete data set for all other outcomes (i.e. baseline factors (demographic data, type of usual care interventions) and training heart rate; 'Data_Other-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx'); (4) folder including the raw and processed heart rate variability (HRV) and electroencephalography (EEG) data for all participants and measurements (HRV-and-EEG_raw-and-processed-data.zip); (5) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.

opencc-by-4.0Nov 2023View details →

Nordic trial reporting project: Raw data from EU Clinical Trials Registry (EUCTR) and ClinicalTrials.gov

Uploaded on behalf of the author team for the research project "Systematic evaluation of clinical trial reporting at medical universities and university hospitals in the Nordic countries".Raw data from EU Clinical Trials Registry (EUCTR) and ClinicalTrials.gov:EUCTR: We retrieved the latest dataset for the EU Trials Tracker of EUCTR trials on Nov 27, 2022, reflecting data from Nov 7, 2022 (1,2). We also used a custom web scraper that automatically extracts data from EUCTR country protocols and results sections (variables described in Appendix Table 2), developed by the EU Trials Tracker team (2). References:  1. Goldacre B, DeVito NJ, Heneghan C, Irving F, Bacon S, Fleminger J, Curtis H. Compliance with requirement to report results on the EU Clinical Trials Register: cohort study and web resource. BMJ. 2018 Sep 12;362:k3218. 2. EU Trials Tracker — Who's not sharing clinical trial results? [Internet]. [cited 2022 Aug 30]. Available from: http://eu.trialstracker.net/ClinicalTrials.gov: We downloaded the complete Aggregate Analysis of ClinicalTrials.gov dataset (AACT, http://aact.ctti-clinicaltrials.org/) on Nov 27, 2022, reflecting data from Nov 9, 2022. See our GitHub and preregistered protocol for more details: https://github.com/cathrineaxfors/nordic-trial-reporting https://osf.io/97qkv/

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Context-dependent multimodal behaviour in a coral reef fish: Stage 1 & 2 total duration and count data in behaviour trials

Animals are expected to respond flexibly to changing circumstances, with multimodal signalling providing potential plasticity in social interactions. Whilst numerous studies have documented context-dependent behavioural trade-offs in terrestrial species, far less work has considered such decision-making in fish, especially in natural conditions. Coral reef ecosystems host 25% of all known marine species, making them hotbeds of competition and predation. We conducted experiments with wild Ambon damselfish (Pomacentrus amboinensis) to investigate context-dependent responses to a conspecific intruder; specifically, how nest defence is influenced by an elevated predation risk. We found that nest-defending male Ambon damselfish responded aggressively to a conspecific intruder, spending less time sheltering and more time interacting, as well as signalling both visually and acoustically. In the presence of a model predator compared to a model herbivore, males spent less time interacting with the intruder, with a tendency towards reduced investment in visual displays compensated for by an increase in acoustic signalling instead. We therefore provide ecologically valid evidence that the context experienced by an individual can affect its behavioural responses and multimodal displays towards conspecific threats.

opencc-zeroMar 2024View details →

opencc-by-4.0Jan 2022View details →

IMU data from walking trials on a treadmill

This dataset contains inertial measurement unit data from 10 treadmill walking trials. The subject is of legal age and wore a total of 12 Xsens MTw Awinda IMUs. More details in our publication (https://doi.org/10.7717/peerj.15097). Includes a readme file with details.

opencc-by-4.0Jan 2022View details →

Data from Viroplant Belgium field trial 2018

This folder contains all relevant data and results of studying the impact of a bacteriophage-based plant protection product on natural bacterial communities as they occur on plants and root material from the EU Viroplant project at a field site in Belgium in 2018. The file contains 16S rRNA sequences and scripts for their analyses, identity tables of sequence variants, qPCR data, data on physicochemical soil characteristics and other information

opencc-by-4.0Jun 2022View details →

Human single-cell TCR data from irradiated sporozoite trial

This is the MiAIRR-compliant single-cell AIRR-seq data of the study "Clonal evolution and TCR specificity of the human TFH cell response to Plasmodium falciparum CSP" by Wahl et al., Sci Immunol 7:eabm9644 (2022). The study defines the clonal evolution and epitope specificity of the human cTFH cell response to Plasmodium falciparum CSP.