Find research datasets worth reusing

A robust method for the measurement of social reward in adult mice

Dataset contains four files. File 1. Harda_et_al._2022_all_data.xlsx All data used in the publication. Results of the social conditioned place preference test perofmed on adult female laboratory mice (strain: C57BL/6). File 2. Harda_et_al._2022_initial_pref_30_70%.xls All data contained in File 1, except for animals that showed initial preference for any of the contexts exceeding 70%. File 3. Harda_et_al._2022_initial_pref_30_70%_trimmed.xlsx Data contained in File 2, randomly trimmed to the same number of animals for each social context. Trimming was performed separately for each experimental group. Data were trimmed by custom R script (File 4). File 4. trimmer.R R script used to randomly trimm data to the same number of animals for each social context.

openother-openMar 2022View details →

The long and short of it: converting between maximum and minimum tarsus measurements in passerine birds

Data and R scripts relating to: Caravaggi A, Bayley S, Facey RJ, de la Hera I, Shewring M, Smith JA. (2022) The long and short of it: converting between maximum and minimum tarsus measurements in passerine birds. Ringing & Migration. doi: <a href="https://doi.org/10.1080/03078698.2022.2050937">10.1080/03078698.2022.2050937</a>

Companion for "Understanding Distributed Deep Learning Performance by Correlating HPC and Machine Learning Measurements"

This is the Companion Material for the paper “Understanding Distributed Deep Learning Performance by Correlating HPC and Machine Learning Measurements”, by Ana Luisa Veroneze Solórzano and Lucas Mello Schnorr. The manuscript was approved for publication in the <a href="https://www.isc-hpc.com/research-papers-2022.html">ISC High Performance 2022</a> for the Research Papers session. A public companion is also availabl in GitLab: <a href="https://gitlab.com/anaveroneze/isc2022-companion/">https://gitlab.com/anaveroneze/isc2022-companion</a>.

Dataset of the determination of the topographic spatial resolution of a confocal point sensor with a type ASG material measure

These original measurement data relate to the publication: J. Schaude, A. C. Gröschl, T. Hausotte: Effect of a Misidentified Centre of a Type ASG Material Measure on the Determined Topographic Spatial Resolution of an Optical Point Sensor, Metrology 2(1), p. 19-32, 2022, <a href="https://doi.org/10.3390/metrology2010002">https://doi.org/10.3390/metrology2010002</a>. Please refer to this open access publication for a detailed description of the measurement setup and procedure. All data are in ASCII-format. Each file contains four columns, where column one to three are the x, y, and z-coordinates of the positioning system and column four is the signal of the photodetector. Content of the folders 10_Plane: Axial probings on 18 points just outside the grooves. 20_Edges: Lateral probings from each point just outside the grooves in the direction of the roughly determined centre of the material measure. 30_PlaneArea: Repeated axial probing on a plane area near the material measure. 40_RadialMeasurement: Radial measurement of the material measure by lateral (radial) probings conducted on different heights (referring to the distance to the plane fitted to the measuring points of 10_Plane), and radii (referring to the centre of the circle fitted to the edges determined in 20_Edges). Each radial probing has its own data file, with the name of the data file being “radial_probing {radius in m} {height in m} {data and time of probing}.txt”. 50_LineMeasurement: Lateral probings conducted on different heights (referring to the distance to the plane fitted to the measuring points of 10_Plane), different lateral offsets (referring to the centre of the circle fitted to the edges determined in 20_Edges) and on two angles (on the groove (0°) and the adjacent top level (10°)). Please refer to sec. 5.2 of the aforementioned publication for a detailed description. Each lateral probing has its own data file, with the name of the file being “lateral probing {angle in °} {offset in m} {height in m} {data and time of probing}.txt”. Acknowledgement This project 20IND07 TracOptic has received funding from the EMPIR programme co-financed by the Participating States and from the European Union’s Horizon 2020 research and innovation programme. Funder name: European Metrology Programme for Innovation and Research (EMPIR); Funder ID: 10.13039/10001413

Home-based measurements of dystonia and choreoathetosis in cerebral palsy using smartphone-coupled inertial sensor technology and machine learning: A proof-of-concept study - dataset

Home-based measurements of dystonia in cerebral palsy using smartphone-coupled inertial sensor technology and machine learning: A proof-of-concept study   This project contains: - 1 main MATLAB script: MODYSathome_main.m - 12 MATLAB functions:     - function_calc_mean_recall_precision.m     - function_create_dataframes.m     - function_deep_learning.m     - function_determine_best_ML_model.m     - function_display_DL_results.m     - function_display_ML_results.m     - function_index_extremities.m     - function_machine_learning.m     - function_oversample.m     - function_partition_data.m     - function_pick_best_models.m     - function_prepare_DL_data.m Downloading the Matlab scripts  - Create a folder named 'MODYS' and create a subfolder named 'results'  - Download the zip file via <a href="https://zenodo.org/record/6379348">RehabAUmc/modys-at-home: v1.0 | Zenodo</a>  - Unzip the zip file in the path MODYS\ STEPS 1. Open MATLAB 2. In MATLAB, go to the 'HOME' tab and click on 'Set Path' 3. Click on 'Add Folder' and browse to MODYS/RehabAUmc-modys-at-home-86b14c3/functions 4. Click on 'Select Folder' and click on 'Save' 5. Click on 'Browse to folder' and browse to a patients' data in MODYS/data/PatientXXX, then click on 'Select Folder' 6. In the 'HOME' tab click on 'Open' and open MODYSathome.m in MODYS/RehabAUmc-modys-at-home-86b14c3 7. In the 'EDITOR' tab click on 'Run Section' to run the script 8. When the code has been run, the results are displayed in the Command Window and saved in MODYS/results/PatientXXX

opencc-by-4.0Dec 2021View details →

Supplementary material for 'In-situ full-field measurements for 3D printed polymers during mode I interface failure'

Additional raw data and correlation analysis output for 'In-situ full- field measurements for 3D printed polymers during mode I interface failure'. We provide the patterned images acquired by the stereo microscopic Correlated Solution system (tiff format) and the VIC3D analysis results (csv format) for one representative specimen with 0°- 0° stacking undergoing mode I interlayer failure.

Particulate matter concentrations (PM1, PM2.5, PM10) since 2009 for a measurement sites in Zagreb, Croatia

Daily samples of PM1, PM2.5 and PM10 fractions have been collected continuously during 12-years period (2009-2020) at Zagreb, Croatia (45°50’7’’ N, 15°58’42’’ E, 116 m a.s.l.,). A sampling site was located in the northern, residential part of city which was characterized by modest traffic and population density. The main sources during the household heating season which usually started in October and lasted until April were gas and/or wood. Mass concentrations of PM1, PM2.5 and PM10 fractions were determined gravimetrically, while meteorological parameters (temperature, RH, wind speed and direction, pressure, and precipitation) were obtained from the Croatian Meteorological and Hydrological Service.

Arecibo measurements of D-region electron densities during sunset and sunrise in August 2016

This dataset is connected to the manuscript 'Arecibo measurements of D-region electron densities during sunset and sunrise: implications for atmospheric composition' submitted to Annales Geophysicae. It contains Arecibo radar data between 28. August 2016 and 01.September 2016, specifically power profiles and plasma line measurements. The data files and associated Matlab reading routines can be found in the appropriate .zip files. The data repository contains also processed data for Fig.3 (afternoon/morning_final_data75.mat/plot_sunset_sunrise_comparison75.m) and Fig. 4(rate_data.mat/plotrate.m) and associated Matlab plotting routines.

VMM Noise Measurement Data

This release contains measured data to study the noise of VMM3a readout chips, which are intended to be used in the front-end readout system of a Triple-GEM detector. Their noise is characterised both in term of RMS output voltage and the equivalent noise charge (ENC). The dependence of the noise on a variety of operation parameters, including peaking time and gain factor, are also studied. The measurements have been performed by Emorfili Terzimpasoglou as part of her Master Thesis ”Investigation on the ASIC for Triple-GEM Detectors” at the University of Bonn.

Data used for the article "Hybrid intrahour DNI forecast model based on DNI measurements and sky-imaging data"

Data used to obtain the results presented in the article "Hybrid intrahour DNI forecast model based on DNI measurements and sky-imaging data". <ul> <li>CNRS_PROMES_DNI_2020-09-03_2021-01-11.zip : contains DNI measurements taken at PROMES-CNRS laboratory in Odeillo.</li> <li>The other zipped files contain image data taken at PROMES-CNRS laboratory in Odeillo. Each zipped file contains all images for one day (the date is given in the file name).</li> </ul> Images and GHI measures from the following days have been used for training and cross-validation: <ol> <li>2020-09-11</li> <li>2020-09-12</li> <li>2020-09-16</li> <li>2020-09-19</li> <li>2020-09-20</li> <li>2020-09-21</li> <li>2020-09-22</li> <li>2020-09-23</li> <li>2020-09-24</li> <li>2020-09-29</li> <li>2020-10-01</li> </ol> Images and GHI measures from the following days have been used for test: <ol> <li>2020-10-04</li> <li>2020-10-05</li> <li>2020-10-08</li> <li>2020-11-05</li> <li>2020-11-15</li> </ol>

Dataset - Desiccation-rehydration measurements in bryophytes: current status and future insights

This dataset is related to "Desiccation-rehydration measurements in bryophytes: current status and future insights" (Morales-Sánchez JA, Mark K, Silva-Souza JP, Niinemets Ü, 2022)

opencc-by-4.0Jun 2022View details →

FlavoriaFoodWeight1700: Automated Lunch Line Meal Pictures with Automatic Measurement of Weight and Contents

A dataset of around 2000 pictures consisting of both pictures taken on a lunch line and their measured contents based on the lunch line's automation systems. The pictures were automatically taken and linked to data via RFID tags on each meal tray. The pictures are linkable to CSV meal contents. CSV includes explanatory headers.

Dataset for pupil response measurements for trustworthiness

Data file name: trustpupil.csv  Data labels photo_num =stimulus number 1–81 age (participants’ age) deception: 0–24 (deception score) Flanders: -10–10 (handedness score) Side: l or r (posing direction) trust_iris: iris diameter of trustworthy face in pixel trust_pupil: pupil diameter of trustworthy face in pixel neutral_iris: iris diameter of neutral face in pixel neutral_pupil: pupil diameter of neutral face in pixel    "-" stands for "unmeasured" reason: reason for unmeasurement

UAV outputs and associated field measurement of the herbaceous of a Sahelian Rangeland during the wet season in Northern Senegal

This dataset contains UAV outputs (mosaic and digital surface model) and field measurement of vegetation (shapefile) that were made in northern Senegal. Site gradient measurement The data was collected on a plot of the Centre of Zootechnical Researches of Dahra / ISRA during 2020 rainy season (from July 19, 2020, to September 17, 2020). The average rainfall for the period 1981-2018 was ranging from 221 mm.y-1 to 468 mm. y-1. The vegetation in the field is a herbaceous savannah where Vachellia tortilis and Balanites aegyptiaca are the dominant trees. Field measurement. UAV flight plan We used two different drones : Bluegrass and Anafi of Parrot. The Bluegrass of Parrot was used from 19/07/2020 to 04/08/2020. The Bluegrass flights were done at 60 meters of altitude, with a speed of 2 m s-1, and 90% of overlap rate between images, on a double grid of 100 m x 100 m. Anafi of Parrot was used for the rest of the season. The Anafi flights were done at 60 meters of altitude, with a speed of 2 m s-1, and 90% of overlap rate between images, on a double grid of 100 m x 100 m and the angle of inclination of the camera fixed at 80°. The flights have been done with PIX4D capture application at earlier in the day every two days. A total of 61 drone flights were conducted over the rainy season. Herbaceous Biomass Every two days , after drone flight, herbaceous measurements were carried out, in three plots of 1 m² distributed respectively under the crown of a tree, at the edge of the crown, and at a distance from the edge of the crown equal to the height of the tree. These plots were rotated among the trees in the field until all four azimuths of trees were covered.We collected Fresh mass and dry mass. Image analysis. The drone images taken for each day of collect, were analyzed in the software PIX4DMapper (Pix4D SA, Lausanne, Switzerland) by the Structure from Motion method. We used precisely the 3D mapping option of the software. Then for each flight we computed and exported an orthophotograph and a digital surface model. Data organization The data contains : <ul> <li>DSM that contains the surface model in tiff</li> <li>Mosaic that the orthomosaic in tiff.</li> <li>Data that contains the shapefile with the position and table with the field measurements</li> </ul>

Interactive Causal Structure Discovery with Hyytiälä measurements (experiment code and data)

This archive contains code and data required to reproduce the results presented in the following two papers. Interactive Causal Structure Discovery in Earth System Sciences published in Proceedings of The KDD'21 Workshop on Causal Discovery, 2021. Technical note: incorporating expert domain knowledge into causal structure discovery workflows published in Biogeosciences, 2022 The archive contains a README markdown document detailing the contents and how to run the experiments.

MEASUREMENTS AND CONTROLS ON MID-WINTER ALPINE GROUND THERMAL REGIME IN THE PURCELL MOUNTAINS, BRITISH COLUMBIA [Dataset]

Datasets and coding from my MSc Thesis titled MEASUREMENTS AND CONTROLS ON MID-WINTER ALPINE GROUND THERMAL REGIME IN THE PURCELL MOUNTAINS, BRITISH COLUMBIA.  Data includes shallow ground, surface, and basal snow temperatures from 29 alpine ground thermal regime monitoring sites and meteorological data from one station located at Conrad Glacier basin in the Purcell Mountains, BC. Data were collected from August 2020 to August 2021.

opencc-by-4.0Feb 2022View details →

Development and implementation of a tool for measuring the training effectiveness of the patient-centered consultation model

Background: The patient-centered consultation model comprises four elements: exploring health, illness, and disease experiences, understanding the whole person, finding common ground, and enhancing the patient-doctor relationship. This method is taught at the course in general practice at Copenhagen University. The aim of the study was to develop a simple tool consisting of a questionnaire about the patient-centered elements and a test video consultation. The outcome is the change in the students’ ability to identify these elements. Used as a pre-course and post-course test it can inform the teachers which elements of the patient-centered consultation need intensifying in the teaching. Methods: The students from a course in general practice volunteered to participate in all steps of the development. They took part in individual interviews to select items from an already existing questionnaire (DanSCORE). The preliminary questionnaire was tested for face and content validity, pilot-tested and tested for test-retest reliability. All video consultations were transcribed and assessed for patient-centered elements through a conversation analysis. The videos showed medical students seeing real patients. Results: The preliminary version of the questionnaire (called DanOBS) <a href="#_msocom_1">[CM1]</a> <a href="#_msocom_2">[MJ2]</a> had 23 items. In the subsequent interviews, items were reduced to 17, each with three response options. After the pilot test, the questionnaire was further reduced to 13 items, all strictly relevant to the model and with two response options. The final questionnaire had acceptable test-retest reliability. The number of test consultation videos underwent a reduction from six videos to one. Conclusions: The DanOBS combined with a test video consultation, used as a pre-and post-course test demonstrates for teachers which elements in the patient-centered consultation need to be intensified in the teaching.

CROSSBOW HLU2-UC1-TC1 measurements: Substation measurements gathered during curtailment activation. Second test

. Capture on 21/04/2022 The data comprises the 2 sec measurements from HOPS SCADA system for for the Konjsko substation before, during and after a curtailment in Pometeno Brno plant (21:00 - 22:30 on 21/04/2022). The measurements gathered from the SCADA are: <ul> <li>P, Q and V of the 110, 220 and 400 Kv buses at the substation</li> </ul> P, Q and V of the line connecting the substation with the plant

opencc-by-4.0May 2022View details →

How green is my valley? Measuring open access friendliness of Indian Institutes of Technology (IITs) through data carpentry (dataset)

This data set is related to the book chapter with the following bibliographic details - Mukhopadhyay, P. (2022). How green is my valley? Measuring open access friendliness of Indian Institutes of Technology (IITs) through data carpentry. In A. Biswas & M. Das Biswas (Eds.), Panorama of open access: Progress, practices & prospects (1st ed., pp. 67–89). Ess Ess. https://doi.org/10.5281/zenodo.6511080. It includes the truncated version of the final data set that has been used for analyzing Open Access Friendliness (OAF) of the Indian Institutes of Technology (IITs). The zipped version of the data set is around 95 MB (465 MB after decompress).