Find research datasets worth reusing

The agrofood systems in France, Spain and Portugal at a NUT2 resolution for the 2014-2019 period (GRAFS Data set)

The GRAFS approach (Generalized Representation of Agro-food systems) describes the agro-food system by considering four main components exchanging nutrient flows: cropland, grassland, livestock systems, and local population. The agro-food system is documented here for the period 2014–2019, at the territorial level of the EU administrative units NUTS2, in terms of N for (i) nutrient inputs to the soil (exogenous fertilization such as synthetic and/or organic fertilization and atmospheric deposition, as well as symbiotic fixation); (ii) the feed required for the existing livestock; (iii) the size of the human population, its dietary preferences, and its excreta; and (iv) food and feed imports/exports (Billen et al., 2018; 2021). These N flows link grassland and cropland productivity (from annual and perennial crops) to livestock feeding, and, finally, to human food. Detailed figures for these different components are presented in the joint Table. Using the GRAFS approach to our study area, we also expand upon the approach used by Le Noë et al. (2018), which established different typologies of the agro-food systems in France. This approach intends to describe the degree of coupling between crop and livestock farming, local production/consumption to shows regional differences (see Table 1SM for a detailed description of the different typologies defined). The GRAFS approach also allows to calculates, NH3 volatisization and N2O emission, as well as leaching concentration (the net soil surplus as a proxy).

Data Set from the DMP survey and interviews - intermediate results

This is the data set for a series of interviews in chemistry on data management (plans) and presents interim results. A more detailed analysis and description can be found in the paper "Road to a Chemistry-specific Data Management Plan" submitted to Data Science Journal (2022-12-15). The interview series will continue in 2023 and final results will be published later in 2023. The aim of the conducted interview series is the enrichment of the online survey data from the RDA WG Discipline-specific Guidance for DMP and in a second step the development of a chemistry-specific data management plan template. For this purpose, the current status of data management as well as information about the workflows in the various chemical disciplines were requested in a personal interview with 22 participants so far. All the gathered information and examples will be used to develop a DMP template or guide in line with chemistry-specific requirements. The results provide a comprehensive outlook on the future developments of RDM in chemistry. Possible strategies for implementation are also discussed.

opencc-by-4.0May 2022View details →

Data-set of the partial pressure of CO2, dissolved concentrations of CH4, N2O, NO3-, NO2- and NH4+, specific conductivity and water temperature in the rivers and streams of the Napo River basin in Ecuador (2018, 2019, 2020, 2021)

Data-set consists of two files: - data_ghgs.xlsx : Time-stamped and georeferenced data-set of the partial pressure of CO2 (pCO2 in ppm), dissolved CH4 concentration (CH4 in nmol/L), dissolved N2O concentration (N2O in nmol/L), specific (Sp.) conductivity (in µS/cm), water temperature (in °C), dissolved nitrate concentration (NO3- in µmol/L), dissolved nitrite concentration (NO2- in µmol/L), and dissolved ammonia concentration (NH4+ in µmol/L) in the rivers and streams of the Napo River basin in Ecuador (October 2018 and 2019, January 2019 and 2020, April 2019 and 2021, July 2019 and 2020). Gas measurements were made by headspace equilibration directly in the field with a infra-red gas analyser for CO2 and in the lab with a gas chromatograph for CH4 and N2O. NO3-, NO2- and NH4+ were measured with standard colometric procedures. Sampling and analytical protocols are provided here <a href="https://doi.org/10.5194/bg-16-3801-2019">https://doi.org/10.5194/bg-16-3801-2019</a> - RiverATLAS.xlsx: hydro-environmental data for the sampled streams extracted from RiverATLAS (https://www.nature.com/articles/s41597-019-0300-6). Data codes and units are available here: https://data.hydrosheds.org/file/technical-documentation/HydroATLAS_TechDoc_v10_1.pdf First column of each of the two files provides station ID allowing to merge both data-sets.

MEG data during the presentation of Gabor patterns and word sets

Subjects MEG was recorded in 7 healthy subjects (5 young right-handed and 1 left-handed and 1 elderly) in the waking state with their eyes open or closed, who were sitting in a comfortable chair. The experimental technique was approved by the ethical commission of the Institute of Higher Nervous Activity and Neurophysiology of RAS (protocol No. 5 dated 02.12.2020). Equipment MEG was recorded on a VectorView device (Elekta Neuromag Oy, Finland), which was placed inside a magnetically protected chamber made of multilayer permalloy (AK3b, Vacuumschmelze GmbH, Germany). Before MEG recording, the coordinates of anatomical reference points (left and right preauricular points and nasion) were determined, as well as indicator coils attached to the surface of the scalp of the subject in the upper part of the forehead and behind the auricles. These points were determined using a FASTRAK 3D digitizer (Polhemus, USA). Each subject had a virtual model of the brain and head obtained from an anatomical 3D MRI taken the day before (file: MRI_V1_7.zip). Registration and pre-processing The subject's head was covered by a helmet, which is part of a fiberglass Dewar vessel with an array of sensors immersed in liquid helium. The subject sat down in such a way that the surface of the head was as close as possible to the sensors. The magnetic signal was recorded from 102 triplets, each of which consisted of 1 magnetometer and 2 gradiometers at rest with eyes closed and upon presentation of visual and speech stimuli. Recording was performed with a sampling frequency of 1000 Hz in a bandwidth of 0.1–330 Hz and was processed by the MaxFilter program (Elekta Neuromag Oy, Finland), which eliminates artifacts (the tSSS method—spatio-temporal separation of signals). The signal levels were corrected in accordance with the data on the position of the subject's head in relation to the MEG sensors. The position of the head during the experiment was controlled using special inductors. Visual and verbal stimuli After recording the background MEG for 3 minutes with closed eyes, the subject opened his eyes on command and observed the fixation point on the projection screen. After 15 seconds, stimulation was started and the subject's responses were received in the form of pressing a button. In response to the 0 degrees and 90 degrees stimuli, the subject had to press the button with the index finger, and to the 45 degrees and 135 degrees inclined stimuli, the adjacent button with the middle finger. Stimuli lasting 100 ms were presented randomly every 3100±100 ms (intervals between stimuli varied randomly). In two series, 42 stimuli of each orientation were presented. Between the series, the subject rested for 2-3 minutes.  Visual stimuli in the form of Gabor contrast gratings (1.9 cycles per angular degree) with dimensions of 5.25 angular degrees and an average brightness of 4 lux were projected onto a screen located at a distance of 95 cm from the subject's eyes using a Panasonic PT-stimulating projector D7700E-K, which is part of the MEG facility. Visual stimulus patterns were generated at http://www.cogsci.nl/pages/gabor-generator with edge parameters: Circular (sharp edge). The samples are contained in the GaborStim.zip file (the names of the sample files correspond to their name in the script file, but do not match their geometric meaning, see table below). The stimulator was programmed using the Presentation software (USA, Neurobehavioral Systems, Inc). Stimulation scripts are contained in the sce.zip file. Table Stimulus or response code Type of stimulus or response STI101_1                          Fixation point STI101_2                           90 degrees STI101_4                         135 degrees STI101_8                             0 degrees STI101_16                         45 degrees STI101_32                       First button (index finger) STI101_64                       Second button (middle finger) After 2 series of visual stimuli, the subject closed his eyes and was presented with 3 series of speech stimuli for 2 minutes with a break of 1 minute. In each series, recordings of audio files of 8 separate adjectives of the Russian language were presented, which were repeated 5 times in a pseudo-random order. The series began with 3 words, which were not taken into account in further analysis. The subject listened to the words and had to press the button after he understood the meaning of the presented word. After pressing or no response, the next word followed in 2±1 s. The audio files are contained in the words101_343.zip file (the names correspond to the script file). Data received The records are contained in files with the name of the type V1m24r, where V1 is the number of the subject, m is the sex (m/f), 24 is the age, and r is the right-handed subject. This dataset can be easily loaded into the Brainstorm program. Spontaneous and evoked MEG can be used for source localization and reconstruction of traveling waves. Acknowledgments The reported study was funded by RFBR, project number 20-015-00475.

DEMIX 10k Tile Data Set

This dataset of tiles, nominally 10x10 km in size on a geographic grid, supports the work of the Digital Elevation Model Intercomparison eXperiment (DEMIX) working group (Strobl and others, 2021; Guth and others, 2021; ; Bielski and others, work in progress).  This data set provides a technical description, naming convention, and GIS data sets in shapefile and geopackage formats. The tiles have a constant latitudinal spacing of 6 arc minutes, and increase the longitudinal spacing toward the poles to approximate a constant area for the tiles. The DEMIX tile system provides a global tessellation at a scale fine enough to produce locally significant results, coarse enough to keep the total number of tiles manageable, and equal enough in size to allow for statistical aggregation and comparative analysis.   To understand the use of the database, see the preprint (Bielski and others, 2023). References: Bielski, C.; López-Vázquez, C.; Guth. P.L.; Grohmann, C.H. and the TMSG DEMIX Working Group, 2023. DEMIX Wine Contest Method Ranks ALOS AW3D30, COPDEM, and FABDEM as Top 1” Global DEMs: <a href="https://arxiv.org/pdf/2302.08425.pdf"> https://arxiv.org/pdf/2302.08425.pdf</a> Guth, P.L.; Van Niekerk, A.; Grohmann, C.H.; Muller, J.-P.; Hawker, L.; Florinsky, I.V.; Gesch, D.; Reuter, H.I.; Herrera-Cruz, V.; Riazanoff, S.; López-Vázquez, C.; Carabajal, C.C.; Albinet, C.; Strobl, P. Digital Elevation Models: Terminology and Definitions. Remote Sens. 2021, 13, 3581. <a href="https://doi.org/10.3390/rs13183581">https://doi.org/10.3390/rs13183581</a> Strobl, P.A.; Bielski, C.; Guth, P.L.; Grohmann, C.H.; Muller, J.P.; López-Vázquez, C.; Gesch, D.B.; Amatulli, G.; Riazanoff, S.; Carabajal, C. The Digital Elevation Model Intercomparison eXperiment DEMIX, a community based approach at global DEM benchmarking. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2021, XLIII-B4-2021, 395–400. <a href="https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-395-2021">https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-395-2021</a>

Data Set for Sandanbata et al. (2023: GRL) entitled "Two volcanic tsunami events caused by trapdoor faulting at a submerged caldera near Curtis and Cheeseman Islands in the Kermadec Arc"

Descriptions This dataset contains supplementary materials for the manuscript under revision for Geophysical Research Letters; the preprint has been uploaded to ESS Open Archive: <ul> <li>Sandanbata, O., Watada, S., Satake, K., Kanamori, H., & Rivera, L. (2023). Two volcanic tsunami events caused by trapdoor faulting at a submerged caldera near Curtis and Cheeseman Islands in the Kermadec Arc. Geophysical Research Letters, 50, e2022GL101086. <a href="https://doi.org/10.1029/2022GL101086">https://doi.org/10.1029/2022GL101086</a></li> </ul> We constructed a source model for the 2017 earthquake at Curtis caldera in the Kermadec Arc. The dislocation distributions and source geometries of this source model, presented in Figure 3, are contained in this dataset.

Data set for publication Sikora P., Techman M., Federowicz K., El-Khayatt A.M., Saudi H.A., Abd Elrahman M., Hoffmann M., Stephan D., Chung S.-Y. Insight into the microstructural and durability characteristics of 3D printed concrete: Cast versus printed specimens. Case Studies in Construction Materials (2022), 17, e01320.

Open dataset for publication Sikora P., Techman M., Federowicz K., El-Khayatt A.M., Saudi H.A., Abd Elrahman M., Hoffmann M., Stephan D., Chung S.-Y. Insight into the microstructural and durability characteristics of 3D printed concrete: Cast versus printed specimens. Case Studies in Construction Materials (2022), 17, e01320. <a href="https://doi.org/10.1016/j.cscm.2022.e01320">https://doi.org/10.1016/j.cscm.2022.e01320</a> File 1 - Mechanical characteristics - *.opju (Origin) File 2 - Particle size distributions of used materials - *.opju (Origin) File 3 - Sorptivity measurement data - *.opju (Origin) File 4 - G-code for printing of 1 layered specimen - *txt File 5 - G-code for printing of 3 layered specimens - *txt

Data set: historical and ethno-linguistic maps covering Western Tigray (1607-2014)

Excerpts of 142 co-eval historical and ethno-linguistic maps covering Western Tigray (Ethiopia). Original data, used to prepare the article Nyssen, J., Biadgilgn Demissie, 2023. Administrative and ethno-linguistic boundaries of Western Tigray (Ethiopia) since 1683. Journal of Maps.

Data set. Optical properties. J-aggregate:PVA polaritonic films.

Optical properties (real and imaginary part of permittivity) of J-aggregate:PVA materials analysed in manuscript entitled "Bio-inspired building blocks for all-organic metamaterials from visible to near-infrared".  arXiv preprint arXiv:2210.02315

Poses of People in Art: A Data Set for Human Pose Estimation in Digital Art History

Throughout the history of art, the pose—as the holistic abstraction of the human body's expression—has proven to be a constant in numerous studies. However, due to the enormous amount of data that so far had to be processed by hand, its crucial role to the formulaic recapitulation of art-historical motifs since antiquity could only be highlighted selectively. This is true even for the now automated estimation of human poses, as domain-specific, sufficiently large data sets required for training computational models are either not publicly available or not indexed at a fine enough granularity. With the Poses of People in Art data set, we introduce the first openly licensed data set for estimating human poses in art and validating human pose estimators. It consists of 2,454 images from 22 art-historical depiction styles, including those that have increasingly turned away from lifelike representations of the body since the 19th century. A total of 10,749 human figures are precisely enclosed by rectangular bounding boxes, with a maximum of four per image labeled by up to 17 keypoints; among these are mainly joints such as elbows and knees. For machine learning purposes, the data set is divided into three subsets—training, validation, and testing—, that follow the established JSON-based Microsoft COCO format, respectively. Each image annotation, in addition to mandatory fields, provides metadata from the art-historical online encyclopedia WikiArt.

Data Set on the Literature Screening for a Scoping Review of Evacuation Training Methods in Buildings

This data set contains all retrieved literature records of a scoping review on fire evacuation training methods in buildings together with the reasoning for their in- or exclusion in the review.

opencc-by-4.0Aug 2022View details →

Data Set: Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation

This is the Python code and plotted figure data used to create the figures for the submitted manuscript, "Single-well pore pressure preconditioning for Enhanced Geothermal System stimulation" submitted to JGR: Solid Earth in 2022. The manuscript concerns a novel technique developed for EGS stimulation, called pore pressure or effective normal stress preconditioning, which preemptively alters the stress field along a fault prior to injection, such that the risk of induced seismicity is reduced. Using a slightly altered version of a preexisting model (a combination of an analytical pore pressure model and a linear slip weakening seismicity model) the effect of this kind of treatment is evaluated.

opencc-by-4.0May 2022View details →

Data set for paper "Spatial Mobility Capital: A Valuable Resource for the Social Mobility of Border-Crossing Migrant Entrepreneurs?"

Data set for paper "Spatial Mobility Capital: A Valuable Resource for the Social Mobility of Border-Crossing Migrant Entrepreneurs?"

Data set for article "Migrant Entrepreneurs as Agents of Development? Geopolitical Context and Transmobility Strategies of Colombian Migrants Returning from Venezuela"

Data set for paper "Migrant Entrepreneurs as Agents of Development? Geopolitical Context and Transmobility Strategies of Colombian Migrants Returning from Venezuela"

Data set for "On the interplay between lipids and asymmetric dynamics of an NBS degenerate ABC transporter"

Supplementary data from molecular dynamics simulations performed on different states of bMRP1 (IF apo, IF ATP- and/or LTX-bound, as well as OF ATP-bound states) and embedded in different lipid bilayer membranes (namely POPC, POPE, POPC:POPE (3:1), POPC-Chol (3:1) and POPC:POPE:Chol (2:1:1). Are included: - Initial and postMD data - MD inputs used - Raw source data used for plot (ABC structural parameters, H-bond and non-covalent analyses, lipid order parameters, and efficiencies from Allopath tool) - PCA supplementary movies (PC1)

Experimental Electrical Impedance Tomography Data Set Using the Spectra Bioimpedance and EIT Complete Kit

Abstract The amount of open-source EIT measurement data is low. This data set concerns the acquisition and processing of different measurement data using the SpectraEIT-Kit as well as information about the deposited files. Aknoelegenment Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1270/2 - 299150580.

Validation of STS Conceptual Model Designing Approach. DMI374 and DMI747 Data Sets.

Surveys of DMI374 and DMI747 student groups were conducted for the purpose of validating the STS conceptual model designing method. A 5-point and dichotomous Likert questionnaire was used for the survey. The files contain response datasets used in statistical processing.

Imaging data-set of mitochondrial Zink Finger localisation in mammalian cells

This repository contains all raw and saved images for experiments with mitochondrial ZincFingers or mtZincFinger-Fluorophores conducted by Timo Rey during 2021 and 2022 at the MRC Mitochondrial Biology Unit without curation (unfiltered). A more detailed description with a selection of representative images and proposed conclusions will follow eventually File-titles should be explicable of cell line and over-expressed plasmid constructs and/or antibodies used. Please refer to the accompanying excel sheet as well as all available plasmid maps for further detail and do not hesitate to enquire by contacting Timo Rey via e-mail, if further clarifications are needed. All images were acquired on an LSM880 Confocal Microscope, except for those on June 2, 2022, which were acquired on an Andro DragonFly Spinning Disk. Have a look and draw your own conclusions!

Changing intensity of hydroclimatic extreme events revealed by GRACE and GRACE-FO Data sets

Updated 2 February 2023. This archive contains the key data files (including figure data) associated with: Rodell, M., and B. Li, 2023: Changing intensity of hydroclimatic extreme events revealed by GRACE and GRACE-FO, Nature Water, accepted. Figure1_time_series_data.xlsx – Data used to create the 14 inset time series plots in Figure 1. fig1_extents.zip – Contains spatial data used to create the "Top wet events" and "Top dry events" maps in Figure 1, in both text and NetCDF formats. Figure2_data.xlsx – Time series data used to create Figure 2. Figure3a_Koeppen-Geiger-ASCII.zip - Contains a text data file of spatial data (latitude, longitude, class) used to create the climate class map in Figure 1.  Note that only the main climates (first letter of class code) are used: A = Tropical, B = Dry, C = Temperate, D = Continental, E = Polar (no data).  See http://koeppen-geiger.vu-wien.ac.at/present.htm for details. Figure3bc_data.xlsx – Time series data used to create Figures 3b and 3c. Figure4_data.xlsx – Location, year, and intensity data used to create the maps in Figure 4. all_event_intensity.xlsx - Contains the centroid location (longitude and latitude), year, and intensity (km3mo) of all 505 wet extreme events and 551 dry extreme events identified and analyzed in this study. Source data and code used in this study are available as follows. Data Availability The GRACE/FO products (CSR GRACE/GRACE-FO RL06 Mascon Solutions, version 02) used in our analyses are available from the University of Texas Center for Space Research (https://www2.csr.utexas.edu/grace/RL06_mascons.html).  The output from a global GRACE/FO data assimilating instance of the Catchment land surface model (GRACEDADM_CLSM025GL_7D 3.0) used to fill the 11-month gap between the GRACE and GRACE-FO missions and 18 additional missing months is available from the Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/GRACEDADM_CLSM025GL_7D_3.0/).  The climate oscillation indicator data can be downloaded from the NOAA Physical Sciences Laboratory (https://psl.noaa.gov/data/climateindices/list/ and https://psl.noaa.gov/gcos_wgsp/Timeseries/DMI/).  The global mean temperature data are available from the NASA Goddard Institute for Space Studies (https://data.giss.nasa.gov/gistemp/).    Köppen-Geiger climate map data are available for download from http://koeppen-geiger.vu-wien.ac.at/present.htm. Code Availability The python code for the ST-DBSCAN clustering algorithm was obtained from the Github repository, https://github.com/gitAtila/ST-DBSCAN.  Statistical analyses were performed and figures were generated using NCL software.