Find research datasets worth reusing

opencc-by-4.0Jul 2022View details →

RobotReviewer evaluation data (new test set)

Includes 3,324 openly available PDFs (rct_pdfs.zip) with risk-of-bias annotations (robotreviewer_eval_data.json) from Cochrane systematic reviews. This data has not been used in the development of RobotReviewer and in this way represents a new, unseen test set. For each PDF/pubmed ID, Cochrane topics are also provided (robotreviewer_topics.json).

opencc-by-4.0Dec 2022View details →

Data Set : Seismic Wave Propagation Simulations in Indo Gangetic Basin using Spectral Element Method

Indo Gangetic (IG) basin is one of the largest alluvial basins in the world.  The surrounding Himalayan topography and  the geometry of the basin make the IG basin unique. The analysis of seismic response of the basin is important as the region is seismically active with more than 40% of Indian population residing in it. This online database consists of  the input files for performing the spectral finite element simulation for IG basin by incorporating the 3D variation of material properties and basin geometry. The input files consists of mesher, solver and CMTSOLUTION files for SPECFEM3D Cartesian (Version-3) simulation.

opencc-by-4.0Jul 2022View details →

PowerDuck: A GOOSE Data Set of Cyberattacks in Substations

A recorded GOOSE data set as described in  Sven Zemanek, Immanuel Hacker, Konrad Wolsing, Eric Wagner, Martin Henze, and Martin Serror. 2022. PowerDuck: A GOOSE Data Set of Cyberattacks in Substations. In Cyber Security Experimentation and Test Workshop (CSET ’22), August 8, 2022, Virtual, CA, USA. ACM, New York, NY, USA, 5 pages. https://doi.org/10.1145/3546096.3546102 The data set contains network traces of GOOSE communication recorded in a physical substation testbed. Further, it includes recordings of various scenarios with and without the presence of attacks. All network packets originating from the attacker are clearly labeled as such to facilitate their identification using the Industrial Protocol Abstraction Layer (IPAL) format. We thus envision PowerDuck improving and complementing existing data sets of substations, which are often generated synthetically, and thus aim to enhance the security of power grids.

opencc-by-4.0Aug 2022View details →

Data set with length measurments of niches in Chachabamba

For the metrological analysis, this type of data was obtained from a 3D point cloud and all measurements for Chachabamba architectural remains were collected in two data sets.The first group belongs to the central part of the sanctuary, called sector A, and consists of 39 measurements. The second group of measurements was collected from the water fountains located in the four corners of sector A, where 31 measurements were collected.

opencc-by-4.0Aug 2022View details →

The thermal state of Volgo–Uralia from Bayesian inversion of surface heat flow and temperature [data set]

This collection contains the dataset and the code which were used to find the thermal parameters’ lateral variations of the Volgo–Uralian subcraton through the Bayesian Markov Chain Monte Carlo (MCMC) statistical approach. The code originally was given in the analogous study of Antarctica's geothermal structure by Lösing et al. (2020) and it can be found in https://github.com/MareenLoesing/GHF-Antarctica-Bayesian. The main changes to the code of Lösing et al. (2020) are listed in the section 2 of the readme file. For an official use of the Bayesian inversion code please also cite: Lösing, M., Ebbing, J. & Szwillus, W. (2020) Geothermal Heat Flux in Antarctica: Assessing Models and Observations by Bayesian Inversion. Front. Earth Sci., 8, 105. doi:10.3389/feart.2020.00105 The lateral variations of the thermal parameters for the single-layer and multi-layer crust are saved in “GHF_Volgo-Uralia_Single-layer.csv” and “GHF_Volgo-Uralia_Multi-layer.csv” respectively.

opencc-by-3.0-usAug 2022View details →

Net Enclosures Disrupt Codling Moth Dispersal Not Establishment - Data Set

To maintain control of codling moth (Cydia pomonella (L.)), apple growers have pursued the use of exclusion netting. The structures implemented range from row covers which are supported by the tree canopy and tied off to the trunk, to full block enclosures which are supported by trellis systems and allow access for workers and equipment. It is uncertain if these nets provide a physical or behavioral barrier to codling moth and if they can prevent establishment in new blocks. To determine the effects of netting we conducted field trials with wild and sterile moths using small (3 trees) and large (48 trees) cages to evaluate the permeability of the netting and the establishment of wild moths.These are the data from those experiments which are used for the publication in Agricultural and Forest Entomology entitled, "Net enclosures disrupt codling moth dispersal not establishment".

Data set for "The ion-ion recombination coefficient α: comparison of temperature- and pressure-dependent parameterisations for the troposphere and stratosphere"

The uploaded data are related to the publication "The ion–ion recombination coefficient $\alpha$: comparison of temperature- and pressure-dependent parameterisations for the troposphere and stratosphere" in Atmospheric Chemistry and Physics (ACP). The data are the same as shown in the figures of the publication. The naming of the uploaded files indicates the figure (e.g., "Fig_2" indicates Figure 2 of the publication).

opencc-by-4.0Jun 2022View details →

Brain Tumor MR Image Data Set For Machine Vision Approach for Brain Tumor Classification using Multi Features Dataset

The uploaded dataset contains the brain tumor MRI dataset. The dataset has been collected form the Bahawal Victoria Hospital, Bahawalpur, Pakistan. This dataset is an authorized MRI brain tumor dataset. Is has been authorized from the expert Radiologists of the Bahawal Victoria Hospital <a href="https://www.qamc.edu.pk/administration/2">BVH</a>. The dataset consists of three brain tumor types,  namely adenomas, meningioma and glioma. it is only for academic, educational and experimental purpose. no other usage will be owned or any liability will be accepted by the authors.

Data set: Quantifying the Accuracy of Collaborative IoT and Robot Sensing in Indoor Settings of Rigid Objects

This is the data set accompanying the paper "Quantifying the Accuracy of Collaborative IoT and Robot Sensing in Indoor Settings of Rigid Objects" by Sune L. Sørensen and Mikkel Baun Kjærgaard. Please refer to the paper for a description of the hardware used to record the data and how it is recorded. It consists of the following files: IoT camera images: RBG images, named img_aa_bbb_0.jpg, where aa is the setup ID, bb is the camera ID (101, 102, 103 or 104). Robot RGB images: RBG images, named aa0.png where aa is the setup ID. Robot point clouds: pcd-files, named aa0.pcd where aa is the setup ID. The transformation from the IoT coordinate system to the robot coordinate system is: robotTiot = np.array([[0.914428, 0.134934, -0.378832, 3.76475], [0.393661, -0.49845, 0.772371, 0.791051], [-0.0846896, -0.855336, -0.509056, 2.37154], [0.0, 0.0, 0.0, 1.0]]) Example, tranforming a pose in IoT coordinates to robot coordinates: p_rob = robotTiot * p_iot

The HAInich: A multidisciplinary vision data-set for a better understanding of the forest ecosystem

We present a multidisciplinary forest ecosystem 3D perception dataset. The dataset was collected in the Hainich-Dün region in central Germany, which includes two dedicated areas, which are part of the Biodiversity Exploratories - a long term research platform for comparative and experimental biodiversity and ecosystem research. The dataset combines several disciplines, including computer science and robotics, biology, bio-geochemistry, and forestry science. We present results for common 3D perception tasks, including classification, depth estimation, localization, and path planning. We combine the full suite of modern perception sensors, including high-resolution fisheye cameras, 3D dense LiDAR, differential GPS, and an inertial measurement unit, with ecological metadata of the area, including stand age, diameter, exact 3D position, and species. The dataset consists of three hand held measurement series taken from sensors mounted on a UAV during each of three seasons: winter, spring, and early summer. This enables new research opportunities and paves the way for testing forest environment 3D perception tasks and mission set automation. We do not focus on even more accurate and better forest data collection, our focus is automated forest inventory for robots.

opencc-by-4.0Jan 2022View details →

Data set for the article 'Robust replication initiation from coupled homeostatic mechanisms'

This data set contains the data of the submitted article "Robust replication initiation from coupled homeostatic mechanisms". The data was generated using simulations in python that are linked below. Experiments indicate that E. coli controls replication initiation via titration and activation of the initiator protein DnaA. We study by mathematical modelling how these two mechanisms interact to generate robust replication-initiation cycles.

Excitation energy transfer and vibronic coherence in intact phycobilisomes — multidimensional electronic spectroscopy data set and MATLAB and Julia analysis code

Data sets used in the article "Excitation energy transfer and vibronic coherence in intact phycobilisomes" by Sil et al. The phycobilisomes were isolated from the short-filament mutant (SF33) of Fremyella diplosiphon UTEX 481 (also known as Tolypothrix sp. PCC 7601). Multidimensional electronic spectroscopy was performed with 6.7 fs mid-visible pulses (520–700 nm) using a pump–probe optical configuration using adaptive pulse shaping techniques. In addition to the full set of two-dimensional spectra and analysis files generated using global and target modeling and analysis of coherences (3DES oscillation maps), we provide here a linear absorption spectrum with phycobiliprotein component analysis as well as a set of 2D excitation–emission fluorescence spectra of intact and broken phycobilisome preparations.  Sil, S.; Tilluck, R. W.; Mohan TM, N.; Leslie, C. H.; Rose, J. B.; Domínguez-Martín, M. A.; Lou, W.; Kerfeld, C. A.; Beck, W. F. Excitation energy transfer and vibronic coherence in intact phycobilisomes. Nat. Chem. (2022), DOI: 10.1038/s41557-022-01026-8. <a href="https://urldefense.com/v3/__https://www.nature.com/articles/s41557-022-01026-8__;!!HXCxUKc!yaVwTZFk8T-j3ROhygpOGW5Xy_E2wQvf-QgNGr9FZZbp4oNpfp_ZmhkdWYLdg2mKSDP8yYrNAZs$">https://www.nature.com/articles/s41557-022-01026-8</a>

An SEM Approach to Validating the Psychological Model of Musical Groove (Data Set)

Data set for the study "An SEM Approach to Validating the Psychological Model of Musical Groove"

Multi-crystal cubic insulin example data set recorded on i24

Data collected as part of routine commissioning on Diamond Light Source beamline i24 15th August 2022 with samples prepared by Felicity Bertram at Diamond following standard techniques. Data are individually incomplete but combined make for a reasonably complete and reasonable data set.    Purpose of the data upload is to make data available for tutorials using the DIALS toolchain (see e.g. examples at https://github.com/graeme-winter/dials_tutorials) however data are available for all purposes without limitation.

IODAQ Exploration Data Set

This repository contains the data underlying the results concerning the exploration of reactions starting from iodine and water presented in Türtscher, P. L.; Reiher, M. 2022 arXiv:2209.04039 [physics.chem-ph].

Data set - What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study

Data set from- What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study Abstract of the study: The treatment of cancer can have a significant impact on quality of life in older patients and this needs to be taken into account in decision making. However, quality of life can consist of many different components with varying importance between individuals. We set out to assess how older patients with cancer define quality of life and the components that are most significant to them. This was a single-centre, qualitative interview study. Patients aged 70 years or older with cancer were asked to answer open-ended questions: What makes life worthwhile? What does quality of life mean to you? What could affect your quality of life? Subsequently, they were asked to choose the five most important determinants of quality of life from a predefined list: cognition, contact with family or with community, independence, staying in your own home, helping others, having enough energy, emotional well-being, life satisfaction, religion and leisure activities. Afterwards, answers to the open-ended questions were independently categorized by two authors. The proportion of patients mentioning each category in the open-ended questions were compared to the predefined questions. Overall, 63 patients (median age 76 years) were included. When asked, “What makes life worthwhile?”, patients identified social functioning (86%) most frequently. Moreover, to define quality of life, patients most frequently mentioned categories in the domains of physical functioning (70%) and physical health (48%). Maintaining cognition was mentioned in 17% of the open-ended questions and it was the most commonly chosen option from the list of determinants (72% of respondents). In conclusion, physical functioning, social functioning, physical health and cognition are important components in quality of life. When discussing treatment options, the impact of treatment on these aspects should be taken into consideration. Reference of research paper: Seghers PAL, Kregting JA, van Huis-Tanja LH, Soubeyran P, O'Hanlon S, Rostoft S, Hamaker ME, Portielje JEA. What Defines Quality of Life for Older Patients Diagnosed with Cancer? A Qualitative Study. Cancers. 2022; 14(5):1123. https://doi.org/10.3390/cancers14051123 Content of the data set: The first Tab describes what questions were asked, the second tab shows all individual anonymised answers to the open questions, the fourth shows the definitions that were used to classify all answers. Q1-Q4 show how the answers were categorised.

data sets of "Dynamic Linear Modeling estimates of long-term ozone trends from homogenized Dobson Umkehr profiles at Arosa, Switzerland"

data sets from "Dynamic Linear Modeling estimates of long-term ozone trends from homogenized Dobson Umkehr profiles at Arosa, Switzerland" Monthly means ozone profiles data sets of MCH homogenized Dobson D051 and of Brewer B040 used in the article entitled: "Dynamic Linear Modeling estimates of long-term ozone trends from homogenized Dobson Umkehr profiles at Arosa, Switzerland" by Eliane Maillard Barras, Alexander Haefele, René Stübi, Achille Jouberton, Herbert Schill, Irina Petropavlovskikh, Koji Miyagawa, Martin Stanek, and Lucien Froidevaux. <a href="https://doi.org/10.5194/acp-2022-344">https://doi.org/10.5194/acp-2022-344</a>

Data Used in [~Re] Setting Inventory Levels in a Bike Sharing Network

Data used to reproduce the publication "Setting an Inventory Levels in a Bike Sharing Network" by Datner et al. This data correspond to the scenarios generated from the parameters given by the authors.

Data set for "Cortical sensory processing across motivational states during goal-directed behavior"

Data set for: Matteucci G, Guyoton M, Mayrhofer JM, Auffret M, Foustoukos G, Petersen CCH, El-Boustani S, Cortical sensory processing across motivational states during goal-directed behavior (2022). Neuron https://doi.org/10.1016/j.neuron.2022.09.032 There are 2 files in this upload: 1. The file named "Matteucci2022.pdf" is the Open Access pdf file of the manuscript published in Neuron. 2. The file named "Matteucci_data_code.zip" (~26.5 GB) is a zipped version of a folder "Matteucci_data_code" (~33 GB), which contains the data analysed in the study along with Matlab code used to generate all main figures of the paper. The analysis code is in a subfolder named "code". This subfolder in turn has three subfolders "analysis_scripts", “analysis_functions” (containing the original code for intermediate data processing) and “paper_figures_scripts” (containing the code for generating each figure panel from pre-processed data). The main script “reproduce_figures.m” will call the subscripts contained in the  “paper_figures_scripts” folder to reproduce the plots contained in all main figures of the paper (and take care of adding the relevant code and data folders and subfolders to Matlab file path). The raw and pre-processed data analysed in the study can be found in the folder named "data". A “README.txt” file provides further details on the content of each subfolder.

Data set for the journal article: Tandem electrocatalytic CO2 reduction with Fe-porphyrins and Cu nanocubes enhances ethylene production

Copper-based tandem schemes have emerged as promising strategies to promote the formation of multi-carbon products of the electrocatalytic CO2 reduction reaction. In such approaches, the CO-generating component of the tandem catalyst increases the local concentration of CO and thereby enhances the intrinsic carbon-carbon (C-C) coupling on copper. However, the optimal characteristics of the CO-generating catalyst for maximizing eventual C2 production are currently unknown. In this work, we developed tunable tandem catalysts comprising iron porphyrin (Fe-Por), as the CO-generating component, and Cu nanocubes (Cucub) to understand how the turnover frequency for CO (TOFCO) of the molecular catalysts impacts C-C coupling on the Cu surface. First, we tuned the TOFCO of the Fe-Por by varying the number of orbitals involved in the π-system. Then, by coupling these molecular catalysts with the Cucub, we assessed the current densities and faradaic efficiencies, discovering that all of the designed Fe- Por boost ethylene production. The most efficient Cucub/Fe-Por tandem catalyst was the one including the Fe-Por with the highest TOFCO and exhibited a nearly 22-fold increase in the ethylene selectivity and 100 mV positive shift of the onset potential with respect to the pristine Cucub. These results reveal that coupling the TOFCO tunability of molecular catalysts along with copper nanocatalysts opens up new possibilities towards the development of Cu-based catalysts with enhanced selectivity for multi-carbon product generation at low overpotential.