Find research datasets worth reusing

Data for coherence measurements of polaritons in thermal equilibrium reveal a power law for two-dimensional condensates

All the raw data sets collected for this project are included in this submission. The code for the numerics is also included.  'Readme.text' files are included with the data sets explaining what the data sets are and how to read them.

Experimental Measurements of Active Vibration Reduction via Current Injection in an Electric Motor

For each considered condition (650 and 800 rpm), two recordings of the motor under test in normal operation without current injection can be found, as well as the 25 current injection tests obtained by combining different values of amplitude and phase. For each case, an excel file with data analysis can also be found. The recordings are provided in the form of .wav files. Each .wav file has 7 channels, arranged as follows: CH1     -> Accelerometer X (Dytran, type 3233A) CH2     -> Accelerometer Y (Dytran, type 3233A) CH3     -> Accelerometer Z (Dytran, type 3233A) CH4     -> Microphone (Bruel&Kjaer, type 4189) CH5    -> Current U CH6    -> Current V CH7    -> Current W

opencc-zeroMay 2024View details →

dryad36/100

Measurements of lead concentrations and isotope ratios of moss and lichens from Portland, Oregon, U.S., and surrounding rural areas

We conducted a high-resolution study of lead in an urban moss, Orthotrichum lyellii, to better understand lead distributions and sources in Portland, Oregon, United States. The goal of this study was to identify modern and persistent legacy urban lead sources. This included an investigation of the impact of relic lead-sheathed telecommunication cables on environmental lead levels. Here we present lead levels and isotopic compositions of (1) moss samples collected from Portland in 2013, (2) moss samples collected 10 years later in 2023 for proximity to lead-sheathed telecommunication cables, (3) archival moss and lichen samples, and (4) rural moss samples. The findings of this study and methods can be found in the linked primary article.

Wavenumber-dependent dynamic light scattering optical coherence tomography measurements of collective and self-diffusion

This repository contains raw data and analysis routines of the publication “Wavenumber-dependent dynamic light scattering optical coherence tomography measurements of collective and self-diffusion” in Optics Express (doi.org/10.1364/OE.521702). The reader is free to use the scripts and data in this depository if the manuscript is correctly cited in their work. For further questions, feel free to contact the corresponding author. Python 3.11 was used for programming. Kindly note that simulating autocorrelation functions from extensive time series data, especially with a high repetition rate, can be time-consuming, often requiring more than 20-30 minutes. Despite parallelized processing routines for the measurement data, the full analysis may still take up to an hour. Please restart the kernel and run the code again if the parallelization fails. Also, keep in mind the significant RAM usage. We've conducted measurements using both a custom-built OCT system and the Thorlabs OCT system. The custom setup specifically focused on measuring diffusion in concentrated suspensions, while the Thorlabs OCT system was used to analyze both concentrated and dilute suspensions. To analyze the data from the custom setup, we require an additional dark measurement file. Conversely, analyzing the Thorlabs measurements necessitates a chirp interpolation file. All filenames, whether for raw data or analysis files, are sufficiently descriptive. Files obtained with the Thorlabs OCT system are easily identifiable as they contain “Thorlabs” in their names. To conduct the analysis of Thorlabs measurements, it's essential to have information regarding the time series length (number of A-scans), the number of repeats (B-scans), and the acquisition rate. The results are plotted at the end of our analysis routines, with the parameters displayed as a function of depth or wavenumber. Raw measurement files and analysis routines are described below. <div> <table> <tbody> <tr> <td> Name </td> <td> Description </td> <td> Parameters </td> </tr> <tr> <td> 10050, 10 us.mat </td> <td> Interference intensity from the custom setup for the concentrated Kostrosöl 10050 sample. </td> <td> Na=8192, Nb=20, 4.5 kHz </td> </tr> <tr> <td> CS50-28, 10 us.mat </td> <td> Interference intensity from the custom setup for the concentrated Levasil CS50-28 sample. </td> <td> Na=8192, Nb=20, 4.5 kHz </td> </tr> <tr> <td> Mix, 10 us.mat </td> <td> Interference intensity from the custom setup for the concentrated mixed sample. </td> <td> Na=8192, Nb=20, 4.5 kHz </td> </tr> <tr> <td> Dark, 10 us.mat </td> <td> Background interference intensity from a custom setup. </td> <td> Na=2048, Nb=5, 4.5 kHz </td> </tr> <tr> <td> Concentrated 8050, Thorlabs.oct </td> <td> Interference intensity from the Thorlabs OCT for the concentrated Kostrosöl 8050 sample. </td> <td> Na=65536, Nb=10, 36 Khz </td> </tr> <tr> <td> Concentrated 9550, Thorlabs.oct </td> <td> Interference intensity from the Thorlabs OCT for the concentrated Kostrosöl 9550 sample. </td> <td> Na=65536, Nb=10, 36 Khz </td> </tr> <tr> <td> Concentrated mix, Thorlabs.oct </td> <td> Interference intensity from the Thorlabs OCT for the concentrated mixed sample. </td> <td> Na=65536, Nb=10, 36 Khz </td> </tr> <tr> <td> Dilute 8050, Thorlabs.oct </td> <td> Interference intensity from the Thorlabs OCT for the dilute Kostrosöl 8050 sample. </td> <td> Na=32768, Nb=20, 36 Khz </td> </tr> <tr> <td> Dilute 9550, Thorlabs.oct </td> <td> Interference intensity from the Thorlabs OCT for the dilute Kostrosöl 9550 sample. </td> <td> Na=32768, Nb=20, 36 Khz </td> </tr> <tr> <td> Dilute mix, Thorlabs.oct </td> <td> Interference intensity from the Thorlabs OCT for the dilute mixed sample. </td> <td> Na=32768, Nb=20, 36 Khz </td> </tr> <tr> <td> Chirp.data </td> <td> File containing k-interpolation data for the Thorlabs OCT measurements. </td> <td>   </td> </tr> <tr> <td> ReadOCTFile.py </td> <td> Written by Jos de Wit, this module reads and imports spectra from raw Thorlabs OCT files. </td> <td>   </td> </tr> <tr> <td> Data_processing.py </td> <td> This module contains all analysis functions. </td> <td>   </td> </tr> <tr> <td> Custom_concentrated.py </td> <td> The script is for analyzing raw concentrated measurement files from the custom setup. </td> <td>   </td> </tr> <tr> <td> Thorlabs_concentrated.py </td> <td> The script is for analyzing raw concentrated measurement files from the Thorlabs setup. </td> <td>   </td> </tr> <tr> <td> Thorlabs_dilute.py </td> <td> The script is for running analysis of raw dilute measurement files from the Thorlabs setup. </td> <td>   </td> </tr> </tbody> </table> </div>

Derived environmental temperatures at Jezero crater from Air Temperature Sensors' measurements on the Perseverance rover.

Material from Version 2 extends derived Air Temperature Sensor data to the first 700 sols of the Mars 2020 mission used in the analysis of Munguira et al. (2024). "One Martian Year of Near-Surface Temperatures at Jezero from MEDA measurements on Mars2020/Perseverance". Journal of Geophysical Research: Planets. [in revision]. We also include the tables needed to generate and reproduce the figures in the paper. Most importantly, the tables include the results from different analyses of temperatures through Fourier series and Reynolds averaging.

Avantes AvaSpec-2048 dark signal measurements for its modeling with ghost pixels (SN: 1311018U2 and 1411011U2)

Each file contains integration time, temperature, dark signal spectra registered (2048 pixels) and the signal recorded by the 20 ghost pixels (20 pixels). This data have been already resampled with a temperature step of 0.1ºC and the temperature delay have been already corrected for UV13.

opencc-by-4.0Apr 2024View details →

Data: Soil moisture modeling with ERA5-Land retrievals, topographic indices, and in situ measurements and its use for predicting ruts

Data for:  Soil moisture modeling with ERA5-Land retrievals, topographic indices, and in situ measurements and its use for predicting ruts Marian Schönauer1, Anneli M. Ågren2, Klaus Katzensteiner3, Florian Hartsch1, Paul Arp4, Simon Drollinger5, Dirk Jaeger1 1Department of Forest Work Science and Engineering, University of Göttingen, Göttingen, Germany 2Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, Sweden 3Institute of Forest Ecology, University of Natural Resources and Life Sciences, Vienna, Vienna, Austria 4Forestry and Environmental Management, University of New Brunswick, New Brunswick, Canada 5Department of Physical Geography, University of Göttingen, Göttingen, Germany

dryad36/100

Changes in ventilatory responses at high altitude measured using rebreathing

Ventilatory responses to hypoxia and hypercapnia play a vital role in maintaining gas exchange homeostasis, and in adaptation to high-altitude environments. This study investigates the mechanisms underlying sensitization of hypoxic and hypercapnic ventilatory responses (HVR and HCVR, respectively) in individuals acclimatized to moderate high altitude (3800 m). Thirty-one participants underwent chemoreflex testing using the Duffin modified rebreathing technique. Measures were taken at sea level and after 2 days of acclimatization to high altitude. Ventilatory recruitment thresholds (VRT), HCVR-Hyperoxia, HCVR-Hypoxia, and HVR were quantified. Acclimatization to high altitude resulted in increased HVR (p<0.001) and HCVR-Hyperoxia (p<0.001), as expected. We also observed that the decrease in VRT under hypoxic test conditions significantly contributed to the elevated HVR at high altitude since the change in VRT across hyperoxic and hypoxic test conditions was greater at high altitude compared to baseline sea level tests (p=0.043). Pre-VRT, or basal, ventilation also increased at high altitude (p<0.001), but the change did not differ between oxygen conditions. Taken together, this data suggests that the increase in HVR at high altitude is at least partially driven by a larger decrease in the VRT in hypoxia versus hyperoxia at high altitude compared to sea level. This study highlights the intricacies of respiratory adaptations during acclimatization to moderate high altitude, shedding light on the roles of the VRT, baseline respiratory drive, and two-slope HCVR in this process. These findings contribute to our understanding of how the human respiratory control responds to hypoxic and hypercapnic challenges at high altitude.

opencc-zeroMay 2024View details →

WST dataset : analysis of the ATR-42 turbulent measurements during EUREC4A

This dataset provides the product of Wavelet Scattering Transform (WST) analysis applied to wind speed (U,V,W), temperature (T) and mixing ratio (MR) measurements taken by the ATR42 during EUREC4A. The WST analysis was conducted on long leg detrended fluctuation data¹, available on the <a href="https://eurec4a.aeris-data.fr/">aeris-data</a> plateform.   This repository includes :  <ul> <li>the WST dataset : WST_analysis_UVWTMR_J12_thr12000.nc</li> <li>script to generate the dataset from initial turbulent data : create_wst_dataset.py </li> <li>python modules : utils.py ; wst1d.py</li> </ul> This research has been funded by the CNRS for the AstrOcean project under the 80Prime initiative. <blockquote> 1 : Lothon, M. & Brilouet, P.-E. (2020).  SAFIRE ATR42: Turbulence Data 25 Hz.  [dataset].  Aeris.  <a href="https://doi.org/10.25326/128">https://doi.org/10.25326/128</a> </blockquote>

Data: Characterizing the sediment dynamics through in-situ measurements in the abyssal Manila Trench, northeast South China Sea

Along the Manila Trench, a total of four moorings were deployed in <a name="OLE_LINK5"></a>September 2019 and recovered in August 2020. The field measurements in velocity and turbidity were resampled to create hourly dataset.

Latest Eocene to mid-late Oligocene calcareous nannoplankton assemblage relative abundance counts and coccolith size measurements: IODP Site U1553

Calcareous nannoplankton are a major group of calcifying marine phytoplankton. Their distribution, productivity and cellular morphological traits are important factors in the role of calcareous nannoplankton in marine ecosystem functions, including the production and export of organic and inorganic carbon.  Using morphometric and assemblage data collected from latest Eocene to mid-late Oligocene sediments International Ocean Discovery Program (IODP) Site U1553, Campbell Plateau in the high latitude southwestern Pacific Ocean, we reconstructed the size structure and associated biogeochemical traits (size-fractionated and total community particulate organic and inorganic carbon) of the community through the Oligocene to investigate the impact of climate-driven changes in community composition on calcareous nannoplankton biogeochemistry.   The datasets presented in this data record are associated with the manuscript: Sheward, R. M., Herrle, J. O., Fuchs, J., Gibbs, S. J., Bown, P. R. and Eibes, P. M. Biogeochemical traits of a high latitude South Pacific Ocean calcareous nannoplankton community during the Oligocene, to be submitted to Paleoceanograpy and Paleoclimatology in June 2024.   This data record contain two primary datasets generated for this study: <ol> <li>assemblage composition (relative coccolith abundance) of the latest Eocene-earliest Oligocene calcareous nannoplankton community</li> <li>morphometric data for the coccolith size of the ten most common morphogroups in the assemblage in this time interval (Chiasmolithus, Clausicoccus subdistichus, Coccolithus, Cyclicargolithus, Reticulofenestra, Sphenolithus, Discoaster and Zygrhablithus bijugatus).</li> </ol>   Correspondence should be addressed to: Rosie Sheward (sheward@em.uni-frankfurt.de).

Monthly production and open-circuit string voltage measurements after 10-year operation of three photovoltaic plants in Southern Spain affected by severe potential-induced degradation

Data are formated in a spreadsheet file.  Data are presented from three photovoltaic plants in Southern Spain (Córdoba province - Northern Andalucía) designed and installed by the same person, with the same photovoltaic module and the same model of inverter, deployed at the same time (end 2009). The plants are severely affected by potential-induced degradation (PID), so that secondary effects produce some by-pass diodes to activate, producing three families of open-circuit voltage (Voc) in the modules (~40V), (~26V) and (~12V) of a total of nominal Voc of 42,6V.  Monthly production is shown along 11 years (2010-2021), and the measurements of the open-circuit voltage of the strings after 10 years of operation along with the voltage range of the modules of each string. Sheet 1: configuration of the architecture of the three photovoltaic plants and the features of the photovoltaic module installed. Sheet 2: energy production for 11 years of opetation. In the last years some recovery is shown in plant 1 and 2 because a repowering project. Sheet 3: partial climate data of the towns were the plants are located. Sheet 4: open-circuit voltages of the strings and number of modules in each string with open-circuit voltage in the ranges (~40V) and (<=26V) in plant 1, july-2018. Sheet 5: open-circuit voltages of the strings and number of modules in each string with open-circuit voltage in the ranges (~40V), (~26V) and (~12V) in plant 2, july-2020.

Chemical Measurement Data Set

The original data from: NAnderson2020MendeleyMangoNIRData.csv: <a href="https://data.mendeley.com/datasets/46htwnp833/2">https://data.mendeley.com/datasets/46htwnp833/2</a> wheat kernels of 30 varieties.csv: <a href="https://github.com/L-Zhou17/Wheat-kernels/tree/master">https://github.com/L-Zhou17/Wheat-kernels/tree/master</a> SMRT_dataset.csv: <a href="https://doi.org/10.6084/m9.figshare.8038913">https://doi.org/10.6084/m9.figshare.8038913</a> CCSbase_data.csv: <a href="https://ccsbase.net/about">https://ccsbase.net/about</a> Pubchem_semistdnp_RI.csv: <a href="https://pubchem.ncbi.nlm.nih.gov/">https://pubchem.ncbi.nlm.nih.gov/</a>

opencc-by-4.0Sep 2023View details →

Quantifying Progress: Metrics and Indicators for Measuring Digital Transformation Maturity in Organizations

As organizations increasingly embark on digital transformation journeys, the need for effective metrics and indicators to measure progress and maturity becomes paramount. This paper investigates the development and application of metrics for quantifying digital transformation maturity in organizations. Through an extensive review of literature and examination of case studies, the paper identifies key dimensions and stages of digital maturity. It proposes a framework encompassing both quantitative and qualitative metrics that can be used to assess an organization's digital transformation journey. The paper explores challenges associated with defining meaningful metrics and offers insights into adapting measurement frameworks to diverse organizational contexts. By addressing this critical gap in the literature, the paper aims to provide practitioners, researchers, and decision-makers with a valuable resource for evaluating and benchmarking digital transformation progress, fostering a more nuanced understanding of the multifaceted nature of organizational digital maturity.

opencc-by-4.0Mar 2017View details →

Fig. 6 in Identification of Muscidae (Diptera) of medico-legal importance by means of wing measurements

Fig. 6 Discrimination of four species of the Muscina based on canonical variate analysis

opencc-by-4.0Mar 2017View details →

Fig. 5 in Identification of Muscidae (Diptera) of medico-legal importance by means of wing measurements

Fig. 5 Discrimination of eight species of the Hydrotaea based on canonical variate analysis

opencc-by-4.0Mar 2017View details →

Fig. 4 in Identification of Muscidae (Diptera) of medico-legal importance by means of wing measurements

Fig. 4 Discrimination of Muscidae genera based on canonical variate analysis

Testing a new optical strain gage for full-field strain measurement: Raw images

<pre>This dataset contains images obtained during two different tests performed to assess the response of a new optical strain gage developped for full-field strain measurement.</pre> <pre>File contents:   - SMA: Folder containing images obtained with a SMA specimen         - SMA_Paint_Ref: contains 100 images in the reference state. These were taken with the optimal parameters for the painted and engraved half (lower half in the images).         - SMA_Paint_Def: contains 100 images in the deformed state.          - SMA_Gage_Ref: contains 100 images in the reference state. These were taken with the optimal parameters for the gage (upper half in the images).         - SMA_Gage_Def: contains 100 images in the deformed state.    - Wood: Folder containing images obtained with a wood specimen         - Wood_Paint_Ref: contains 100 images in the reference state.         - Wood_Paint_Def: contains 100 images in the deformed state.          - Wood_Gage_Ref: contains 100 images in the reference state.         - Wood_Gage_Def: contains 100 images in the deformed state.  These images can be processed with the Python code available in the OpenLSA library: https://gitlab.ip.uca.fr/expmech/openlsa .</pre> An example is provided in this library.

opencc-by-sa-4.0Jun 2024View details →

LENS: A LEO Satellite Network Measurement Dataset - 202404 - Part 2

LENS dataset 2024-04 Part 2 Please see <a href="https://github.com/clarkzjw/LENS" target="_blank" rel="noopener">https://github.com/clarkzjw/LENS</a> for the complete description of the dataset.