Find research datasets worth reusing

Dwelling conversion and energy retrofit modify building anthropogenic heat emission under past and future climates: a case study of London terraced houses

This archive includes the data used (e.g. Time use survey (UK-TUS) data), model files (idf files for running EnergyPlus) and codes for analysis in the paper (<a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.enbuild.2024.114668" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.enbuild.2024.114668</a>). Files in this archive should include: <ul> <li>Time use survey data analysis</li> </ul> o   Main dataset: TUS_activity.zip o   Code: TUS_clustering_code.zip o   Output: InternalHeatProfile.zip <ul> <li>Building energy modeling </li> </ul> o   Main dataset (run in EnergPlus 9.4): IDFfiles.zip o   Output: Eplus_output.zip <ul> <li>PostProcess analysis</li> </ul> o   Code: QF_analysis_code.zip o   Output: QF_output.zip   Note: this version currently only includes the outputs of all processes, the main dataset and code will be updated later.

WBES2023 data for paper entitled "The effect of informal competition on family firms' performance: The case of three Western Balkans candidates for EU membership"

WBES2023 data for paper entitled "The effect of informal competition on family firms’ performance: The case of three Western Balkans candidates for EU membership"

opencc-by-4.0Aug 2021View details →

Fig. 4 in Use of ITS-1 to identify Bactrocera dorsalis and Bactrocera occipitalis (Diptera: Tephritidae): a case study using flies trapped in California from 2008 to 2018

Fig. 4. Image of wing of fly (16V457) with Bactrocera occipitalis ITS‑1 sequence.

opencc-by-4.0Aug 2021View details →

Fig. 3 in Use of ITS-1 to identify Bactrocera dorsalis and Bactrocera occipitalis (Diptera: Tephritidae): a case study using flies trapped in California from 2008 to 2018

Fig. 3. Image of first Bactrocera occipitalis trapped in California in 1983.

Demo-Dataset for publication "FAIR workflows in Earth system modelling: a use case with semantic data management"

This demodataset is intended to be used to test the workflow described in the publication by Lennartz & Schlemmer  "FAIR workflows in Earth System modelling: a use case with semantic data management". It contains example model output for an arbitrary biogeochemical model tracer (here: dissolved organic carbon, DOC) from an ocean model as a 4-dimensional dataset (latitude, longitude, depth, time), the corresponding grid point locations as well as a textfile specifying parameter inputs for the model. The file structure is adapted for seamless integration into the workflow described in Lennartz & Schlemmer, which builds on the open source semantic research data management system LinkAhead. The dataset contains the following structure: The folder DataAnalysis stores data required for data analysis, such as the grid point locations in the file TMM_grid_v2018a.mat. The folder SimulationData stores model output in the folder 2022_TMM, containing the parameter input file nl_in.txt and the model output TR_monthly.mat. Related instructions can be accessed here: https://gitlab.com/salexan/fairworkflows-demodataset .

Mapping the potential habitat suitability, and opportunities of bush encroacher species in Southern Africa: a case study of the SteamBioAfrica project.

Senegalia mellifera (Benth) Seigler & Ebinger. , Dichrostachys cinerea (L.) Wight & Arn. and Terminalia sericea Burch. Ex DC., are three important bush encroacher species that contribute to the well-known ecological process named "thicketization" in Southern Africa. This issue has persisted for many years, impacting species distribution, plant communities, soil, and fauna dynamics. According to climate change projections, Southern Africa is expected to become drier and warmer in future scenarios, creating favourable conditions for proliferation of bush encroacher species. In the paper, we analyze the habitat suitability of these bush encroachers through MaxEnt 3.4.4 under three different future climate models and scenarios. Future projections were made using the shared socio-economic pathways (SSPs) for greenhouse gas concentrations, specifically SSP245-585 across two-time horizons: 2041-2060 and 2061-2180. We utilized <a href="https://www.worldclim.org/data/cmip6/cmip6climate.html">WorldClim 1-km resolution climate data</a> from three global Earth System Models (ESMs) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) that obtained better results than CMIP5 models (Bouramdane 2022; Mmame and Ngongondo 2024): the Max Planck Institute for Meteorology Earth System Model (MPI-ESM1.2-HR), the Hadley Climate Center Earth System Model (UK-ESM1.0-LL) and the Institute Model for Numerical Mathematics (INM-CM5-0).

Hydrodynamic and Polarization Data for 'The Curious Case of V CVn'

A subset of the data for the Curious Case of V CVn.  Polarization data columns are in the form (problem_time, gamma_p). Hydrodynamic data columns are in the form (x1b(i), x2b(j), d(i,j,k), e1(i,j,k), x1a(i), x2a(j), v1(i,j,k), v2(i,j,k), divv(i,j,k)). Each of the variables are standard definitions in ZEUS3D.

Leveraging Multi-Agent Systems and Decentralised Autonomous Organisations for Tax Credit Tracking: A Case Study of the Superbonus 110% in Italy

The present dataset was obtained as output of the simulation of Secure Fiscal Credit Model (SCFM) demonstrator. The software, inspectable at the link in the repository url, allows to simulate the workflow and payments involved in the execution of Italian Superbonus 110% fiscal credits model. Two different Scenarios were tested, parameters are reported in the following table. <table> <tbody> <tr> <td> </td> <td>GC payment</td> <td>Tech Asseveration</td> <td>Open</td> <td>Anticipation</td> <td>SAL1</td> <td>SAL2</td> <td>EOW</td> <td>Tech fee</td> </tr> <tr> <td>Scenario 1</td> <td>50%</td> <td>50%</td> <td>10%</td> <td>10%</td> <td>30%</td> <td>40%</td> <td>10%</td> <td>15%</td> </tr> <tr> <td>Scenario 2</td> <td>25%</td> <td>25%</td> <td>10%</td> <td>10%</td> <td>30%</td> <td>40%</td> <td>10%</td> <td>15%</td> </tr> </tbody> </table> File named with S1 prefix refer to Scenario 1, while those with S2 prefix refer to Scenario 2.

New insights into the driving mechanism of the mid-Eocene (43 Ma) tectonic transition in the western Pacific margin—A case study of stress field modeling in Pingbei

This is the dataset for " New insights into the driving mechanism of the mid-Eocene (43 Ma) tectonic transition in the western Pacific margin—A case study of stress field modeling in Pingbei" including modeling parameters and raw results.

Process Integration Multi-Actor Multi-Criteria Optimization (PI-MAMCO) Framework: Case Study on Palm Oil Based Complex (POBC)

The dataset includes the complete workflow for the PI-MAMCO method implementation, demonstrated on a POBC integration case study. The files are structured as follows: <ol> <li> NOTEBOOKS Folder: This folder contains the Jupyter notebooks that constitute the entire workflow of our case study. These notebooks import necessary model equations, data, and functions from the "MODEL" folder. Running these notebooks with the correct Python package versions will reproduce the exact results presented in our submitted article. </li> <li> MODEL Folder: This folder includes all model equations, data, and functions required by the Jupyter notebooks. The scripts in this folder are integral to executing the PI-MAMCO method as outlined in our research. </li> <li> OUTPUTS Folder: The results generated by running the notebooks are saved in this folder. This includes all outputs reported in our manuscript as well as additional results not included in the paper. </li> <li>OUTPUTS_GENERATED Folder: The files contained in this folder are the expected results from executing the case study notebook.</li> </ol> Reproducibility: To ensure the reproducibility of our results, please ensure that you are using the correct versions of the required Python packages. Detailed instructions for setting up the Python environment are provided within the notebook and the readme.txt. Contained are also outputs from the <a href="https://www.sciencedirect.com/science/article/pii/S0957417422003931" target="_blank" rel="noopener">IRenE procedure</a>, used for the literature review (01_extracted_keywords.xlsx ; 02_sampling_results.csv)

The number of HAdV species B and HAdV species C positive cases by age group, and their positivity rates among ARTI cases.

The number of HAdV species B and HAdV species C positive cases by age group, and their positivity rates among ARTI cases.

Tab. 1 in Cases of albinism and leucism in amphibians in Italy: new reports

Tab. 1 - Cases of albinism and leucism in Italian amphibians observed in this study.<table><thead><tr><th>Species</th><th>Phase</th><th>Individuals</th><th>Chromatic aberration</th><th>Region of origin</th></tr></thead><tbody><tr><th>Salamandra salamandra</th><td>Larva</td><td>3</td><td>Partial albinism with xantophores</td><td>Lombardy</td></tr><tr><th>Salamandra salamandra</th><td>Larva followed after metamorphosis</td><td>1</td><td>Partial albinism with xantophores</td><td>Lombardy</td></tr><tr><th>Salamandra salamandra</th><td>Adult</td><td>1</td><td>Leucism</td><td>Lombardy</td></tr><tr><th>Salamandra salamandra</th><td>Adult</td><td>1</td><td>Leucism</td><td>South Tyrol</td></tr><tr><th>Triturus carnifex</th><td>Larva</td><td>1</td><td>Leucism</td><td>Lombardy</td></tr><tr><th>Hydromantes sarrabusensis</th><td>Adults/subadults</td><td>6/4</td><td>Leucism</td><td>Sardinia</td></tr><tr><th>Hydromantes flavus</th><td>Adult</td><td>3</td><td>Leucism</td><td>Sardinia</td></tr><tr><th>Hydromantes supramontis</th><td>Adult</td><td>3</td><td>Leucism</td><td>Sardinia</td></tr><tr><th>Bufo viridis</th><td>Tadpole</td><td>1</td><td>Leucism</td><td>Lombardy</td></tr></tbody></table>

LIAISE LES - Prescribed Surface Fluxes Case

Model input fields and select statistics for the MicroHH Large Eddy Simulation used in the prescribed surface flux case of the LIAISE LES experiment.  In order to run the case, one needs to have the MicroHH model (https://github.com/microhh/microhh) and the (LS)2D package (https://github.com/LS2D).   More information on the LIAISE experiment as well as the radiosonde data used for initialization and nudging can be found at: https://liaise.aeris-data.fr/page-catalogue/.   Contents:  <ul> <li>LIAISE_GoldenDay_sfc_30m_ext_8Dec.nc - Netcdf file with the prescribed surface fluxes averaged over 20-22 July 2021.</li> <li>offline_may2024.py - File to create MicroHH model input and binary files. It uses the input from the surface fluxes netcdf file as well as smoothed radiosondes from the Els Plans site (available for download from the LIAISE catalogue). </li> <li>offline_may2024.ini – initialization file that is edited created with the offline_may2024.py file. </li> <li>Statistics from the model: </li> <ul> <li>offline_may2024.default.0000000.nc - spatial statistics for the entire extended LIAISE domain </li> <li>offline_may2024.regional.0000000.nc - spatial statistics for the LAISE regional scale</li> <li>offline_may2024.wet.0000000.nc - spatial statistics for the wet landscape scale</li> <li>offline_may2024.dry.0000000.nc - spatial statistics for the dry landscape scale</li> </ul> </ul>

Tab. 4 in The local forms of Zootecus (Gastropoda: Pulmonata: Subulinidae) of Pakistan: an archaeomalacological case study

Tab. 4 - Values of q based on Tukey test. The pairs pointed out with asterisks (*) are significantly different.<table><tbody><tr><th>Comparison of samples</th><th>q</th></tr></tbody><tbody><tr><th>RH59 - RH480</th><td>0.5853</td></tr><tr><th>RH59 - WP31 *</th><td>4.8001</td></tr><tr><th>RH59 -WP16 *</th><td>5.9384</td></tr><tr><th>RH59 - UTHAL *</th><td>6.402</td></tr><tr><th>RH480 - WP31</th><td>1.3343</td></tr><tr><th>RH480 - WP16</th><td>1.5047</td></tr><tr><th>RH480 - UTHAL</th><td>2.8947</td></tr><tr><th>WP31 - WP16</th><td>3.4168</td></tr><tr><th>WP31 - UTHAL *</th><td>5.4741</td></tr><tr><th>WP16 - UTHAL</th><td>2.2843</td></tr></tbody></table>

Tab. 3 in The local forms of Zootecus (Gastropoda: Pulmonata: Subulinidae) of Pakistan: an archaeomalacological case study

Tab. 3 - Results of ANOVA test. DF, degree of freedom; S 2, variance; F, variance ratio; P, significance level.<table><tbody><tr><th>Source of variation</th><th>Deviance</th><th>DF</th><th>S 2</th><th>F</th><th>P</th></tr></tbody><tbody><tr><th>Within groups variance</th><td>107.8805</td><td>986</td><td></td><td></td><td></td></tr><tr><th>Common regression slope</th><td>0.226133</td><td>1</td><td>0.226133</td><td>2.075882</td><td><0.01</td></tr><tr><th>Between regression slopes</th><td>0.8000667</td><td>4</td><td>0.200017</td><td>1.836137</td><td><0.05</td></tr><tr><th>Error for coefficient</th><td>106.8637</td><td>981</td><td>0.108933</td><td></td><td></td></tr></tbody></table>

Tab. 2 in The local forms of Zootecus (Gastropoda: Pulmonata: Subulinidae) of Pakistan: an archaeomalacological case study

Tab. 2 - Number of individuals, heights (H), diameters (D), means, roundness indices (H/D), whorl numbers and linear regression coefficient for Zootecus sp. of the five sites.<table><tbody><tr><th></th><th>WP 16</th><th>WP 31</th><th>UTHAL</th><th>RH 59</th><th>RH 480</th></tr></tbody><tbody><tr><th>Numbers of individuals</th><td>240</td><td>162</td><td>217</td><td>197</td><td>167</td></tr><tr><th>Mean H mm</th><td>10.75</td><td>11.40</td><td>11.57</td><td>11.97</td><td>10.70</td></tr><tr><th>Max H mm</th><td>13.50</td><td>13.30</td><td>14.85</td><td>17.00</td><td>12.90</td></tr><tr><th>Min H mm</th><td>8.00</td><td>9.50</td><td>8.30</td><td>10.00</td><td>8.50</td></tr><tr><th>Delta H mm</th><td>5.50</td><td>3.800</td><td>6.55</td><td>7.00</td><td>4.40</td></tr><tr><th>Mean D mm</th><td>4.69</td><td>4.85</td><td>4.80</td><td>4.19</td><td>4.87</td></tr><tr><th>Max D mm</th><td>6.00</td><td>5.60</td><td>5.50</td><td>4.85</td><td>5.60</td></tr><tr><th>Min D mm</th><td>3.80</td><td>3.90</td><td>4.10</td><td>3.70</td><td>3.50</td></tr><tr><th>Delta D mm</th><td>2.20</td><td>0.95</td><td>1.40</td><td>1.15</td><td>2.10</td></tr><tr><th>Mean roundness H/D</th><td>2.30</td><td>2.30</td><td>2.41</td><td>2.85</td><td>2.19</td></tr><tr><th>Whorl numbers</th><td>8</td><td>8</td><td>8 and 9</td><td>8 and 10</td><td>7 and 8</td></tr><tr><th>Linear regression equation</th><td>y = 0.2493x + 1.9771</td><td>y = 0.1606x + 3.0419</td><td>y = 0.302x + 1.1788</td><td>y = 0.10278x + 2.9634</td><td>y = 0.2122x + 2.5862</td></tr></tbody></table>

Deliverable D1.2 - Supplementary material : Datasets on substance prioritization for subsequent development of target analytical methods for relevant iPM(T) substances in waters in case studies CS#1, CS#2, CS#3 & CS#7.

Additional information on deliverable D1.2. Data sets for substance prioritization and subsequent development of target analytical methods for relevant iPM(T) substances in waters in case studies CS#1, CS#2, CS#3 and CS#7.

Data underlying the manuscript: "Analysis of Research Data Sharing in Scientific Articles on Climate Change in the Covid-19 Year. The Spanish case 2020".

This is the research data for the manuscript "Analysis of Research Data Sharing in Scientific Articles on Climate Change in the Covid-19 Year. The Spanish case 2020". The following is the original abstract: Introduction: Sharing research data on climate change would facilitate the development of solutions to curb its impact, for this, data needs to be shared in an optimal way. General objective: To identify how many Spanish scientific articles on climate change published during 2020 share their research data in some way. Specific objectives: a) Identify the attributes of shared research data b) Describe the characteristics of the case studies found on how research data are shared. Methodology: Qualitative and descriptive study analyzing nine attributes: availability (1), accessibility (2), format (3), license (4), linkage (5), funding (6), editorial policy (7), content (8), statistics (9). Results: We analyzed 2212 articles were analyzed, 1867 (84%) articles had no associated research data. The remaining 16% have associated research data: 152 (7%) articles deposited their data in repositories, 42 (2%) submitted their data as supplementary material, 136 (6%) will share their data upon request to the author and 15 (1%) do not have publication permissions. Conclusions: Researchers are willing to share their research data, but under different conditions. Researchers who reused research data did not share the new data they generated. There is a lack of training among researchers on how to manage their research data. There is information on the web on this topic, but it is not just a matter of publishing manuals, but also of creating training spaces within universities, institutes and research centers to build a community of researchers committed to Open Science.

Network formation as Narrative: Case Study Data

This data is the companion to a forthcoming paper entitled Network Formation As Narrative In Computer Role-playing Games. It consists of several excel sheets and gephi files with some graphs of social network data from a campaign of Mount & Blade: Warband, a campaign of The Exile Princes, and some hand-curated data on networks presented in the narrative of the early part of Baldur's Gate 3.