Find research datasets worth reusing

opencc-by-4.0Nov 2024View details →

Facial and body colouration is linked to social rank in the African cichlid Astatotilapia burtoni

These are raw data files for our publication studying animal colouration and behaviour in an African cichlid, Astatotilapia burtoni.    Abstract Animal colouration is important for social communication within conspecifics to signal threats to competitors or fitness to possible mates. Social status and animal colouration are covarying traits that are plastic in response to dynamic environments. In the African cichlid, Astatotilapia burtoni, body colouration and behaviour have been reported to vary with social rank. However, the nature of the interaction between these two traits is poorly understood. We hypothesise that colouration patterns could be linked to the behavioural repertoires underlying social status and situated across regions of interest on the cichlid body plan. To test this hypothesis, we generated Territorial and Non-territorial males and employed computer vision tools to quantify and visualise patterns/colour enrichment associated with stereotyped Territorial/Non-Territorial male behaviour. We report colour-behaviour interactions localised in specific areas of the body and face for two colour morphs, illustrating a more nuanced view of social behaviour and colouration. Since behavioural and morphological variation are key drivers of selection in the East African Great Rift Lakes, we surmise our data may be translatable to other cichlid lineages and underline the importance of trait covariance in sexual selection and male competition.

opencc-zeroJan 2022View details →

A dataset of 200000 terminal toric varieties of Picard rank 2

Toric varieties of Picard rank 2  with at worst terminal singularities A dataset of 200000 randomly generated toric varieties of Picard rank 2 with at worst terminal Q-factorial singularities, in dimensions 2 to 10. The data consists of the plain text files "rank_2_dim_N.txt" where N, which is the dimension of the toric variety, is in the range 2 to 10. Each line of the file specifies the entries of a (2 x N+2)-matrix. For example, the first line of "rank_2_dim_4.txt" is: [[1,3,5,4,1,0],[0,1,2,5,3,1]] and this corresponds to the 4-dimensional toric variety with weight matrix 1  3  5  4  1  0 0  1  2  5  3  1 and stability condition given by the sum of the columns, which in this case is 14 12 For details, see the paper: "Machine learning the dimension of a Fano variety", Tom Coates, Alexander M. Kasprzyk, and Sara Veneziale, Nature Communications, 14:5526 (2023). doi:10.1038/s41467-023-41157-1 Magma code capable of generating this dataset is in the file "generate_rank_2.m". If you make use of this data, please cite the above paper and the DOI for this data: doi:10.5281/zenodo.5790096

opencc-by-4.0Mar 2022View details →

Data and script for: "Increased birth rank of homosexual males: disentangling the older brother effect and sexual antagonism hypothesis"

Data and script for Tables 2, 3, S2, S3, S4, and S5, and Figures 1, 3, 4, and S1. Individual dataset: France: <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/France_data_df12.csv">France_data_df12.csv </a> Indonesia: <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Indonesia_data.csv">Indonesia_data.csv </a> Greece: <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Greek_data.csv">Greek_data.csv </a> The file <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/France_script.Rmd">France_script.Rmd </a>contains all the analyses of the french data set, including values presented Tables 2, 3, S3, S4, S5, Figures 3, 4 (output in file <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/France_script.html">France_script.html</a>). Same thing for files <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Indonesia_script.Rmd">Indonesia_script.Rmd </a> and <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Greek_script.Rmd">Greek_script.Rmd</a>. For figure 1: <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Fig1.html">Fig1.html </a> For Figure S1: <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Fig_S1.html">Fig_S1.html </a> For Table S2: <a href="https://zenodo.org/api/files/acdb78f8-397c-4bc3-8f68-ec048edbc5f5/Table_S2_script.html">Table_S2_script.html </a>

opencc-by-4.0Dec 2017View details →

Data of the article Analysis of the self-archiving policies of journals in the highest rank category of the Finnish journal classification system within computer science, physics and electronic engineering

The publication forum level three journals representing the three fields of science of computer science, computer science and electrical engineering were identified by utilizing the MinEdu field search filter while searching for the top-ranked journals from the publication channel search (https://www.tsv.fi/julkaisufoorumi/haku.php?lang=en), which is based on Field of Science, Statistics Finland classification (https://www.stat.fi/meta/luokitukset/tieteenala/001-2010/index_en.html). The data were extracted during august 2017 consists of total of 127 individual journals. It is worth noting that circa 30 journals were classified into more than one fields of sciences under scrutiny. First, the journals were divided into representing gold and hybrid model journals. Second, green open access policies of the identified hybrid journals were analyzed using Laakso’s (2014) publisher policy coding framework. Also publishers of the individual journals were identified and subsequently added to the data. NOTE! The data includes the shortest embargo to either institutional or subject repositories. For example, Elsevier had no embargo to opening accepted manuscripts from arXiv subject repository and thus no embargoes to Elsevier's journals are included within this datasheet. Data is in CSV. format

opencc-by-4.0Nov 2019View details →

Ranking data for the eo-Delphi project

The eo-Delphi project (https://osf.io/8f3aj/) created consensus for a core set of outcomes for future studies evaluating the effects of oral corticosteroid therapy in chronic obstructive pulmonary disease (COPD) patients stratified by eosinophil levels. The dataset presented here reports individual ranking scores for proposed outcomes.

opencc-by-4.0Nov 2016View details →

Data of the Open Access Repository Ranking 2015

The Open Access Repository Ranking 2015 ranks open access repositories from Germany, Austria and Switzerland. Data for the 2015 ranking was partly submitted by the respective repository managers, and partly automatically validated via the OAI interfaces. The OARR team reviewed all submissions assuring the quality and validity. The ranking is based on an open and transparent metric that was developed in accordance with the open access community. This metric is a synthesis of different schemes and studies that surveyed and describe open access repositories. Data includes the 2015 scores and descriptive information on the repositories as well as the 2015 metric.

opencc-zeroMar 2022View details →

Rank-based Metric Adjustments

This table contains the adjustments for rank-based metrics for datasets in PyKEEN stratified by split (i.e., training, testing, validation) as well as ranking side (i.e., head, tail, both). If you're not familiar with ranking sides, you probably want both. The columns in the TSV are: <ol> <li>dataset</li> <li>metric</li> <li>side</li> <li>split</li> <li>value</li> </ol>

opencc-by-4.0Mar 2022View details →

Raw Metrics and Rankings for "Exploratory Analysis on Pixelwise Image Segmentation Metrics with an Application in Proximal Sensing"

These datasets accompany the article published in Remote Sensing entitled: "Exploratory Analysis on Pixelwise Image Segmentation Metrics with an Application in Proximal Sensing". For each of the three segmentation models presented in the paper (DTSM, SVM and CIVE) two types of datasets are included:  <ul> <li>Raw Metrics: the raw evaluations for each image returned by each of the 12 evaluation metrics. </li> <li>Rankings: the ranking of each image in the dataset based on its raw evaluation. This dataset has been created by sorting in ascending order the dissimilarity metrics (GCE and HDD) and descending order the similarity metrics (all the other metrics). </li> </ul> The datasets are in Excel (.xlsx) format and can be easily loaded in R and used to reproduce the results presented in the article.

opencc-by-4.0Jun 2024View details →

Leonhard Rank (r2452)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Leonhard Rank musiXplora-ID: r2452 musiXplora-URI: <a href="https://musixplora.de/mxp/r2452">https://musixplora.de/mxp/r2452</a> Gender: m First Mentioned: 2013 Sectors: Alte Musik, Instrumentenbau Professions (Musical): Geigenbauer, Restaurator, Violoncellist Other Places of Activity: Köln, Mittenwald Persönlicher Umkreis: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Netzwerk</td><td>Netzwerkpartner</td><td>Johannes Loescher</td><td><a href="https://musixplora.de/mxp/l2230">l2230</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

opencc-by-4.0Jun 2024View details →

Franz Michael Rank (r1882)

-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> -- Name: Franz Michael Rank musiXplora-ID: r1882 musiXplora-URI: <a href="https://musixplora.de/mxp/r1882">https://musixplora.de/mxp/r1882</a> Gender: m Date of Birth: 19 September 1811 Place of Birth: Rottenburg/Neckar Date of Death: 1870 Place of Death: Undefined First Mentioned: 1839 Sectors: Instrumentenbau Professions (Musical): Holzblasinstrumentenbauer Main Place of Activity: Rottenburg/Neckar Portfolio: <table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Sortimente</td><td>Sortiment</td><td>Fagott</td><td><a href="https://musixplora.de/mxp/2001465">2001465</a></td></tr><tr><td>Sortimente</td><td>Sortiment</td><td>Oboe</td><td><a href="https://musixplora.de/mxp/2001485">2001485</a></td></tr></tbody></table> Titel/Medien: <table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Related</td><td>New Langwill Index 1993</td><td>The New Langwill Index. A Dictionary of Musical Wind-Instrument Makers and Inventors. NLI</td><td><a href="https://musixplora.de/mxp/5001112">5001112</a></td></tr></tbody></table> Ereignisse: <table><tbody><tr><th>Role</th><th>Sigel</th><th>Title</th><th>mXp-ID</th></tr><tr><td>Hersteller</td><td></td><td>Herstellung</td><td><a href="https://musixplora.de/mxp/6021026">6021026</a></td></tr></tbody></table> Changelog:   - v0.0.1: Initial Upload.

Programas académicos en el Ranking de Shanghai 2019 de Universidades Colombianas

Ranking de Shanghai 2019 Programas académicos en el Ranking de Shanghai 2019 de Universidades Colombianas Fuente: http://www.shanghairanking.com/es/

Ranking web of Repositories

TRANSPARENT RANKING: All Repositories by Google Scholar. Incluye Top 10 repositorios de Colombia 2018 y 2019 Fuente: http://repositories.webometrics.info/en/node/30

Frequency and Rank of Family Names in Peru

Count of family names (surnames, last names) in Peru, from an approximately 7% sample of the adult population. In Peru, many people are registered as supporters of political parties, and their names are published by the <a href="https://aplicaciones007.jne.gob.pe/srop_publico/Consulta/PadronAfiliado">Registro de Organizaciones Políticas</a>.  The lists include a DNI (national identity number) for each person to avoid duplicates. The 1,572,002 people on these lists (excluding the regional movements) represent around 7% of the adult population of Peru. Their maternal and paternal family names have been sorted and counted. Nearly all of the names have entries for both paternal and maternal names. These 3,142,561 family names represent 85,395 different names, most of which are infrequent.  The file has been limited to names that occur ten or more times in the sample, which is 12,139 unique names (3,021,655 names, more than 96% of the total). Each row in the file contains the rank, a percentage of that name in the entire set of 3,142,561 names, a count of the times the name occurs in the sample, and the name.  There are some names (around 800) in this file that contain a space. In most cases, these are names like "GARCIA DE RUIZ", where RUIZ is the name of the woman's husband.  There are also cases where the name is like "DE LA CRUZ", which is a complete family name.  No attempt has been made to remove the part of names which refer to the husband's name, this could be considered for a later version.

Frequency and Rank of First Names in Peru

Count of popularity of adult first names (forenames, given names) in Peru, from an approximately 7% sample of the adult population. In Peru, many people are registered as supporters of political parties, and their names are published by the <a href="https://aplicaciones007.jne.gob.pe/srop_publico/Consulta/PadronAfiliado">Registro de Organizaciones Políticas</a>.  The lists include a DNI (national identity number) for each person to avoid duplicates. The 1,572,002 people on these lists (excluding the regional movements) represent around 7% of the adult population of Peru. The first and middle names have been sorted and counted (there are an average of 1.6 first names for each person). These 2,538,011 first (and middle) names represent 76,720 different names, most of which are infrequent.  The file has been limited to names that occur ten or more times in the sample, which is 7,250 unique names (2,417,750 names, more than 95% of the total). Each row in the file contains the rank, a percentage of that name in the entire set of 2,538,011 names, a count of the times the name occurs in the sample, and the name.