Resultados de investigación

This data set contains a data-mining performed to assess the impact of crop diversification, tillage and fertilizer type on soil microbial, fungal and bacterial abundance under arable crops worldwide by a further meta-analysis of the data. These data correspond to the open-access article "The impact of crop diversification, tillage and fertilization type on soil total microbial, fungal and bacterial abundance: A worldwide meta-analysis of agricultural sites" published in Agriculture Ecosystems and Environment. (doi:10.1016/j.agee.2022.107867), funded by the European Commission Horizon 2020 project SoildiverAgro [grant agreement 817819].

Aplicación de métodos de análisis y predicción de series temporales basados en sistemas dinámicos no lineales y redes complejas. Aplicados a una serie temporal multidimensional obtenida del servicio OpenData de la AEMET, compuesta por diversas variables meteorológicas (temperatura media, mínima, máxima, velocidad media del viento, irradiación solar, y presión atmosférica, entre otras) diarias registradas por la estación de Murcia (código 7178I) desde el 2016-03-01 hasta el 2021-02-01. Estos datos se han recopilado para el proyecto BitBlue: Investigación de técnicas de difusión, procesado y análisis de Big Data del medio marino, financiado por el Instituto de Fomento de la Región de Murcia con el apoyo de los Fondos FEDER.

This dataset contains the experimental data obtained during the characterization and tribological evaluation of water-based biolubricants formulated with choline acetate, choline chloride and choline lysinate. The dataset includes physicochemical characterization, friction and wear results, viscosity measurements, wettability studies, corrosion tests and surface analyses associated with tribological testing., Ministerio de Ciencia e Innovación (MCIN/AEI): Project PID2021-122169NB-I00. Predoctoral contract PRE2022-102014

Rainfall data only for non-commercial use, see License file. See meta file for more information.This item is a part of the collection "Dataset for Bellinge: An urban drainage case study", https://doi.org/10.11583/DTU.c.5029124 Changes in version 2 - 31-08-2021- Updated documentation file- The period is extended to Aug 18th 2021

The repository is formatted in the following structure: - README.md: markdown file with repository description - MarSOC-Dataset.Rproj: R project file - useful when using RStudio - Maxwell_MarSOC_dataset.csv: .csv file containing the final dataset. The data structure is described in the metadata file. It contains 17,454 records distributed amongst 29 countries. - Maxwell_MarSOC_dataset_metadata.csv: .csv file containing the main data file metadata (equivalent to Table 1). - data_paper/: folder containing the list of studies included in the dataset, as well as figures for this data paper (generated from the following R script: ‘reports/04_data_process/scripts/04_data-paper_data_clean.R’). - reports/01_litsearchr/: folder containing .bib files with references from the original naive search, a .Rmd document describing the litsearchr analysis using nodes to go from the naive search to the final search string, and the .bib files from this final search, which were then imported into sysrev for abstract screening. - reports/02_sysrev/: folder with .csv files exported from sysrev after abstract screening. These files contain the included studies with their various labels. - reports/03_data_format/: folder containing all original data, associated scripts, and exported data. - reports/04_data_process/: folder containing data processing scripts to bind and clean the exported data, as well as a script testing the different models for predicting soil organic carbon from organic matter and finalising the equation using all available data. A script testing and removing outliers is also included.