Big data and data quality
Al CREAF, investiguem com gestionar i analitzar grans volums de dades ambientals per millorar la comprensió i la gestió del medi ambient. Desenvolupem i optimitzem bases de dades geoespacials, afavorim iniciatives de dades obertes, establim estàndards de qualitat per a la informació geoespacial, i creem eines avançades de visualització. Apliquem tècniques de Big Data a la genòmica, els inventaris forestals i l'ecologia per aprofundir en el coneixement dels ecosistemes.
Que es Big data and data quality?
Environmental Big Data refers to the collection, management and analysis of large volumes of data related to the environment. This data can come from various sources, such as sensors, satellite images, and field studies. The ability to process and interpret these large volumes of data allows for a better understanding of changes in ecosystems, climate trends and the impact of human activities on the environment. Advances in Big Data facilitate the identification of patterns, the prediction of future trends and the making of more informed decisions in environmental management.
How to work with Big Data in environmental research?
- Optimization of Geospatial Databases: We research and develop optimal formats for geospatial information, including long time series of remote sensing images. This includes studies on data compression, preservation and computational optimization.
- Open Data: We promote and integrate open science initiatives, facilitating free access to data and metadata to promote transparency and collaboration in research.
- Quality Standards: We implement innovative tools for the visualization and search of geospatial information, establishing quality standards to guarantee the reliability and consistency of the data.
- Applications in Ecology: We use Big Data for stoichiometric ecology, ecometabolomics and functional ecology, creating mathematical models that relate carbon concentrations and flows to species diversity and global change factors.
