AGU is convening a partnership in the Earth and space science community to develop the standards to connect researchers, publishers, and data repositories.
data management
Posted inEditors' Vox
“Do You Expect Me to Just Give Away My Data?”
The Editor-in-Chief of JGR: Oceans explains why the new AGU data policy is important for the rigor and long-term security of scientific research.
Posted inScience Updates
Strengthening the Observational Basis for Carbon Science, Policy
Sustained Observations for Carbon Cycle Science and Decision Support Workshop; Boulder, Colorado, 13–14 April 2016
Posted inFeatures
Monitoring Ocean Change in the 21st Century
Time series data sets, which contain measurements repeated over a span of decades, yield important insights into our oceans’ vital signs.
Posted inOpinions
Three Steps to Successful Collaboration with Data Scientists
A step-by-step cartoon guide to efficient, effective collaboration between Earth scientists and data scientists.
Posted inEditors' Vox
New Findings from Old Data
Recalibrated and reanalyzed data from the Voyager flybys of Jupiter 40 years ago, presented in a series of papers in JGR: Space Physics, show the value of archival data.
Posted inScience Updates
Giovanni: The Bridge Between Data and Science
Using satellite remote sensing data sets can be a daunting task. Giovanni, a Web-based tool, facilitates access, visualization, and exploration for many of NASA’s Earth science data sets.
Posted inResearch Spotlights
New Data Record Extends History of Global Air Pollution
Researchers extend long-term aerosol records to the past 40 years by combining two existing algorithms to process satellite data over both land and sea.
Posted inResearch Spotlights
Blending Satellite Data to Monitor Agricultural Water Use
A new technique that merges data gathered by multiple satellites can be used to monitor agricultural water use and improve water quality assessments around the globe.
Posted inScience Updates
Tracking River Flows from Space
Satellite observations, combined with algorithms borrowed from river engineering, could fill large gaps in our knowledge of global river flows where field data are lacking.