Category: Research

With increasing pressure from climate change, loss of biodiversity, and demand for natural resources from already stressed ecosystems, it has become essential to understand and address environmental changes by making sustainable land use decisions with the latest and most accurate data. As part of the Amazon Sustainability Data Initiative (ASDI), AWS invited Joe Sexton, chief scientist and co-founder of terraPulse, to share how AWS technologies and open data are supporting terraPulse’s efforts to provide accurate and up-to-date information on the world’s changing ecosystems.

Since 1971, Canada Centre for Mapping and Earth Observation (CCMEO) at Natural Resources Canada (NRCan) has accumulated an Earth observation (EO) data archive in excess of two petabytes (PB). NRCan wanted to modernize its geospatial offerings at a faster pace, so they turned to the AWS Snow Family on AWS to migrate their large volume of data.

The Materials Project at Lawrence Berkeley National Laboratory (LBNL) is an open database that offers information about material properties, or, all the elements and substances that make up the products we use every day. By harnessing the power of the Department of Energy’s (DOE) high-performance scientific computing and state of the art electronic structure methods, the Materials Project provides open web-based access on AWS to computational datasets on both known and potential materials, along with powerful analysis tools to help discover, inspire, and design new materials.

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on Amazon Web Services (AWS). Our full list of publicly available datasets are on the Registry of Open Data on AWS. This quarter, we released 13 new or updated datasets including CMIP5, 1950s US Decennial Census, and open genomics data for Galaxy. Read on for some highlights.

As part of the Amazon Sustainability Data Initiative (ASDI), AWS invited Rafael Monge Vargas, director of the National Center of GeoEnvironmental Information (CENIGA) at the Costa Rica’s Ministry of Environment and Energy (MINAE), to share how his team is helping advance conservation and economic development in Costa Rica and how they utilize ASDI and AWS to support these efforts.

A research team led by Dr. Beatriz Martinez Lopez at UC Davis supports pig farmers with a data analytics platform that aggregates and analyzes animal health data to diagnose animal viruses and diseases. But this platform was primarily designed for analysts and data scientists. To truly transform animal disease management, Martinez-Lopez wants to put this data analytics tool into the hands of farmers around the world. So the research team is using the scalable, cost-effective tools of the AWS Cloud, along with a research grant letter of support from AWS, to make this optimized platform a reality.

How do we avoid the next global pandemic? For researchers collaborating with the University of British Columbia Cloud Innovation Center (UBC CIC), the answer to that question lies in a massive library of genetic sequencing data. But there is a problem: the data library is so massive that traditional computing can’t comprehensively analyze or process it. So the UBC CIC team collaborated with computational virologists to create Serratus, an open-science viral discovery platform to transform the field of genomics—built on the massive computational power of the Amazon Web Services (AWS) Cloud.

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS. We work with data providers to democratize access to data by making it available to the public for analysis on AWS; to develop new cloud-native techniques, formats, and tools that lower the cost of working with data; and to encourage the development of communities that benefit from access to shared datasets. This quarter, we released 19 new or updated datasets like validated OpenStreetMap data, bioacoustic data, COVID-19 detection data, and more.

It takes a medical village to discover and diagnose rare diseases. The National Institutes of Health’s Undiagnosed Diseases Network (UDN) is made up of a coordinating center, 12 clinical sites, a model organism screening center, a metabolomics core, a sequencing core, and a biorepository. For many years prior to the UDN, the experts at these sites were limited by antiquated data-sharing procedures. The UDN leadership realized that if they wanted to scale up and serve as many patients as possible, they needed to transform how they process, store, and share medical data—which led the UDN to the AWS Cloud.

Galaxy is a scientific workflow, data integration, and digital preservation platform that aims to make computational biology accessible to research scientists that do not have computer programming or systems administration experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system, running on everything from academic mainframes to personal computers. But researchers and organizations may worry about capacity and the accessibility of compute power for those with limited or restrictive budgets. In this blog post, we explain how to implement Galaxy on the cloud at a predictable cost within your research or grant budget with Amazon Lightsail.