iPlant cyberinfrastructure for sharing, discovering, and analyzing ecological data
Do you work with big data? Do you need to share your data and analyses with collaborators at multiple institutions? Does it take days to run your analyses on your laptop? The iPlant Collaborative (http://www.iplantcollaborative.org/) provides free cyberinfrastructure to biologists to address these very challenges. We are an NSF-funded initiative with the mission to facilitate the transformation of life sciences research and education by providing the computing infrastructure and expertise needed to answer biological questions that were previously difficult or impossible to address. Despite the name, iPlant’s scope includes any life sciences research, be it genomics or ecology; in plants, animals, or microbes; from single-researcher investigations to community-wide collaborations. Our cyberinfrastructure is suitable for ecological research that requires access to shared data storage, very large data sets, high performance computing, or cloud computing. iPlant also provides a platform for developers and informaticians to share their tools with the ecological community.
This presentation will provide an overview of the tools and services available through iPlant, with an emphasis on their utility to ecologists and ecological informaticians. These include: data storage, sharing, and metadata mark-up via the iPlant Data Store; data publishing and discovery through the iPlant Data Commons; cloud-based computing through Atmosphere; web-based access to dozens of applications through the Discovery Environment; iPlant Application Programming Interfaces (APIs) for developers and informaticians; an image management and analysis system with a high performance computing back-end (Bisque); access to high-resolution global environmental layers; and educational and training resources. Several projects that use iPlant’s infrastructure will be touched upon, including the Botanical Information and Ecology Network (BIEN), the One Thousand Plants (1KP) project, and the iMicrobe project. iPlant’s flexible, open-source architecture should be of interest to anyone who needs to organize and analyze very large data sets, is using genomic or metagenomic methods to address ecological questions, or is developing or using ecological models that require large memory or parallel computations.