Lifemapper: Using and Creating Geospatial Data and Open Source Tools for the Biological Community
Aimee Stewart, C.J. Grady, James Beach
Abstract
The open source project Lifemapper 2 creates an archive of species predicted habitat maps and other spatial distribution information. Lifemapper 2 uses museum specimen data archived by the Global Biodiversity Information Facility (GBIF) and accessed through their web services, current and future International Panel on Climate Change (IPCC) climate scenarios, the openModeller niche modeling library, and a 64-node compute cluster. Applied studies using the resulting data can predict the impacts of climate change, loss of biodiversity, spread of invasive species, and emerging diseases.
Lifemapper 2 uses various open source libraries and applications to provide information to the biological community and general public. The Geospatial Data Abstraction Library (GDAL), PostgreSQL, PostGIS, and Mapserver are used in the pipeline of the system, while the cluster uses Sun Grid Engine and openModeller to create the niche models. The website provides archive browsing and data query and download, while web services provide programmatic access.
The services provided by this project will provide inputs for more user-friendly software tools for biological collection data integration and analysis. This will provide a foundation for a new pluggable, extensible architecture that will tie together the services, functions and methods of different applications. The end result will improve quality of data collected and provide support to researchers in studying species’ actual and potential distributions.
Lifemapper 2 uses various open source libraries and applications to provide information to the biological community and general public. The Geospatial Data Abstraction Library (GDAL), PostgreSQL, PostGIS, and Mapserver are used in the pipeline of the system, while the cluster uses Sun Grid Engine and openModeller to create the niche models. The website provides archive browsing and data query and download, while web services provide programmatic access.
The services provided by this project will provide inputs for more user-friendly software tools for biological collection data integration and analysis. This will provide a foundation for a new pluggable, extensible architecture that will tie together the services, functions and methods of different applications. The end result will improve quality of data collected and provide support to researchers in studying species’ actual and potential distributions.