USGS - science for a changing world

Core Science Analytics, Synthesis, and Libraries (CSAS&L)

About Core Science Analytics, Synthesis, and Libraries

Background and Moving Forward

Core Science Analytics, Synthesis, and Libraries (CSAS&L) is formerly the Biological Informatics Program (BIP) and Core Science Informatics (CSI) Organization under the U.S. Geological Survey Core Science Systems (CSS) Mission Area. The two groups merged on October 24, 2011.

CSAS&L Goals

Goal 1: Develop and implement standard business practices across CSAS&L to improve efficiency and effectiveness in accomplishing the Program's Mission.
Goal 2: Provide leadership, guidance, and expertise to assist USGS scientists in fully implementing the data lifecycle for the long-term management of earth science data and information products.
Goal 3: Enable data-driven science by continuing to develop and integrate core species and habitat datasets, scalable to the national level.
Goal 4: Enable earth science data discovery, integration, and analysis in USGS by developing and supporting suites of tools, data transformation capabilities, and technological capacity.
Goal 5: Conduct research, in coordination with other USGS teams, which advances the science of data discovery, integration and analysis, and improves understanding of our key stakeholders, their data needs, and workflow processes.
Supports the USGS Science Strategy

Start with Science: Science StrategyCSAS&L broadens its focus to incorporate all of USGS by maintaining key expertise in biological informatics and by leveraging current expertise and capacity to strengthen the USGS leadership role in scientific data management and preservation. These efforts advance the capacity of CSAS&L to conduct synthesis, analysis, and visualization of scientific data and reduce duplication of effort.

Key Functions Include:

  • Applied Science Products and Support
  • Applied Scientific Modeling and Application Development
  • Scientific Computing Platform
  • Community Leadership and Facilitation
  • Science Data Management and Leadership
  • Applied Earth Science Informatics Research
Science Data Management
Science Data Integration and Visualization
Applied Earth Systems Informatics Research
Biogeographic Characterization
Eco-Science Synthesis