Science Inputs (the brown elements) Monitoring, Assessment, & Research: USGS scientists conduct monitoring, assessment, and research that generates data assets. Through the application of business, computational, and analytical processes and technologies, these assets are converted into information products that can be shared with other researchers, stakeholders, and citizens to increase our knowledge and understanding of the Earth's physical and biological systems. Science Project Support: Successful science projects encompass a range of activities represented in the SDLCSDLM. At each step in the cycle, researchers and data stewards rely on an array of sophisticated tools and services for data, information and knowledge discovery, acquisition, integration, management, and sharing. Communities of Practice (the tan element) Communities of practice are the foundation for CDI and all its products – the communities of people working towards the goal of advancing scientific data and information management and data integration across the USGS. Data & Information Assets (the blue elements) USGS assets include Data (e.g., raw data, databases, and linked open data (RDF1)); Information or derived/interpreted information products in the broad sense (e.g., published or shared maps, reports, datasets); and Knowledge of all types and in all forms — recorded, organized, and preserved in the form of various artifacts. Knowledge can then be improved; shared across groups, organizations, and domains; and reused to support individual and group learning and research. Computational Tools & Services (the green elements) Scientific Science Data Life Cycle Lifecycle processes include tools and services that move data through the SDLC, human and machine interactions, and interactions with data through technology. Detailed descriptions of SDLC Processes: - Planning – A documented sequence of intended actions to identify and secure resources and gather, maintain, secure, and utilize data assets;
- Acquisition – The series of actions for collecting or adding to data assets;
- Processing – A series of actions or steps performed on data to verify, organize, transform, integrate, and extract data in an appropriate output form for subsequent use;
- Analysis – A series of actions and methods performed on data that help describe facts, detect patterns, develop explanations, and test hypotheses;
- Preservation – Actions and procedures to keep data for some period of time; to set data aside for future use; and
- Publishing/Sharing – To prepare and issue, or to disseminate data or information products.
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