The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing scientific data and information management and integration capabilities within the United States Geological Survey (USGS).
In 2012, the CDI Coordinators developed a Science Support Framework (SSF) (Figure 2) that categorizes and relates the activities and processes through which research data flows and within and upon which the CDI operates. It is these categories that provide the focus and a framework for coordination and integration of current and future CDI-funded projects. A more detailed explanation of the CDI SSF categories and the direction of data flow through the framework are included towards the end of this page.
CDI Operational Context for the Science Support Framework
Since 2009, CDI has funded a variety of projects that support the overarching goal of data integration (Proposals). USGS and other researchers conduct monitoring, assessment, and research activities that generate data assets, which through the application of business, computational, and analytic processes and technologies are converted into information that contributes to our understanding of the Earth’s physical and biological systems. It is within this context that data management and integration occurs and where the CDI operates (Figure 1). The CDI has provided funding support for projects that promote data integration and
- Focus on short-term benefits to science
- Leverage existing capabilities
- Apply solution/methodology that can be replicated
- Ensure sustainability
- Seek substantial return on investment
- Expose corporate data
- Organize science models and outputs
- Preserve and access project data
Figure 1: Overview of CDI Operational Context
Communities of practice include scientists, the CDI as a whole, CDI Working Groups, external partners, and the human network of scientific domain collaborators.
Computational tools and services include applications, Web services, data discovery tools, models, semantic services and tools, infrastructure, data brokers, and visualization tools.
Management, policy, and standards include data stewardship, the implementation of the Data Management Life Cycle, knowledge management, data standards, governance, and policy.
Data and information assets include persistent archives, data registries, catalogs, data, metadata, derived information products, knowledge bases, and vocabularies/ontologies.
CDI Science Support Framework (SSF)
The CDI SSF provides a conceptual architecture that: illustrates how the CDI contributes to Bureau-level data integration efforts; and defines how current and future CDI projects fit within the framework.
USGS SCIENTISTS conduct MONITORING, ASSESSMENT, AND RESEARCH that generates DATA ASSETS. Through the application of business, computational, and analytical processes and technologies, these data assets are converted into INFORMATION products that contribute to our KNOWLEDGE and understanding of the Earth's physical and biological systems.