Minnesota Population Center Science and Technical Core

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Summary Statement: Scientific/Technical Core The MPC Scientific/Technical Core (STC) aims to advance research in population dynamics by providing services in computing and software development, spatial analysis, and data science. STC provides expertise to investigators designing new projects, coordinates technical support of ongoing research projects, and helps investigators master advanced methods and technologies. In past MPC center grant proposals, these three areas were separate cores. The STC consolidates these functions into a single core to reduce redundant effort, maximize administrative efficiency, and better coordinate services. This model allows MPC to employ the most advanced development tools and design standards available, giving us a leading role in demographic data management. Computing and software development services include the development of new software for consistency checking, automated data cleaning and editing, sampling, disclosure control, database harmonization, metadata creation and parsing, and web-based tools for documentation browsing, extraction, and analysis as well as systems administration. Spatial analysis services include training in GIS and spatial statistics, data preparation, data analysis, and data visualization. Data sciences services include data retrieval and preparation; design and development of data integration and dissemination projects; and data coding, cleaning, and preparation. Center grant support of the STC is highly cost-effective, providing research projects with shared resources that could not be efficiently supported by any single project. Investigators have access to specialists for each aspect of their project—such as database design, geocoding, or metadata design—that they could never afford to hire on their own. For example, many projects cannot afford a full-time user experience specialist, but they nevertheless need some user design services. MPC’s model of centralized technical services can provide far better support than could be obtained from a part-time developer hired on a short-term basis. The model increases the impact and pace of population science conducted at the Center in three ways: 1) by maximizing the fit between technical expertise and project needs; 2) by maintaining a pool of talented software developers, GIS experts, and data scientists with experience working with demographic datasets; and 3) by minimizing startup time for new projects.