Data science is “the interdisciplinary field of inquiry in which quantitative and analytical approaches, processes, and systems are developed and used to extract knowledge and insights from increasingly large and/or complex sets of data” (NIH Strategic Plan for Data Science).
From the National Institutes of Health National Cancer Insitute: "Implementation science is the study of methods to promote the adoption and integration of evidence-based practices, interventions, and policies into routine health care and public health settings to improve the impact on population health."
A design methodology that provides a solution-based approach to solving problems. It’s extremely useful in tackling complex problems that are ill-defined or unknown, by understanding the human needs involved, by re-framing the problem in human-centric ways, by creating many ideas in brainstorming sessions, and by adopting a hands-on approach in prototyping and testing (Rikke Friis Dam and Yu Siang Teo, Interaction design foundation).
Systems science is an interdisciplinary approach to studying the nature of systems at a variety of scales and levels of complexity. Systems science efforts at BCSSW will focus on three interrelated areas: research and practice, education, and partnerships.
We will expand on our growing body of systems research to address complex societal problems in Boston and around the globe and continue to build a community of practice with partner organizations, students, faculty and staff. This will include building the capacity of students, faculty, staff, and key organizations to use systems science through courses, skill labs, and partnership development.
Translational science is "the field of investigation focused on understanding the scientific and operational principles underlying each step of the translational process," where the translational process represents "turning observations in the laboratory, clinic and community into interventions that improve the health of individuals and the public—from diagnostics and therapeutics to medical procedures and behavioral changes" (National Institutes of Health National Center for Advancing Translational Sciences).
Many seemingly intractable social problems are embedded in complex systems. Often attempts to understand and solve these problems fail or have unintended consequences. Community-based system dynamics (CBSD) is a participatory approach for engaging communities in the process of understanding and changing systems from the perspective of system dynamics. CBSD puts the perspectives of communities experiencing social problems at the fore to advance the common good.
Through informal maps and formal simulation models, CBSD explores how components in a system connect and feedback into one another to shape system behavior. CBSD provides the tools for communities to visualize complexity, generate deeper understanding of complex social problems, and identify leverage points for robust solution design and implementation at scale.
- They are made up of a large number of heterogeneous elements.
- These elements interact with each other.
- The interactions produce an emergent effect that is different from the effects of the individual elements.
- This effect persists over time and adapts to changing circumstances.
- System dynamics: Uses informal and formal models with computer simulation to uncover and understand endogenous sources of complex system behavior.
- Netong actors, including people, organizations and other information processing entities.
- Agent-based modeling: Uses computer simulations to examine how elements of a system (agents) behave as a function of their interactions with each other and their environment.work analysis: The measurement and analysis of relationships and flows am