Big Data
Big data is a term for data sets that are so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, querying, updating and information privacy. The term often refers simply to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set.[2] Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency, cost reduction and reduced risk.
Health Analytics Consortium
The Health Analytics Consortium (HAC) is an open incubator for collaboration and digital scholarship that emphasizes team-based transdisciplinary data science and advanced health analytics. A core mission of HAC is to foster integration of innovative research, development, education and training, and outreach in data and health sciences.
University of Michigan Institute for Healthcare Policy and Innovation Data Sets
The University of Michigan Health System provides leadership and support of “Collaborative Quality Initiatives” (CQIs) which seek to address some of the most common, complex, and costly areas of surgical and medical care. CQI Coordinating Centers, led by UMHS faculty, work collaboratively with health care providers throughout Michigan to collect data to a centralized registry; analyze and share data to identify processes that lead to improved delivery of care and outcomes, and guide quality improvement interventions.
SOCR Datasets: Examples of Biomedical, Health, Imaging, Economic and Biosocial Data
This is an open-access archive of a diverse collection of datasets that can be used for demonstrations, algorithm development, instrument testing, exploratory analytics and hands-on experiential practice of data-driven inference. The data are classified by type. Meta-data is provided to frame the information into the scope of specific driving motivational challenges. Observed and simulated data are included in the SOCR Data archive. The data can be redistributed (CC-BY).
Applied Biostatistics Laboratory (ABL)
ABL consults and collaborates with investigative teams in nursing, contributing their expertise to the designing of experiments, statistical analysis planning (including sample size justification), statistical analysis in support of grants, and preparing/submitting grant proposals.
LORIS
(Longitudinal Online Research and Imaging System) is a web-based data and project management software for neuroimaging research studies. It is an OPEN SOURCE framework for storing and processing behavioural, clinical, neuroimaging and genetic data. LORIS also makes it easy to manage large datasets acquired over time in a longitudinal study, or at different locations in a large multi-site study.
XNAT
XNAT is an open source imaging informatics platform, developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. Learn more here
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