Translating data into discoveries
Human survival has always hinged on the ability to translate visual signals into patterns, trends, and correlations. In the age of big data, this aptitude has proven effective at turning data into life-saving discoveries.
Part art, part science, big data visualization combines software, statistics, and science through storytelling. When told well, these stories have the power to illuminate, inspire, and most importantly, lead to new biologic and therapeutic insights.
Infusing promising labs with big data expertise
Researchers associated with the Fred Hutchinson/University of Washington Cancer Consortium are eligible to work with our team. Once a quarter our steering committee meets to determine which project(s) would be the most impactful. Once awarded, the research lab is infused with data visualization, engineering and data science resources. In addition to accelerating research, these engagements expose researchers to new approaches, technologies and people - strengthening the broader research community in the Seattle area.
Keep moving together
Seattle is home to world-renowned research institutions and technology giants, and together this provides tremendous opportunities for solving the underpinnings of disease. When scientists and software engineers operate collectively under the umbrella of open science, we find access to data and methods at a scale like never before. Fred Hutch Data Visualization supports open science by making all products free and accessible via open source licensing. See our local partners supporting this initiative.
Drawing conclusions from data
To extract meaning from a corpus of omics data that doubles every seven months require new technologies and new ways of seeing things. Leveraging over 30 years of experience in user experience, interaction, and motion design, our team applies cutting edge web technologies to distill and disseminate the knowledge embedded in scientific datasets.
Extracting signals from noise
Data Analysis is the process of systematically applying statistical and/or logical techniques to describe and illustrate, condense and evaluate data. Best-in-class analysis of research data often requires domain-specific expertise to ask the right questions on any given dataset. Over the years, we have gained experience working with a variety of scientific data types. More importantly, we have established relationships with many of the brightest data scientists in the greater Seattle area.
Big Data Infrastructure
Data engineers are the designers, builders and managers of the information. As data scientists answer questions from large sets of data, they need robust systems for collecting and validating that information. Over time, our team has established a catalog of data and computational resources that allow us to focus the majority of our time on project-specific data. To vet and scale our solutions, we partner closely with the Hutch Data Commonwealth and Scientific Computing programs.