What if all you had to do was asking the right scientific question?

The Scientific community spends a disproportionate amount of time developing ad-hoc solutions for scientific data-management, cleaning, and analysis pipelines. We conduct research in siloed, isolated environments and even though we know that significant advances in science will require extensive collaboration and cross-modal data integration, we are often struggling with finding the right tools to make this happen in a meaningful, scalable, and sustainable way.

Biomedical Informatics can provide the next generation scientists and clinicians with the tools to cut through these barriers. To enable them to look at all data in context and to provide intuitive, scalable and sustainable mechanisms for data visualization, exploration, discovery, and analysis.

Our vision is a world where scientific data is transparent. This does not mean that all data is freely available, or made public by default. Instead, it means that there are platforms and technologies that connect the right data to the right people at the right time. It means that we shift from siloed research and mandated data sharing to a paradigm where augmented collaboration through technology significantly accelerates our pace of scientific discovery.

Why this matters:

Data sharing is not just something the NIH mandates or the act of making files publicly available.

Meaningful data sharing is synonymous with creating effective collaborations and increased scientific impact. However, scalable infrastructure and tools to support this are sparse, which prevents meaningful exchange of information within the research community.

FAIR data does not mean free data and we need to work on developing data ecosystems that are both scalable and sustainable. This is far from trivial and requires significant effort and understanding of both technological as well as process related challenges that currently exist.

Novel insights in clinical and research data will result from deeply annotating and linking complex data, and having meaningful mechanisms to query and visualize results.

Biomedical Informatics can provide solutions to bridge the gap between clinicians, scientists and patients. We do this by creating platforms and tools that solve real problems and by having a thorough understanding of the workflows that we are integrating with.

Biomedical software is going to be the next big step towards improving patient care. As with the medical device industry, this will require significant engineering, updated policies, and commitment from federal institutions, academic- and industry partners.

Scientific collaboration is a global strategy to advance our understanding of disease and Neuroscience. It spans countries, and continents. We can leverage cloud-based technologies to foster collaborations and spur new collaborations that were not possible before.

Thorough integration of distributed data is key to significantly impact the pace of scientific progress. We need better mechanisms to support reproducible workflows, and tools to allow non-informaticians to leverage state of the art data-science methodologies.

Given the complexities and scale of scientific and clinical data, novel data ecosystems need to exists within the cloud, and we need to move away from the notion of processing data locally.