Jurgen Schulze - US grants

Multi-scale, multi-modal, multi-site science, such as terrestrial observatories and other dynamic and adaptive sensor-based application, high resolution sub-cellular imaging, or genomic analyses of communities of organisms, builds large data sets that can serve as the basis for in silico exploration and analysis. Often the data collections represent a wide range of disciplines, yet there are often a limited number of interpretations, guided by an individual scientist?s expertise. Intuitive exploration that transcends disciplinary boundaries and expertise could enhance the process of interdisciplinary collaboration, as well as drive the process of discovery in new directions. This proposal seeks to develop a dynamic metadata-based approach for intuitive, interactive, and immersive multi-scale, multi-modal data exploration application to a wide range of data sets and their associated metadata. The original focus will be on metagenomics data from the Global Ocean Survey. The development of the environment will enable a different dynamic sorting and sifting of data rather than relying solely on known or expected features. Such open-ended exploration occurs not only in observational science, but also in tasks ranging from network intrusion detection. Students will be engaged in the research and collaboration, with dissemination in public cultural activities, as well as through more traditional academic venues.

Proposal #: 13-38192
PI(s): Kuester, Falko; DeFanti, Thomas A.; Rosing, Tajana S.; Schulze, Jurgen P.
Institution: University of California - San Diego
Title: MRI/Dev.: Advanced Visualization Instrumentation for the Collaborative Exploration of Big Data
Project Proposed:
This project, developing a Scalable Omni-Presence Environment (ScOPE), a next generation visualization system for collaborative exploration of large volumes of data, provides an environment for analyzing, processing, and visualizing Big Data resulting from many different areas of science and engineering. The instrument serves as an integrative, virtual metaphor for a combined microscope and telescope, enabling users to explore data from the nano to macro to mega scale. ScOPE provides researchers the ability to study simulated and acquired data at a level of precision previously unmatched. It is expected to become the platform for training a new generation of users to be fluent in data analytics in collaborative environments. Initially, three universities will have direct access to the ScOPE instrument and all its features: U. California-San Diego (UCSD), Jackson State U. (JSU), and U of Texas Medical Branch (UTMB). Nonetheless, following the tradition of the project team (effectively done with earlier generations of visualization technologies (e.g., OptIPortal tile display walls now installed at more than 100 institutions worldwide), the critical components of the infrastructure will be broken such that they may be replicated for use at remote locations by other research or educational institutions. The developers anticipate that private-sector collaborators, such as Qualcomm and Intel, will help popularize use of specific components for the nation?s big-data analytics infrastructure. Notwithstanding, the broadest impact of the instrument should be evident in the discoveries and advances made by engineers and scientist that use ScOPE to enhance collaboration and analysis in the disciplines that have been singled out as ?Domain Drivers? for the project. These include projects led by researchers in ocean sciences (and ocean observatories); cyber-archaeology and cultural heritage diagnostics; real-time brain imaging; digital cinema and very-high quality digital media; integrative computational biology; underwater microscopy; molecular dynamics; structural biology and computational chemistry; and large-scale numerical simulation. In turn, these domain specialists will work alongside computer scientists who will address grand challenges in system architecture, data transport, security, representation, arching, processing multi-modal analytics, and human-computer interaction. ScOPE?s long-distance collaboration will be supported by telepresence at bandwidths ranging up to 40 Gigabits per second. Thus, the project creates a highly interactive collaboration space equipped with a natural human-computer interface and advanced 3D modeling and rendering at a sufficient scale to tackle complex experiments and analyze large amount of visual and numerical data pertaining to phenomena of wide dimensions and extreme time scales. Domain drivers have been identified to ensure that the resulting environment and tools are applicable to a broad array of scientific disciplines. These include earth system sciences, civil and structural engineering, mechanical and aerospace engineering, biomedical and electrical (and ocean observatories engineering, social sciences, and anthropology. This project takes a great leap forward into a new generation of collaborative environment that until recently was unthinkable. The display capabilities will no longer be passive; envisioned is a continuous spatial workspace imaging, including eye, skin response, and even mobile electroencephalography sensing, allowing ScOPE to respond to and infer user intent. The environment will be designed specifically to handle ?big data,? using a failure-tolerant and cloud-centric approach while also downsizing the supercomputer flash memory architecture. ?Big Data.? The instrument will enable scientific discoveries as well as research on how best to process, analyze, and visualize Scope will serve as a prototype for other similar instruments. The research enabled by ScOPE will have impacts in many areas of science.
Broader Impacts:
As previously mentioned, the ScOPE instrument provides researchers the ability to study simulated and acquired data at a level of precision previously unmatched. ScOPE is expected to become the platform for training a new generation of users to be fluent in data analytics in collaborative environments. The developers anticipate that private-sector collaborators, such as Qualcomm and Intel, will help popularize the use of specific components for the nation?s big-data analytics infrastructure. Notwithstanding, the broadest impact of the instrument should be evident in the discoveries and advances made by engineers and scientist that use ScOPE to enhance collaboration and analysis in the disciplines that have been singled out as ?Domain Drivers? for the project. These include projects led by researchers in ocean sciences (and ocean observatories); cyber-archaeology and cultural heritage diagnostics; real-time brain imaging; digital cinema and very-high quality digital media; integrative computational biology; underwater microscopy; molecular dynamics; structural biology and computational chemistry; and large-scale numerical simulation. In turn, these domain specialists will work alongside computer scientists who will address grand challenges in system architecture, data transport, security, representation, arching, processing multi-modal analytics, and human-computer interaction. The instrument will have direct impact on three universities, while the technology developed in building the instrument will inform the construction of similar instruments around the nation. To promote greater public appreciation of scientific research, the public will be invited to tour the visualization facilities, hopefully encouraging young people to enter career in science and engineering. The area of ScOPE accessible to the public will have significant impact on the public?s impression of academic research. ScOPE?s capabilities are likely to transform our ability to collaborate with distributed research teams and be directly applied to day-to-day research.

The Planning Grants for Engineering Research Centers competition was run as a pilot solicitation within the ERC program. Planning grants are not required as part of the full ERC competition, but intended to build capacity among teams to plan for convergent, center-scale engineering research.

Improving the quality and efficiency of healthcare - at home, in long-term care facilities, and in hospitals - is becoming ever more important for patients and the society at large. Although the two current trends in healthcare - telemedicine and digital medicine - are making headway, they only scratch the surface of the problem as opposed to dealing with the root cause. To revolutionize healthcare delivery, we need a comprehensive biophysical patient model, namely a "digital twin", that fuses data streams, doctor notes/assessments, and medical histories with a rigorous computational engine that can make probabilistic predictions of future patient health/well-being. Healthcare providers will then be able to integrate traditional knowledge/training with the "data-to-decision" posture of the digital twin, while working with the patient, to best assess their health, evaluate options, predict future health, and optimize patient outcomes and prognosis. The aim of this Planning Grant is to engage and converge a broad stakeholder community of engineers, data scientists, educators, artists, medical specialists, hospitals, consulting firms, digital health firms, and health and government agencies to openly discuss and identify the most urgent engineering research, education, and outreach gaps that need to be addressed for revolutionizing medical decision-making and personalized medicine. Once the ERC is established, the team will partner closely with stakeholders to identify current issues in medical care, design and build engineering solutions, and deploy these solutions in phases after careful assessment of their effectiveness. It is through these activities that truly personalized medicine will be achieved, where cyber-physical healthcare monitoring can be tailored to specific patients as they are identified early at risk versus when severe complications unfold. Furthermore, the education and outreach initiatives of the CYBER-MD ERC will actively recruit women, underrepresented, and economically disadvantaged individuals for research and training future generations of multidisciplinary, convergent scientists and engineers.

Healthcare practice today only provides clinicians with limited amounts of historic patient data, and doctors tend to rely on outdated training and anecdotal experiences to best care for their patients. However, given the broad overlap in symptomatology across various diseases, missed diagnosis and misdiagnosis remains a major problem. The vision of the CYBRE-MD ERC is to establish a cyber-physical innovation hub, where engineering breakthroughs in bio-physical modeling, imaging, sensing, data science, data visualization, and probabilistic risk assessment methodologies collectively revolutionize the medical diagnostic/treatment process for improving patient outcomes. The cornerstone of this concept is a "digital twin" that is born and then evolves with the patient while constantly being updated over time with new data streams ranging from biometrics to illness/injury assessments to diagnostic images/results to subsequent treatments. The digital twin not only presents a new data architecture for storing patient health informatics, but it also provides transformative health assessment and predictive analytic capabilities that enable doctors and patients to work together to improve patient health, well-being, and outcomes. CYBER-MD is inherently transdisciplinary and spans the entire spectrum of science, technology, engineering, arts, and mathematics (STEAM) as well as all branches of medicine. This Planning Grant will convene diverse experts to converge on a final strategic implementation, define focused research grand challenges, identify relevant thematic areas, communicate with stakeholders, educate, devise innovative and broadly implementable education/outreach efforts, and assemble the most competent and diverse team that underpins this transdisciplinary NSF ERC. The activities planned directly support convergent research, which is of utmost necessity for tackling this overarching grand challenge that spans the fields of STEAM, medicine, healthcare, and public health/well-being.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.