eScience Concept

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Description: Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.

Projects:
DCO-DS LogoDeep Carbon Observatory Data Science (DCO-DS)
Principal Investigator: Peter Fox
Co Investigator: John S. Erickson and Jim Hendler
Description: Given this increasing data deluge, it is clear that each of the Directorates in the Deep Carbon Observatory face diverse data science and data management needs to fulfill both their decadal strategic objectives and their day-to-day tasks. This project will assess in detail the data science and data management needs for each DCO directorate and for the DCO as a whole, using a combination of informatics methods; use case development, requirements analysis, inventories and interviews.
Health Data Challenge (HealthData)
Principal Investigator: Deborah L. McGuinness and Jim Hendler
Co Investigator: Kristine Gloria, Alvaro Graves, Tim Lebo, and James McCusker
Description: An infrastructure for large-scale collaboration around aggregation, generation, and publication of health-related Linked Data.
MBVL Project LogoMarine Biodiversity Virtual Laboratory (MBVL)
Principal Investigator: Peter Fox, David Mark Welch, Heidi Sosik, and Stace Beaulieu
Description: This research effort brings together computational and information scientists, oceanographers and microbiologists to develop a Marine Biodiversity Virtual Laboratory (MBVL). In addition to research investigations of marine ecosystems, the Virtual Laboratory provides a platform for education via student diversity programs at the three institutions. The important learning opportunities will be two-fold for students: (1) to learn about, model, and make predictions for biodiversity in natural systems, and (2) to be exposed to working in an interdisciplinary team that includes both natural scientists and computer scientists.
Mobile Health Project LogoMobile Health
Principal Investigator: Deborah L. McGuinness
Description: The Mobile Health project aims to bring semantic representations of medical data collected from a variety of consumer and medical grade devices and integrate those data on an individual's mobile smartphone. Combined with the reasoning capabilities of semantic web and technologies such as IBM Watson, this project plans to enable personalized health care through the instrumented self.
TW LogoNightingale: Proactive Depression Treatment with Individual Social, Sensory and Virtual Technologies. (Nightingale)
Principal Investigator: Jonas Braasch, Joanne S. Luciano, and Mei Si
Description: Depression costs! Each year, billions of dollars are wasted and millions of lives are disrupted because depression is complex, access is limited, treatments are one-size-fits-all, and therapies are trial and error. Nightingale aims to develop innovative solutions using social machines, virtual reality, and pervasive sensor technologies. The goals are: (1) predict an upcoming depression based on personalized features and cognitive modeling, (2) intervene using intelligent synthetic characters and augmented realities with telepresence capabilities for therapists, and (3) provide intelligent tools to users to inform themselves about their condition. Nightingale monitors the user using non-invasive cameras and biosensors, web-based weather data and information about the user’s daily activities. Nightingale intervenes with constructive suggestions, a positive environment, or an alert that medical help is needed. Together, these solutions can better target the right treatments for the right patients at the right time.
data.rpi.edu Project LogoRensselaer Polytechnic Institute Data Services (Data.rpi.edu)
Principal Investigator: Peter Fox and Jim Hendler
Description: Providing data storage, data services, data access, data discovery, data search, and data lifecycle and management for RPI research projects.
SEMMDD LogoSemantically Enabled Modeling of Major Depressive Disorder (SEMMDD)
Principal Investigator: Joanne S. Luciano
Description: In this project, we study the effects of how different antidepressant treatments, including non-pharmacological treatments, affect the underlying brain regions, clinical symptoms, and behaviors. We use mathematical modeling and computer simulation to combine clinical research with neuroscience research.
People:
Peter Fox

Peter Fox is a Tetherless World Constellation Chair and Professor of Earth and Environmental Science, Computer Science and Cognitive Science at Rensselaer Polytechnic Institute. Fox also directs the Insitution-wide interdisciplinary Information Technology and Web Science program. Previously, he was [...]

Deborah L. McGuinness

Dr. Deborah McGuinness is a leading expert in knowledge representation and reasoning languages and systems and has worked in ontology creation and evolution environments for over 20 years. Most recently, Deborah is best known for her leadership role in semantic web research [...]

Patrick West

Patrick West is a senior full-stack web developer at Workday Inc. He is currently responsible for the design and development of full-stack web applications in support of the various applications provided by Workday including HR and Payroll support applications. Previously Patrick was the princip [...]

Stephan Zednik

Stephan Zednik is a Senior Software Engineer with the Tetherless World Constellation at Rensselaer Polytechnic Institute. His research interests include researcher collaboration networks, quality representation and semantics, and provenance representation from data science tools. Stephan partici [...]

Research Areas:
Data Frameworks
Lead Professor: Peter Fox
Description: None.
Concepts: eScience
Data Science
Lead Professor: Peter Fox
Description: Science has fully entered a new mode of operation. Data science is advancing inductive conduct of science driven by the greater volumes, complexity and heterogeneity of data being made available over the Internet. Data science combines of aspects of data management, library science, computer science, and physical science using supporting cyberinfrastructure and information technology. As such it is changing the way all of these disciplines do both their individual and collaborative work.

Data science is helping scienists face new global problems of a magnitude, complexity and interdisciplinary nature whose progress is presently limited by lack of available tools and a fully trained and agile workforce.

At present, there is a lack formal training in the key cognitive and skill areas that would enable graduates to become key participants in escience collaborations. The need is to teach key methodologies in application areas based on real research experience and build a skill-set.

At the heart of this new way of doing science, especially experimental and observational science but also increasingly computational science, is the generation of data.

Concepts: eScience
Semantic eScience
Lead Professor: Peter Fox
Description:
Science has fully entered a new mode of operation. E-science, defined as a combination of science, informatics, computer science, cyberinfrastructure and information technology is changing the way all of these disciplines do both their individual and collaborative work.
As semantic technologies have been gaining momentum in various e-Science areas (for example, W3C's new interest group for semantic web health care and life science), it is important to offer semantic-based methodologies, tools, middleware to facilitate scientific knowledge modeling, logical-based hypothesis checking, semantic data integration and application composition, integrated knowledge discovery and data analyzing for different e-Science applications.
Partially influenced by the Artificial Intelligence community, the Semantic Web researchers have largely focused on formal aspects of semantic representation languages or general-purpose semantic application development, with inadequate consideration of requirements from specific science areas. On the other hand, general science researchers are growing ever more dependent on the web, but they have no coherent agenda for exploring the emerging trends on the semantic web technologies. It urgently requires the development of a multi-disciplinary field to foster the growth and development of e-Science applications based on the semantic technologies and related knowledge-based approaches.

Concepts: eScience
X-informatics
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: Semantic Web, eScience