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.
TW LogoDeep Time Data Infrastructure (DTDI)
Principal Investigator: Peter Fox
Description: Earth’s living and non-living components have co-evolved for 4 billion years through numerous positive and negative feedbacks. Yet our ability to document, model, and explore these complex intertwined changes has been hampered by a lack of data synthesis and integration from many complementary disciplines—mineralogy, petrology, paleobiology, geochronology, proteomics, geochemistry, and more. The rise of oxygen exemplifies the co-evolution of rocks and life, and underscores both the tantalizing opportunities and technical challenges of deciphering transient characteristics of Earth’s storied past.
Health Data Challenge (HealthData)
Principal Investigator: Jim Hendler and Deborah L. McGuinness
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.
TW LogoMaterials Processing Ontology (MPO)
Principal Investigator: Jim Hendler
Co Investigator: Peter Fox and Robert Hull
Description: We propose the development of the field of materials processing ontology so that the US establishes leadership in this critical technological arena. The goal is the development of a framework, language and algorithm set for organizing and categorizing the myriad relationships between materials processing, properties and structure. No ubiquitous framework currently exists for relating materials processing parameters to properties and structure that translates across multiple materials fields and technologies. In essence, an advanced “Dewey Decimal System” is needed for materials processing, such that data and knowledge that is developed in one materials processing technology can cross-pollinate across other materials technologies.
TW 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.
NOCV Project LogoNational Ocean Council Vocabulary (NOCV)
Description: The objective of the NOCV project is to demonstrate technical capabilities that are available and can be deployed to implement solutions to key needs identified in the National Ocean Policy in regard to data and the decision-support requirements that arise from data-oriented questions.
TW LogoNightingale: Proactive Depression Treatment with Individual Social, Sensory and Virtual Technologies. (Nightingale)
Principal Investigator: Joanne S. Luciano, Mei Si, and Jonas Braasch
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.
OPeNDAPOPeNDAP
Description: Tasks for various TWC projects related to data access and the OPeNDAP software products.
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.
SemantAQUA LogoSemantic Water Quality Portal (SemantAQUA)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Joanne S. Luciano
Description: We present a semantic technology-based approach to emerging environmental information systems. We used our linked data approach in the Tetherless World Constellation Semantic Water Quality Portal (TWC-SWQP). Our integration scheme uses a core domain ontology and integrates water data from different authoritative sources along with multiple regulation ontologies to enable pollution detection and monitoring. An OWL-based reasoning scheme identifies pollution events relative to user chosen regulations. Our approach also captures and leverages provenance to improve transparency. In addition, semantic water quality portal features provenance-based facet generation, query answering and data validation over the integrated data via SPARQL. We introduce the approach and the water portal, and highlight some of its potential impacts for the future of environmental monitoring systems.
TW LogoSemantically Enabled Facetd Browser (S2S)
Principal Investigator: Peter Fox
Co Investigator: Stephan Zednik
Description: S2S is a user interface framework that leverages the machine-readable semantics of data, services, and user interface components, or "widgets". S2S automates various tasks in UI development for search interfaces.
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.
Semantically-Enabled Science Data Integration (SESDI)
Principal Investigator: Peter Fox
Co Investigator: Deborah L. McGuinness
Description: The vast majority of explorations of the Earth system are limited in their ability to effectively explore the most important (often most difficult) problems because they are forced to interconnect at the data-element, or syntactic, level rather than at a higher scientific, or semantic, level.
TAF LogoThe Asthma Files (TAF)
Principal Investigator: Michael Fortun
Co Investigator: Kim Fortun and Peter Fox
Description: The Asthma Files is an electronic archive of text, still images, video and audio that illustrate multiple perspectives on asthma-- from the vantage point of affected people in different locales and communities, heath care providers, and scientists from many different disciplines.
ToolMatch LogoToolMatch (ToolMatch)
Description: or a given dataset, it is difficult to find the tools that can be used to work with the dataset. In many cases, the information that Tool A works with Dataset B is somewhere on the Web, but not in a readily identifiable or discoverable form. In other cases, particularly more generalized tools, the information does not exist at all, until somebody tries to use the tool on a given dataset. Thus, the simplest, most prevalent use case is for a user to search for the tools that can be used with a given dataset. A further refinement would be to specify what the tool can do with the dataset, e.g., read, visualize, map, analyze, reformat.
People:
Peter Fox

Peter Fox is a Tetherless World Constellation Chair and Professor of Earth and Environmental Science and Computer Science at Rensselaer Polytechnic Institute. Previously, he was Chief Computational Scientist at the High Altitude Observatory of the National Center for Atmospheric Research. Fox has a [...]

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 principal software engineer with the Tetherless World Constellation at Rensselaer Polytechnic Institute. His current projects are focused on the semantic expression of data science concepts and relationships in various domains, including solar, upper atmosphere, ocean science [...]

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