Semantic eScience Projects

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CHEAR Project LogoChild Health Exposure Analysis Repository (CHEAR)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Kristin Bennett
Description: Child Health Exposure Analysis Repository Data Science Semantics
DOfAMP Project LogoDeveloping Ontologies for Additive Manufacturing Processes (DOfAMP)
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.
Jefferson Project at Lake George Project LogoE-Science Jefferson Project on Lake George (Jefferson Project)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Paulo Pinheiro
Description: The Jefferson Project at Lake George is building one of the world’s most sophisticated environmental monitoring and prediction systems, which will provide scientists and the community with a real-time picture of the health of the lake. Launched in June 2013, the project aims to understand and manage multiple complex factors—including road salt incursion, storm water runoff, and invasive species—all threatening one of the world’s most pristine natural ecosystems and an economic cornerstone of the New York tourism industry. The project is a three-year, multimillion-dollar collaboration between Rensselaer Polytechnic Institute, IBM, and The FUND for Lake George. The collaboration partners expect that the world-class scientific and technology facility at the Rensselaer Darrin Fresh Water Institute at Lake George will create a new model for predictive preservation and remediation of critical natural systems in Lake George, in New York, and ultimately around the world.
First Responders logoFirst Responders Requirements Metholodology (FirstResponders)
Principal Investigator: Deborah L. McGuinness
Co Investigator: John S. Erickson
Description: The purpose of this project is to design and prototype a requirements-gathering methodology driven by the first responders community. The methodology will include examining the current state of collecting and synthesizing responder requirements, assessing the effectiveness of that process, evaluating existing candidate platforms for use within this community, and producing a roadmap that can be used by NIST and others to achieve a solution enabling the responder community to more effectively dialogue with key stakeholders. A prototype implementation of the methodology will be developed using the roadmap and will be available for testing and evaluation and requirements gathering.
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.
Description: Tasks for various TWC projects related to data access and the OPeNDAP software products.
Repurposing Drugs with Semantics (ReDrugS)
Principal Investigator: Jonathan Dordick and Deborah L. McGuinness
Description: We aim to find new effective treatments for disease using existing drugs. Our approach is to gather and integrate existing data using semantic technologies to help discover promising drug repurposing.
SemantEco Annotator Project LogoSemantEco Annotator
Principal Investigator: Deborah L. McGuinness
Co Investigator: Patrice Seyed
Description: Generating useful RDF linked data is not a straightforward process for scientists using today's tools. In this project we introduce the SemantEco Annotator, a semantic web application that leverages community-based vocabularies and ontologies during the translation process itself to ease the process of drawing out implicit relationships in tabular data so that they may be immediately available for use within the LOD cloud. Our goal for the SemantEco Annotator is to make advanced RDF translation techniques available to the layperson.
SVF LogoSemantic Vernaculars for Fungi (SVF)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Nathan Wilson
Description: Fungi are typically referred to by either scientific or common names. Neither of these terminologies meets the need for well-defined, persistent definitions of groups of fungi who exhibit similar macroscopic qualities, but may be dissimilar genetically. We propose a community-developed vocabulary that can be used to identify mushrooms based on properties that can be observed in the field (without microscopic or genomic examination). We show how an ontology can be used to develop and organize the terms and definitions and to enable applications based on the vocabulary.
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.
S2S Project 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.
SESDI Project LogoSemantically-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. In many cases, syntax-only interoperability IS the state-of-the-art. In order for scientists and non-scientists to discover, access, and use data from unfamiliar sources, they are forced to learn details of the data schema, other people¿s naming schemes and syntax decisions. Our work is aimed at providing scientists with the option of describing what they are looking for in terms that are meaningful and natural to them, instead of in a syntax that is not. The missing element in enabling the higher-level interconnections is the technology of ontologies, ontology-equipped tools, and semantically aware interfaces between science components. Ontologies fill a major technology gap in machine-to-machine communication across multiple disciplines to advance Earth system science by enabling data integration without the need for human intervention. This project, the Semantically-Enabled Science Data Integration (SESDI), will demonstrate how ontologies implemented within existing distributed technology frameworks will provide essential, re-useable, and robust, support for an evolution to science measurement processing systems (or frameworks) as well as for data and information systems (or framework) support for NASA Science Focus Areas and Applications.
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.