Semantic eScience Projects

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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.
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.
TW LogoSemantic Data Dictionaries (SDD)
Principal Investigator: Deborah L. McGuinness
Co Investigator: James McCusker
Description: A methodology building on existing data dictionaries in order to describe entities, attributes, and relationships in data sets through the Semanticscience Integrated Ontology (SIO) and relevant domain ontologies. Semantic Data Dictionaries are being developed in support of other projects, including CHEAR.
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.