Lighting Talk-D1 AHM Semantics-MAY2014

Printer-friendly version

Abstract:

History

DateCreated ByLink
November 5, 2014
14:49:05
Xixi LuoDownload

Related Projects:

DataONE Semantics LogoDataONE Semantics (D1-Semantics)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Matt Jones, Ben Leinfelder, Xixi Luo, and Mark Schildhauer
Description: Semantic search on measurements will enable precise data discovery by helping users identify relevant content from the massive and heterogeneous catalog in DataONE, thereby improving efficiency and opportunities for researchers and other data consumers.
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.

Related Research Areas:

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:
Ontology Engineering Environments
Lead Professor: Deborah L. McGuinness
Description: Ontology Engineering Environments
Concepts: Semantic Web