Semantic Data Frameworks Come of Age

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Presented at the Astroinformatics 2011

Authors:Peter Fox

Abstract:

History

DateCreated ByLink
September 26, 2011
20:23:32
Peter FoxDownload

Related Projects:

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.
SeSF Project LogoSemantic eScience Framework (SeSF)
Principal Investigator: Peter Fox
Co Investigator: Jim Hendler and Deborah L. McGuinness
Description: Over the past few years, semantic technologies have evolved and new tools are appearing. Part of the effort in this project will be to accommodate these advances in the new framework and lay out a sustainable software path for the (certain) technical advances. In addition to a generalization of the current data science interface, we will include an upper-level interface suitable for use by clearinghouses, and/or educational portals, digital libraries, and other disciplines.
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.
DCO-DS LogoVirtual Solar Terrestrial Observatory (VSTO)
Principal Investigator: Peter Fox
Co Investigator: Deborah L. McGuinness
Description: VSTO is a collaborative project between the High Altitude Observatory and Scientific Computing Division of the National Center for Atmospheric Research and McGuinness Associates. VSTO is funded by a grant from the National Science Foundation, Computer and Information Science and Engineering (CISE) in the Shared Cyberinfrastructure (SCI) division.

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