Facilitating Next Generation Science Collaboration: Respecting and Mediating Vocabularies with Semantics in Ecosystems Assessments.

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Presented at the AGU Fall Meeting 2011

Abstract:

A newly funded initiative is developing and deploying an integrated ecosystem assessment (IEA) system using an information science and semantic technologies. The intention is to advance the capacity of an IEA to provide the foundation for synthesis and quantitative analysis of natural and socio-economic ecosystem information to support ecosystem-based management. In particular, the initiative is create the capacity to assess the impacts of changing climate on two large marine ecosystems: the northeast U.S. and the California Current. These assessments will be essential parts of the science-based decision-support tools used to develop adaptive management measures. Enhanced collaboration is required to achieve these goals: interaction and information sharing within and among diverse data providers, analysis tool developers and user groups that constitute the broader coastal and marine ecosystem science application community. This presentation indicates how semantic solutions are fundamental to this initiative.

History

DateCreated ByLink
December 7, 2011
18:01:28
Peter FoxDownload

Related Projects:

ECOOP LogoEmploying Cyber Infrastructure Data Technologies to Facilitate IEA for Climate Impacts in NE & CA LME's (ECO-OP)
Principal Investigator: Peter Fox
Co Investigator: Andrew Maffei
Description: The purpose of this INTEROP proposal is to facilitate the deployment of an Integrated Ecosystem Approach (IEA) to management in the Northeast and California Current Large Marine Ecosystems (LMEs). The direct result of the proposed activity will be application-level data and information enhanced communication for developing the consensus networks to define the specific components of interest to support the implementation of NOAA’s Driver-Pressure-State-Impact Response framework (DPSIR) decision framework and the cyberinfrastructure technologies to ensure data interoperability and reuse.
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.

Related Research Areas:

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: