The integrated ecosystems assessment initiative—enabling the assessment of impacts on large marine ecosystems: informatics to the forefront of science‐based decision support

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Abstract:

What has been lacking, until recently, is a successful method to develop, implement, and sustain informatics solutions to modern application problems, such as environmental and climate assessments, that provide interoperability among diverse and heterogeneous data and information sources, as well as multidisciplinary organizations and people. This approach is directed toward an integrated ecosystem assessment for marine fisheries. The objective is to enable routine, integrated ecosystem assessments and forecasts, including impacts related to climate change and the capacity to address vulnerability, risks, and resiliency, and to develop an outcome‐based process that results in informed trade‐offs and priority setting. The goal is to bring ocean informatics to the forefront as an essential tool for implementing this new national policy framework and advancing the capacity for science in support of ecosystem‐based management, large marine ecosystems, as well as integrated ecosystem assessments. Existing data will be leveraged via semantic web technologies to capture knowledge. These technologies can leverage extant vocabularies and data repositories used by the stakeholders and define the meaning of that data by providing language constructs understood by computers that closely reflect how people think and pose questions of the data. Central to the success of this initiative is the commitment to train a new generation of scientists who will learn to interact effectively with this new integrated and interoperable ecosystem assessment capability.

History

DateCreated ByLink
October 8, 2012
14:36:02
Massimo Di Stefano Download

Related Projects:

ECO-OPEmploying 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.

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: eScience
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
X-informatics
Lead Professor: Peter Fox
Description: In the last 2-3 years, Informatics has attained greater visibility across a broad range of disciplines, especially in light of great successes in bio- and biomedical-informatics and significant challenges in the explosion of data and information resources. Xinformatics is intended to provide both the common informatics knowledge as well as how it is implemented in specific disciplines, e.g. X=astro, geo, chem, etc. Informatics' theoretical basis arises from information science, cognitive science, social science, library science as well as computer science. As such, it aggregates these studies and adds both the practice of information processing, and the engineering of information systems.
Concepts: , eScience