Informatics approaches as basis for integrating science and governance across scales in complex networks of large marine ecosystems.

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Authors:Peter Fox

Abstract:

The many scales encountered in assessing and managing large marine ecosystems (LMEs) presents a level of diversity and heterogeneity, or complexity, presents a challenge to those diverse stakeholders and contributors (spanning the spectrum from the general public through decision makers and on to scientists). In turn, the knowledge network of LMEs is necessarily complex, i.e. there is not one overall 'categorization, or typing' of LMEs. The clear and overarching goal is to sustainable governance (broadly cast) of LMEs based on the best science; data and information. Forms of vertical integration will be presented in this contribution, as will the ways in which stakeholder identities and roles are preserved and respected. The basis for maxmizing potential for success lies in the application of modern informatics theory and practice, including use cases, information modeling, and scalable multi-modal network design. The presentation will outline what the resulting virtual organization may look like, and conclude with some tactical steps now that the immediacy of ecosystem based management of the oceans is apparent world wide.

History

DateCreated ByLink
November 29, 2014
17:34:08
Peter FoxDownload

Related Projects:

DCO-DS LogoDeep Carbon Observatory Data Science (DCO-DS)
Principal Investigator: Peter Fox
Co Investigator: John S. Erickson and Jim Hendler
Description: Given this increasing data deluge, it is clear that each of the Directorates in the Deep Carbon Observatory face diverse data science and data management needs to fulfill both their decadal strategic objectives and their day-to-day tasks. This project will assess in detail the data science and data management needs for each DCO directorate and for the DCO as a whole, using a combination of informatics methods; use case development, requirements analysis, inventories and interviews.
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.

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:
Knowledge Provenance
Lead Professor: Deborah L. McGuinness
Description: Knowledge Provenance
Concepts: Provenance,