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IOOC Observational Network (ION) Project

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The IOOC Organizational Network (ION) is a project aimed at organizing the relationships between ocean observing institutions and groups. The initial ION data and visualizations were completed using Gephi Software, which is an open graph and visualization platform.  The links below reflect outcomes from this initial analysis.

Network analysis is valuable in the context of large organizational problems and can provide a tool to identify information needs within the network of organizations, as well as a clearer understanding of the impacts of current network structures on operations beyond organizational boundaries.  By coding for number of relationships or types of relationships, network analysis can indicate centrality of certain players, providing a powerful tool for determining those pathways that will most effectively disseminate information, messaging, or action items.

International Database

National Database

In order to build the current database of information on ocean observing networks at the national and international level, the analyst conducted online legal research, and visited each organization/agency website to find legal instruments and documents that reflected relationships between agencies and between global organizations, as well as policy documents and mission statements that contained information on the players basic interest or involvement in the 26 Core IOOS variables.  Based on this research, the data was binned and coded in multiple ways.

Partnership strengths were binned according to a Collaboration, Coordination, Cooperation scale found in use by U.S. agencies and in literature on categorizing organizational relationship strengths (Mandell, 2007).  At the national scale, relationships were binned according to the kind of legal instrument utilized, and these instruments were further binned on the three C’s scale outlined above:

Weight

Category

Legal Instruments

1

Cooperation

Program, Work Plan, Working Group

2

Coordination

MOU, MOA, Charter, Policy

3

Collaboration

Law, Agency, Executive Order

At the international and national levels, relationships were also binned by four categories reflecting a broad understanding of the nature of the relationship (Wagner, 2005):

Relationship Type

Description

Data

Relationships categorized under “Data” are those in which the primary purpose is to share data, or provide complementary data analysis.  The products of Data relationships could be co-managed databases, international co-authorships, and contribution to ongoing data sets.

Infrastructure

Relationships categorized under “Infrastructure” are those in which the primary purpose of the partnership is to maintain high cost equipment (e.g. research vessels, buoys) or maintain long-term research projects that depend on access to high cost equipment and therefore depend on partnerships that can pool funding resources and and create greater stability.

Human Resources

Partnerships categorized under “Human Resources” involve relationships whose primary purpose is to share and gain access to scarce or unique resources, which could include funding, access to unique expertise or skills, and access to administrative support (Bammer, 2008).

Communications

Relationships categorized under “Communications” imply a focus on enhancing the exposure of research, ocean observations, and ocean policy among organizations and out to a public audience.  Activities include increasing messaging capacity and developing guidance materials for inter-organizational operations.

 

Bibliography

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  2. Anderson, D.M. et al., Harmful Algal Bloom (HAB) Sensors in Ocean Observing Systems, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

  3. Block, B.A. et al., Toward a U.S. Animal Telemetry Observing Network (US ATN) for our Oceans, Coasts, and Great Lakes, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

  4. Alexander, C., Priorities for IOOS Data Management and Communications (DMAC)

  5. Anderson, D.M. et al., Harmful Algal Bloom (HAB) Sensors in Ocean Observing Systems, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

  6. Bailey, B.H. et al., The Need for Improved Met-Ocean Data to Facilitate Offshore Renewable energy Development, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

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  17. Kudela, R.M., et al. Leveraging Ocean Observatories to Monitor and Forecast Harmful Algal Blooms: A Case Study of the U.S. West Coast, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

  18. Leonard, L., et al., Identifying Stakeholder Driven User Needs: Lessons Learned in the Southeast, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

  19. Rosenfield, L. et al., IOOS Modeling Subsystem: Vision and Implementation Strategy, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

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  21. Simoniello, C. et al., Creating Education and Outreach Opportunities for the U.S. IOOS, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

  22. Tronvig, K.A. et al., Interagency Collaboration for Operationalizing Datums Standards, IOOS Summit Whitepaper (2012), available at http://www.iooc.us/activities/white-paper-guidelines/.

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  31. Bammer, G. (2008). Enhancing research collaborations: three key management challenges. Research Policy, 37(5), 875-887.

  32. Mandell, Myrna and Robyn Keast (2007). Evaluating Network Arrangements: Toward Revised Performance Measures. Public Performance & Management Review, 30(4), 574-597.