Lessons in Building Effective Environmental Information Systems

1. How do you build an information system that works? Lessons from environmental case studies Karen I. Stocks San Diego Supercomputer Center kstocks@sdsc.edu Karen S. Baker Scripps Institution of Oceanography kbaker@ucsd.edu

2. Task: Forward Planning for CalCOFI“California Cooperative Oceanic Fisheries Investigations”

3. How do you build an information management system that works?

4. Insights from 4 Environmental Information Systems • CalCOFI (www.calcofi.org): • biological and physical oceanographic data • 50+ year time span • 2 institutions, centralized system • OBIS (Ocean Biogeographic Information System - www.iobis.org) • species distribution data • 5 years • international federation, distributed system • LTER (Long Term Ecological Research Network - www.lternet.edu) • broad array of ecological data • 24 years • 26 field sites nationally, distributed system • SeamountsOnline (seamounts.sdsc.edu) • species distribution data • 4 years • 1 person, centralized system

5. Our ConclusionInformation system projects (or project components) fail or succeed for organizational/social reasons as frequently as they fail or succeed for technical reasons

6. Lessons Learned • What have these four system case studies taught us? • What are the characteristics that foster success • What mechanisms create those characteristics

7. Characteristic: Sustainability • Mechanism: recognizing and providing rewards for • participation at the individual, project, and institution level • non-monetary rewards can be effective • Example: LTER learning community, OBIS editorial board titles

8. Characteristic: Participant Engagement Mechanism: consensus decision making (with hierarchical representation when needed for large bodies) Mechanism: seed resources available for allocation to participants

9. Characteristic: Usefulness of the System Mechanism (long-term): clearly articulated, focused project vision/goals produced with broad input from users and participants Mechanism (short-term): modular development with usable products at each step

10. Lessons from Science and Technology Studies: Myths and Realities NSF/Human Social Dynamics 2004-2007: Interoperability Strategies for Scientific Cyberinfrastructure: A Comparative Approach (Bowker and Baker)

11. Information System Design and Development • Myth: System development is linear: design, then implement, then finish • In practice: • complex feedbacks and interdependencies exist, development is iterative • - technological, organizational, and funding landscape constantly changing

12. Design for Flexibility Waterfall Model Spiral Model requirements Reflect and Plan Determine Objectives design implementation Evaluate alternatives Develop alternatives test Boehm, 1986. A Spiral Model of Software Development and Enhancement. ACM SIGSOFT Software Engineering Notes 11(4):14-24.

13. Participatory Design an approach to the design and development of technological and organizational systems that places a premium on the active involvement of workplace practitioners in design and decision-making processes. • Schuler and Namioka, 1993. Participatory Design: Principles and Practices. Hillsdale, NJ, Lawrence Erlbaum Associates • Letondal and Mackay, 2004. Participatory Programming and the Scope of Mutual Responsibility: Balancing Scientific, Design and Software Commitment. Proceedings Participatory Design Conference 2004, Toronto, Canada.

14. Organizational Concepts • Myth: Technology is objective - it gets used by an organization • In practice: • - enacting technology changes organizations Technology Work practice Technology Work practice Fountain, 2001

15. Understand the tensions open-source long-term science flexibility ecosystem view community outreach modeled observed inreach economic Species view standards short-term technology microsoft

16. New Organizational Models Integrated routine and knowledge work knowledge work routine work Traditional hierarchical structure Integrated horizontal structure And new roles: system architects, data managers, programmers

17. Managing Organizational Change Weick and Sutcliffe. 2001. Managing the Unexpected, Assuring High Performance in an Age of Complexity. Jossey-Bass • Recognize and define the new roles • Rewards for interdisciplinary and new roles • Professional development at all levels • Mixed representation on decision-making bodies

18. Reading List • Davenport, 1997. Information Ecology, Oxford University Press. New York. • Iivari, 1991. Paradigmatic Analysis of Contemporary Schools of IS Development. European Journal of Information Systems 1(4):249-272. • Jirotka and Goguen, 1994. Requirements Engineering: Social and Technical Issues. London, Academic Press. • Karasti and Baker, 2004. Infrastructuring for the Long-Term: Ecological Information Management, Proceeding of the Hawaii International Conference for System Science, Big Island, hawaii 5-8 Jan 2004. • Karasti and Syrjanen, 2004. Artful Infrastructuring in Two Cases of Community Participatory Design. Proceedings of the Participatory Design Conference, Toronto, Canada. • Star and Bowker, 2002. How to Infrastructure in The Handbook of New Media. Lievrouw and Livingstone (eds), SAGE Publications, London, p151-162. • Funding provided by the National Science Foundation Office of Polar Programs, and the NSF Social, Behavioral and Economic Sciences