• Slides are available for the Second KNB Data Management Tools Workshop, which was held February 2-4, 2005.
• Slides are available for the First KNB Data Management Tools Workshop, which was held September 28-30, 2004.

To meet the Education, Outreach, and Training goals of the KNB project, we are implementing our plans to: 1) engage scientists, graduate students, and policy makers in appropriate phases of the design and development of the prototype knowledge network and associated tools; 2) widely disseminate the computer science and informatics products of our research to the scientific community; and 3) train scientists--especially young investigators--in the application of knowledge networking tools and computer-based approaches to data synthesis that generate new knowledge, particularly knowledge regarding biocomplexity.

Biocomplexity refers to phenomena that arise as a result of dynamic interactions within biological systems (including humans) and between these systems and the physical environment. It includes the structural and functional attributes of dynamic systems that arise at all levels of biological organization, including individuals, populations, and communities. Currently, ecological components of biocomplexity (e.g., biodiversity, ecosystem services) are in crisis, and are undergoing potentially irreversible changes in the face of rapid human population growth and economic development.

One major obstacle to understanding biocomplexity and other broad-scale or multidisciplinary areas of ecology is that the necessary data are difficult to identify, retrieve, and understand. Ecological and environmental data are typically heterogeneous in form, they reside in various locations, and may not be documented sufficiently to be useful to the community of ecological researchers.

To address these challenges, researchers at the National Center for Ecological Analysis and Synthesis (NCEAS), the LTER Network Office, San Diego Super Computer Center, and Texas Tech University have initiated research to develop a Knowledge Network for Biocomplexity (KNB). The KNB will integrate distributed and heterogeneous information sources that are required for the development and testing of theory in ecology and its sister fields. The KNB will provide conceptually sophisticated access to integrated data products drawn from distributed, autonomous data repositories. In addition, the KNB will include advanced tools for exploring complex data sets and to facilitate hypothesis testing with those data.

In a series of integrated, multi-campus graduate seminars, we will explore a variety of topics related to biocomplexity research and ecological synthesis. In addition, these seminars have been designed to provide a critical contribution to the development of the knowledge network. The first set of seminars will be offered at University of California Santa Barbara, University of New Mexico, and Texas Tech University in Winter 2001. The goals of these seminars are to: (1) involve students, faculty and other members of the ecological community in testing and designing the KNB; (2) allow participants to conduct research and prepare scientific publications on the scale-dependent nature of the relationship between species richness and productivity (this research will focus on synthesizing data from individual research sites); and, ultimately, (3) demonstrate the power of a collaborative, multi-scale, multidisciplinary approach to biocomplexity research.

Participants at each institution will collaborate on a research project that uses ecoinformatics tools and principles to investigate the relationship between species richness and productivity. They will assemble, synthesize, and analyze  previously existing data from a single ecosystem represented by a nearby research site. At the end of each seminar, the faculty leader and two students from each institution will have an opportunity to participate in cross-site synthesis and additional research through a working group at NCEAS in Santa Barbara.

Andelman, S.J., C.M Bowles, M.R. Willig and R.B. Waide. 2004. Understanding environmental complexity through a distributed knowledge network. BioScience 54(3):240-246.

• Biocomplexity: What is it & why and how do we study it?
• Why we need sophisticated computing tools to facilitate data synthesis and analysis
• Philosophy of knowledge in an information age
• The nature of synthesis and the synthesis of nature
• The culture of data sharing and how to accomplish multidisciplinary research
• Anatomy of knowledge networks, the KNB, and how to manage data and metadata
• Data entry and use of Morpho: Data Management for Ecologists software
• A general introduction to the biological questions and current controversy concerning the relationships between species diversity and ecosystem function
• Introduction to the project-specific biological questions regarding the relationship between species richness and primary productivity
• Scale-dependence and how one might choose appropriate data analysis and meta-analyses to study it
• Field trip to research site contributing data for student research projects

• Course Syllabus
• Course Reading List