1. Advancing Software for Ecological Forecasting

2. Introduction: Scientific Workflows Schlesinger et al. 1979 Terminology for model credibility. Simulation. Inference Engines Kruschke et al 2012 The time has come: Bayesian methods for data analysis in the organizational sciences.

3. Workshop Objectives Establish current state of our projects Common challenges Opportunities to collaborate, couple existing tools Foster collaborations, coupling of existing tools Identify common design principles and standards Envision next generation software Make science faster and more useful

4. Agenda: Today 9-10: Plenary Welcome, David LeBauer, University of Illinois Inference Engines, Perry de Valpine, University of California at Berkeley Scientific Workflows, Matthew Smith, Microsoft Research, Cambridge 10-12: Lightning Talks (4 min ea.) Scientific Workflow Projects Inference Engine Projects 1-5 Working Groups

5. Lightning Talks and Workshop Participants

6. Agenda: Wednesday and Thursday Wednesday 9 AM Keynote: Aaron Ellison, Harvard Reaching the 99%: making statistical software relevant and useful for ecologists 10-5 Working Groups Thursday 9 AM Plenary: Matt Jones, NCEAS Looking forward: what next? 10-5 Working Groups

7. Organizers Technical: David LeBauer, Chair, University of Illinois Matthew Smith, Microsoft Research Perry de Valpine, University of California, Berkeley Practical: Ank Michielsen, University of Illinois Becky Heid, University of Illinois Gail Jones, University of Oklahoma

8. Sponsors NSF RCN: Forecasts Of Resource and Environmental Changes: data Assimilation Science and Technology (Yiqi Luo, PI) Additional Support: Microsoft Research Connections Institute for Genomic Biology