1. The Heart of Ecoinformatics at Multiple Scales: Ontologies for Ecological Information Neo Martinez and Rich Williams 1 PEaCE Lab (www.PEaCELab.net) Pacific Ecoinformatics and Computational Ecology Lab Berkeley, California Rocky Mountain Biological Laboratory, Crested Butte, Colorado 1 Computer Science Department, San Francisco State U. San Francisco, California www.FoodWebs.org

2. Ecoinformatics The study, organization, and manipulation of ecological information The study, organization, and manipulation of ecological information Study: Ecological types of information Study: Ecological types of information Entities, Interactions, Environment Entities, Interactions, Environment Organization: Groups and organization of types Organization: Groups and organization of types Subdisciplines, Measurements, Space, Time Subdisciplines, Measurements, Space, Time Manipulation: Architecture and Applications Manipulation: Architecture and Applications User interfaces, Access, Analysis, Visualization User interfaces, Access, Analysis, Visualization

3. Current Situation Ecologists document more or less observations and save them as Excel or text files Ecologists document more or less observations and save them as Excel or text files Summaries of data are sometimes published. Summaries of data are sometimes published. Raw data occasionally estimated from graphs Raw data occasionally estimated from graphs Context of data minimally described Context of data minimally described Additional context (why, when, where, how) lost as time proceeds Additional context (why, when, where, how) lost as time proceeds

4. Current Situation Time since observation Value of observation

5. Ecoinformatic Fantasy Time since observation Value of observation

6. Ecoinformatic Data Improvement Higher spatiotemporal resolution (auto GPS) Higher spatiotemporal resolution (auto GPS) Integrated habitat, elevation, aspect, etc. Integrated habitat, elevation, aspect, etc. More context information More context information Purpose: experimental, survey, subdiscipline Purpose: experimental, survey, subdiscipline Procedure: measurement methodology Procedure: measurement methodology Precision: bio./chem. species ID, sig. figs., pics Precision: bio./chem. species ID, sig. figs., pics Permanent storage and annotation Permanent storage and annotation Trust, security, verifiability, error checking Trust, security, verifiability, error checking Increased accessibility Increased accessibility Immediate and long term Immediate and long term

7. Semantic Web "The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation." Tim Berners-Lee, James Hendler, Ora Lassila The Semantic Web Scientific American, May 2001 Also see Hendler 2003. Science 229:520-521 Science and the Semantic Web..

8. Ecological Ontologies Describe organization of ecological information Describe organization of ecological information Describes the types of information Describes the types of information Character strings, values, associations Character strings, values, associations Organizes types into sets and properties Organizes types into sets and properties Sets, supersets, subsets, “is a…,” “has a…,” Sets, supersets, subsets, “is a…,” “has a…,” Provides Standards: Architecture & Applications Provides Standards: Architecture & Applications Ontology Web Language (OWL) Ontology Web Language (OWL) Resource Description Framework (RDF) Resource Description Framework (RDF) Designed to be multiple, overlapping, and evolving Designed to be multiple, overlapping, and evolving

9. Defining Meaning of Terms Ex. 1 Feeding terms: Information beyond “eat”? Feeding terms: Information beyond “eat”? Herbivore, Omnivore, Predator, Parasite, Parasitoid, Hyper-parasitoid, Folivore, Fungivore Herbivore, Omnivore, Predator, Parasite, Parasitoid, Hyper-parasitoid, Folivore, Fungivore What is eaten: organism(s) and or their part(s) What is eaten: organism(s) and or their part(s) When it is eaten: period and amount of time When it is eaten: period and amount of time Where it is eaten: aquatic, terrestrial, pelagic, soil Where it is eaten: aquatic, terrestrial, pelagic, soil Consequences of eating: death, pollination, disease Consequences of eating: death, pollination, disease

10. Defining Meaning of Terms Ex. 2 Habitat: Information content beyond where? Habitat: Information content beyond where? E.g. marine benthos, tropical canopy, endophytic E.g. marine benthos, tropical canopy, endophytic Physical matrix: water, salinity, solid, air Physical matrix: water, salinity, solid, air Biological matrix: trees, host, inside, outside Biological matrix: trees, host, inside, outside Climate: temperature, moisture, variability Climate: temperature, moisture, variability Meaning of terms coded by one or more predefined dimensions described in ontologies Meaning of terms coded by one or more predefined dimensions described in ontologies

16. Ecoinformatic Fantasy Handheld vegetation survey data entry in field Handheld vegetation survey data entry in field User selects among available data sheets User selects among available data sheets GPS, elevation, weather, automatically stored GPS, elevation, weather, automatically stored Space-time specific electronic field guide retrieved Space-time specific electronic field guide retrieved Family, genus, species name/location verified Family, genus, species name/location verified User notified if other local surveys available User notified if other local surveys available User notified of analysis/modeling tools User notified of analysis/modeling tools Marked up data saved on server Marked up data saved on server Others notified of data available (email, crawler…) Others notified of data available (email, crawler…) Invasive/endangered species Invasive/endangered species Range mapping Range mapping

17. Future Build ontologies and scrape databases Build ontologies and scrape databases Semantic Web Informatics for Species in Space Semantic Web Informatics for Species in Space SWISS SWISS Integrated ecoinformatics for species’: Integrated ecoinformatics for species’: Properties: size, abundance, metabolism & assimilation rates Properties: size, abundance, metabolism & assimilation rates Interactions: feeding, pollination, facilitation Interactions: feeding, pollination, facilitation Spatial Distribution: location, habitat, certainty Spatial Distribution: location, habitat, certainty Data Entry, Analysis (kepler), Visualization Data Entry, Analysis (kepler), Visualization

18. This work was supported by NSF grants:  Scaling of Network Complexity with Diversity in Food Webs  Effects of Biodiversity Loss on Complex Communities: A Web-Based Combinatorial Approach  Webs on the Web: Internet Database, Analysis and Visualization of Ecological Networks (WOW)  Science on the Semantic Web: Prototypes in Bioinformatics (SPiRE) Science Environment for Ecological Knowledge (SEEK) Thanks to Jim Hendler, Jen Golbeck, Jen Dunne, Ilmi Yoon, Paul Yoon, Tamara Romanuk, Eric Berlow, Ulrich Brose, Tim Finin, Jim Quinn Bowers, S., D. Thau, R.J. Williams, and B. Ludaescher. 2005. Data procurement for enabling scientific workflows: on explorign inter-ant parasitism. Pages 57-63 in Lecture Notes in Computer Science, Vol. 3372. C. Bussler, V. Tannen, and I. Fundulaki, eds. Springer-Verlag. Brose, U., E.L. Berlow, T. Josson, C. Banasek-Richter, L.-F. Bersier, J.L. Blanchard, T. Brey, S.R. Carpenter, M.-F. Cattin Blandenier, J.E. Cohen, L. Cushing, H.A. Dawah, T. Dell, F. Edwards, S. Harper-Smith, U. Jacob, R.A. Jnapp, M.E. Ledger, J. Memmott, K. Tintenbeck, J.K. Pinnegar, B.C. Rall, T. Rayner, L. Ruess, W. Ulrich, P. Warren, R.J. Williams, G. Woodward, P. Yodzis, and N.D. Martinez. In press. Body sizes of consumers and their resources. Ecology. Yoon, I., R.J. Williams, S. Yoon, J.A. Dunne, and N.D. Martinez. 2005. Interactive 3D visualization of highly connected ecological networks on the WWW. Pages 1207-1217 in ACM Symposium on Applied Computing (SAC 2005), Multimedia and Visualization Section.