The Canopy Database Project Observation Model canopy . evergreen

1. The Canopy Database ProjectObservation Modelhttp://canopy.evergreen.edu Judy Cushing, Nalini Nadkarni Anne McIntosh, Lee Zeman and others The Evergreen State College Collaborators NSF CISE and BIO 04-0417311, 03-019309, 01-31952, 01-9309 99-75510, 9630316, 93-07771

2. Canopy DB Project • Studying complex ecosystems across multiple scales requires data integration & analysis and synthesis… different types of information – different formats & different sources…. • To synthesize, data must be archived & documented, locatable & integrate-able • Who has time to document data… (need better tools) • What documentation is useful…(need synthesis case studies) • Database & Component Technology could help, BUT • Ecology studies cannot afford programmers, and • Scientists want to do research, not be programmers. • We aim for Eco-Informatics tools that enable scientists to program • Increase individual (field ecologist) researcher productivity…. • Facilitate later data integration and ecological synthesis

3. Canopy DB Project Scientific VisionThousand Year Chronosequence (1kcs) Forest structure determines forest functions. • Categorize within-tree & -stand structure across age classes. • Conduct structure-function synthesis. Relate structure (stems, crowns, understory, branches, interstices, etc.) to functional characteristics (through-fall, light, sap-flow, water use). Image by Bob Van Pelt

4. Canopy DB Primary Use Cases • Given a study design, create a research database using system-supplied domain-specific Components • Empty MS Access database or Excel spreadsheet, metadata profile, input forms, validation. • Create-edit components (templates) • End user (or user community) template library. • Given a database in our format, generate standard visualizations, e.g., impose observations on structural data. • Upload to and download from a data repository (Study Center).

5. Canopy DBObservation Model Overview

6. Organization of the Implemented ModelObjects and Observations translate to templates Stem Branch ENTITIES DBH Length OBSERVATIONS Height Spread Species

7. Organization of the Implemented ModelTemplates “understand” observation structure 1 Many Stem Branch DBH Length Species Height Spread Name Species 1 1 Auth.

8. Canopy DBAssociated tools, features, framework • Canopy DataBank – generates research field database and EML metadata file. • Component (template) Library Editor – creates an end user (or user community) template library. • CanopyView – performs data visualization on DataBank DBs. • Canopy Study Center – Online Warehouse for Canopy DBs.

9. Documentation Document DataBank Products .HTML File MS Access Database Forms .mdb file MS Excel Spreadsheet .xls file Ecological Metadata Language document *_eml.xml Other Metadata Software

10. Documentation Document DataBank Products .HTML File MS Access Database Forms .mdb file .xls file MS Excel Spreadsheet *_eml.xml Other Metadata Software _workspace.xml .CVState File CanopyView

11. Stem Model Branch Foliage Model Foliage Start, stop Foliage inner, mid, outer Foliage length and width Upright stepped Upright cone, Upright linear, Upright cylinder, cylinder, Height, DBH Height only Height, DBH Multiple girth measures Branch Length Measurement Branch length Branch length perpendicular along branch to stem How the ‘Observation’ became CentralFirst Cut Templates were structure-based • Validate generated databases with rules • e.g., Stem: • depends onstudy area, plot • includes species table Capitalize on core components for tools Visualization, Metadata Provision, Data Acquisition & Validation, research protocol, statistical analysis….

12. Current DataBank TemplatesObservation-Based 1. Entities = structural components of the forest canopy 2. Observations = measurements taken on an entity Branch length perpendicular to stem Branch length along branch

13. Templates in Data Design Green = entityBlue = observation

14. MS Access DataBank Design

15. CanopyView

16. Model Extensibility(what we do) • How do we extend … if new domain terms • the model has been static • the tool (DataBank) – use the Template Editor • the tool (CanopyView) – designate color-coding • Restrictions on allowed extensions – none for now • How extensions are supported • Template Library Editor

17. Model Extensibility(what we’d like to do) • How do we extend … if new domain terms • Better connections between the model and the tool(s) • Template library naming • Identification by CanopyView of ‘observations’ and codes • Connect templates to higher level abstractions • structure, conceptual framework • Add some restrictions on allowed extensions • How extensions are supported • Add theoretical restrictions to Template Editor • Use better naming conventions • StudyCenter query capabilities, linked to observations

18. 0 1 2 3 . . … … … . . .. . . .. A. 0-, 1-, 2-, 3-dimensional B. Reactive or non-reactive C. Spatially referenced or spatially independent Collection, Network, Continuous Component