Illinois Educational Digital Natural History Museum

1. Illinois Educational Digital Natural History Museum P. Bryan Heidorn University of Illinois at Urbana-Champaign pheidorn@uiuc.edu

2. National Science Digital Library

3. Biobrowser

4. Biological Information Browsing Environment (BIBE) • NSF Biological Databases and Informatics • Indexing, searching and visualizing biological information • Augmenting dichotomous keys

5. Self-repairing Biodiversity Database • NSF Information Technology Research • Wireless access to flora and fauna in the field • Synchronous Collaboration with experts • Mapping Distributions of species

7. Entomologist Botanist BaseServer Internet FieldServer Field Wireless

8. Workshop on Biodiversity Digital Library Design • Five Components • Survey Support Services • Collection searching • Federation of EcoSystem species data • Remote Sensing and Geographic Information Systems • Decision Support Analysis and Publishing

9. DL Software Requirements • Needs to meet biodiversity needs • Low Cost for citizen groups and governments • Ease of use • Management tools • Information sharing • Collaborative development and use

10. Remote Sensing and GIS • Activities • Identification of sites • Historical/Seasonal conditions • Distributions • Monitoring abiotics (siltation, tepidity, pH, water temperature, • Socioecosystem overlays, land use, weather • Reports and Proposals

11. RS Requirements • Sufficient resolution: 1m? • Timeliness • Reliability • Continuity of service • Costs • Redistribution of images • Image processing / Classification • clustering, false color, forest-type, wetland • Repackaging for reports

12. RS Requirements • Tools need to meet needs • Water cover • Forest cover • Leaf-out time

13. GIS Requirements • Land use reports • Geopolitical Units • Point distribution and GPS • Extrapolation / GAP-like • Predictive modeling

14. Self Publishing • Sharing Findings • Post Aerial images • Post Classification / Image processing

15. Training • Evaluation Procedures • Verification • Use of RS & GIS

16. Community Biology Collections • Virtual, distributed natural history collections (one per school or community) • Specimen data • Species data • Ecology: distribution and interactions • Teacher enhancement • Biology information library and portal • NSDL infrastructure

17. Features of Community Biology Collections • Inquiry-based (observation and research) • Multimedia (physical collection optional) • Low-cost creation and viewing tools • Permanent collections • Quality verification

18. Advantages • Inquiry-Based Learning • Ask activity-oriented • Investigate students conduct field and library research • Create fact sheets • Discuss with peers and professionals • Reflect permanent keys of local flora and fauna • Research

19. Curriculum Integration • Teacher certification • New teacher training • Science club and advanced placement programs • Student mobility • Cross-curricular activities • Biology • Earth science • Social science

20. Specimen Data • Name • Location • Collector • Description • References • Images, Sounds

21. Specimen Data Example • Name: Danaus plexippus/Monarch butterfly • Location: Open weedy area • Collector: Jim McKay • Description: Orange and black, four inch wing span • References: Opler, P. (1992). A field guide to eastern butterflies. Boston: Houghton Mifflin.

22. Size Food Flight habits Taxon Fact Sheets • Summary information about a species • Name • Editor • Description • Distribution • References • Images, Sounds

23. Size: 3 3/8 - 4 7/8 inches Food: Flower nectar Flight habits: Slow, gliding Taxon Fact Sheet Example • Name: Danaus plexippus/Monarch butterfly • Editor: Jim McKay • School: Pekin High • Description: Black and orange, scent patch on underside • Distribution: Statewide • References: Opler, P. (1992). A field guide to eastern butterflies. Boston: Houghton Mifflin.

24. Taxon Fact Sheet Example Danaus plexippus/Monarch butterfly

25. Quality Control • On-line reports with quality tags • Peer review • Teacher review • State review • Environmental biology internships • Illinois Natural History Survey

26. Infrastructure • Web-based and Java for accessibility • Research, state, local servers • Connection to NSF/NSDL as peer • Borrow heavily from Tropicos and VAH • Learning technology hubs • Z39.50 federation

27. Some features • Based on observation and research • Multimedia without physical collection • Low cost creation and viewing tools • Persistent components • Quality verification

28. What is it good for? • Learning • Active, product oriented learning • Students conduct field and library research • Peer and professional evaluation • Part of professional project • Student Publishing - Keys, Local Flora/Fauna • Research

29. Specimen Data • Name • Location • Collector • Description • References • Images, sounds

30. Conservation status Allies Natural history notes …. Taxon Fact Sheets • Summary information about a species • Name • Editor • Description • Distribution • References • Keys • Images, Sounds

31. Quality Control • Most reports stay on line but with Quality tags. • Peer review • Teacher review • School review • State Review

32. Tasks • Participants • Teachers and Schools • Herbaria • Framework for Treatments • Input Screens • Database Structure • Services (dot maps, compendia caching, account management, …)

33. Biobrowser

34. WebVIBE: Web-Base Information Browsing Vector model retrieval Point Of Interest (POI) Document Clustering Remote Collections

35. Projects • Opler, Paul A., Harry Pavulaan, and Ray E. Stanford (coordinators). 1995. Butterflies of North America. Jamestown, ND Northern Prairie Wildlife Research Center Home Page. http://www.npwrc.usgs.gov/resource/distr/lepid/bflyusa/bflyusa.htm. Where we indexed some butterflies.

36. Databases • Missouri botanical IMLS http://hoya.mobot.org/imls/ • The New York Botanical Garden http://www.nybg.org/bsci/herb/ Type imaging project • The CalFlora Species Database • http://elib.cs.berkeley.edu/calflora/about.html

37. USDA • THE USDA Plants Database http://plants.usda.gov/plants/ • Integrated Taxonomic Information System (ITIS)http://www.itis.usda.gov/index.html

38. Features • Retrieval Set Size • Stack Size • Disambiguation • Motion • Highlighted influencing POIs • Lasso collections of Icons

39. Features under Development (or underdeveloped features) • Faceted Retrieval • Similarity Based Retrieval • Data Mining • Data Fusion • Federated Search

40. Faceted Retrieval • Semi-structured field search • Trees, to 25 m, crowns narrow. Bark of young trunks and branches reddish brown, when mature becoming pinkish white to light red (starkly white in interior Alaska; D. F.Murray, pers. comm.), smooth, exfoliating in thin sheets. Twigs glabrous, covered with conspicuous resinous glands…..

41. Similarity Based Retrieval Statistical Similarity - such as the cosine measure.

42. Data Mining • Conversion of free text to another format • “Trees, to 25 m, crowns narrow” • Plant height in meters, color, texture.. • Free text to DELTA • Intelligent similarity • round > oval > lancolate

43. Data Fusion • Multiple sources • FNA, CalFlora, USDA Plants, NYBG Herbarium…

44. Federated Search • Across collection and locations • ZBIG - Z39.50 • Biological XML Data Interchange Standard • Taxonomic Data Working Group