1. BioGeomancer: Semi-automated Georeferencing Engine
John Wieczorek, Aaron Steele, Dave Neufeld, P. Bryan Heidorn, Robert Guralnick, Reed Beaman, Chris Frazier,
Paul Flemons, Nelson Rios, Greg Hill, Youjun Guo

2. Spatially Challenged Occurrence Data
LA PEÑITA; 5.5. KM N
Baird Mtns.; Salmon R. headwaters
CALIENTE MOUNTAIN
10 MI SW CANAS, RIO HIGUERON
near Sedan
4.4 MI N, 6.2 MI W SEMINOLE

3. Spatially Enabled Occurrence Data

4. Input - Verbatim Locality Strings
LA PEÑITA; 5.5. KM N
Baird Mtns.; Salmon R. headwaters
CALIENTE MOUNTAIN
10 MI SW CANAS, RIO HIGUERON
near Sedan
4.4 MI N, 6.2 MI W SEMINOLE

5. Legacy Locality Data Issues
Treat locality description as accurate
Treat locality description as complete

6. Legacy Locality Data Issues
Treat locality description as accurate
Treat locality description as complete
We need these to start processing.

7. Legacy Locality Data Issues
Treat locality description as accurate
Treat locality description as complete
We need these to start processing.
These are assumptions
we should not hold to be true.

8. Legacy Locality Data Issues
Treat locality description is accurate
Treat locality description as complete
Apply rules for locality string interpretation

9. Legacy Locality Data Issues
Treat locality description is accurate
Treat locality description as complete
Apply rules for locality string interpretation
There is more than one way to
accomplish string interpretation.

10. Locality Interpretation Methods
Regular expression analysis
GeoLocate - Tulane
Enhanced BioGeomancer Classic – Yale
Machine Learning/Natural Language Processing
U. Illinois, Urbana-Champagne
Inxight Software, Inc.

11. Locality Types F – feature P – path
FO – offset from a feature, sans heading
FOH – offset from feature at a heading
FO+ – orthogonal offsets from a feature
FPOH – offset at a heading from a feature along a path
31 other locality types known so far

12. Five Most Common Locality Types*
51.0% - feature
21.4% - locality not recorded
17.6% - offset from feature at a heading
8.6% - path
5.8% - undefined
*based on 500 records randomly selected from the 296k records georeferenced manually in the MaNIS Project.

13. Clause
Subset of a locality description to which a locality type can be applied.

14. Step 1: Define Clause Boundaries
LA PEÑITA; 5.5. KM N
Baird Mtns.; Salmon R. headwaters
CALIENTE MOUNTAIN
10 MI SW CANAS, RIO HIGUERON
near Sedan
4.4 MI N, 6.2 MI W SEMINOLE

15. Step 1: Define Clause Boundaries
<LA PEÑITA; 5.5. KM N>

16. Step 1: Define Clause Boundaries
<LA PEÑITA; 5.5. KM N>
<Baird Mtns.; >

17. Step 1: Define Clause Boundaries
<LA PEÑITA; 5.5. KM N>
<Baird Mtns.; ><Salmon R. headwaters>

18. Step 1: Define Clause Boundaries
<LA PEÑITA; 5.5. KM N>
<Baird Mtns.; ><Salmon R. headwaters>
<CALIENTE MOUNTAIN>
<10 MI SW CANAS, ><RIO HIGUERON>
<near Sedan>
<4.4 MI N, 6.2 MI W SEMINOLE>

19. Step 2: Determine Locality Types
<FOH>LA PEÑITA; 5.5. KM N</FOH>

20. Step 2: Determine Locality Types
<FOH>LA PEÑITA; 5.5. KM N</FOH>
<F>Baird Mtns.; </F>

21. Step 2: Determine Locality Types
<FOH>LA PEÑITA; 5.5. KM N</FOH>
<F>Baird Mtns.; </F><PS>Salmon R. headwaters</PS>

22. Step 2: Determine Locality Types
<FOH>LA PEÑITA; 5.5. KM N</FOH>
<F>Baird Mtns.; </F><PS>Salmon R. headwaters</PS>
<F>CALIENTE MOUNTAIN</F>
<FOH>10 MI SW CANAS, </FOH><P>RIO HIGUERON</P>
<NF>near Sedan</NF>
<FO+>4.4 MI N, 6.2 MI W SEMINOLE</FO+>

23. Step 3: Interpret Clauses
<FOH>LA PEÑITA; 5.5. KM N</FOH>
Feature: LA PEÑITA
Offset: 5.5
Offset Units: KM
Heading: N

24. Step 4: Find Feature Descriptions
<FOH>LA PEÑITA; 5.5. KM N</FOH>
Feature: LA PEÑITA
Offset: 5.5
Offset Units: KM
Heading: N

25. Legacy Locality Data Issues
Treat locality description is accurate
Treat locality description as complete
Apply rules for locality string interpretation
Treat spatial data references as accurate

26. Legacy Locality Data Issues
Treat locality description is accurate
Treat locality description as complete
Apply rules for locality string interpretation
Treat spatial data references as accurate
This is another assumption
we should not hold to be true.

27. “Davis, Yolo County, California”
testing slide 2

28. “Davis, Yolo County, California”
testing slide 2

29. “Davis, Yolo County, California”
testing slide 2

30. Legacy Locality Data Issues
Treat locality description is accurate
Treat locality description as complete
Apply rules for locality string interpretation
Treat spatial data references as accurate
Apply rules for spatial description building

31. Step 5: Construct Spatial Description for Each Clause

32. Step 5: Construct Spatial Description for Each Clause
West of B

33. Step 6: Construct Final Spatial Interpretation
10 MI SW CANAS, RIO HIGUERON
Clause 1: <FOH>10 MI SW CANAS, </FOH>
Clause 2: <P>RIO HIGUERON</P>

34. Step 6: Construct Final Spatial Interpretation
10 MI SW CANAS, RIO HIGUERON
Clause 1: <FOH>10 MI SW CANAS, </FOH>
Clause 2: <P>RIO HIGUERON</P>
We hold these clauses
to be simultaneously true.

35. Step 6: Construct Final Spatial Interpretation
10 MI SW CANAS, RIO HIGUERON
Clause 1: <FOH>10 MI SW CANAS, </FOH>
Clause 2: <P>RIO HIGUERON</P>
We hold these clauses
to be simultaneously true.
The final spatial description is the intersection of the spatial descriptions of all clauses.

36. Legacy Locality Data Issues
Treat locality description is accurate
Treat locality description as complete
Apply rules for locality string interpretation
Treat spatial data references as accurate
Apply rules for spatial description building
Apply criteria to reject unwanted hypotheses

37. Additional Input - Preferences
Assume terrestrial locations
Assume aquatic locations
marine only
freshwater only
Assume direct offsets
Assume offsets by road, if possible

38. Output Original data Zero, one, or more spatial interpretations
- spatial footprint
- point-radius description
Process metadata
preferences (e.g., GeoLocate method, assume by road)
omissions (e.g., unused information)
confidence values

39. Conclusion Georeferences are hypotheses Hypotheses require testing
Tested hypotheses should be so noted