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Large Scale Collaborative Georeferencing A FishNet Perspective

Large Scale Collaborative Georeferencing A FishNet Perspective. Nelson E. Rios nrios@tulane.edu. i DigBio Train the Trainers Georeferencing Workshop Gainesville, FL 8-12, Oct 2012. History of FishNet. 1999: C reation of original FishNet Network. Z39.50 protocol for sharing data.

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Large Scale Collaborative Georeferencing A FishNet Perspective

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  1. Large Scale Collaborative GeoreferencingA FishNet Perspective Nelson E. Rios nrios@tulane.edu iDigBio Train the Trainers Georeferencing WorkshopGainesville, FL 8-12, Oct 2012

  2. History of FishNet 1999: Creation of original FishNet Network Z39.50 protocol for sharing data Search via Species Analyst (distributed query model) 2005: FishNet 2 created Transition to DiGIR Protocol Search via DiGIR Portal (distributed query model) 2010: FishNet 2 (centralized query model) Harvesting of DiGIR, DwCA, Static Spreadsheets Search via FishNet 2 Portal (centralized query model)

  3. Global network of fish collections 52 data providers 3.3 million lots 30+ million specimens 57% georeferenced 4+ million lots100% georeferenced

  4. Georeferencing Collaborators

  5. Preliminary Assignments 2 out of 4 million records in need of georeferencing~250,000 locality records

  6. Collaborative Georeferencing Performance • 2100 randomly selected collecting events from the Tulane University fish collection were imported and georeferenced using the collaborative georeferencing framework • 33% were duplicates • 30% more related by similarity index 2100 782 63% reduction in effort overall

  7. Software & services for georeferencing of natural history collections data automated georeferencing verification & correction multi-lingual kml export interoperability soap & rest api batch processing training geographic visualization uncertainty determination google, bing, openstreet, wms collaborative georeferencing

  8. Uncertainty • Point (legacy) • Point + Radius • Point + Radius + Polygon

  9. Leveraging Existing Technology and Expertise

  10. Workflow: Integrating API’s produce datasets for CoGe based on institution and anticipated difficulty of verification pre-georeference, assess verification difficulty, identify problematic records clean data, add to locality gazetteer & match against locality gazetteer Assign workloads by institution, difficulty & region verify, correct & annotate final review of results repatriate data providers http://geolocate.fishnet2.net/workflow.html

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