| Day One Pre-workshop Assignment | 
        
        Availability of species interaction datasets is limitedOpen Data, Open Science, and FAIR principles facilitate data availability | 
  
  
  
    
      | Day One Group Assignment Part One | 
        
        Many species interaction datasets are openly publishedInteraction data are shared in various waysMany interaction data records have common data elementsReviewing data can be time consuming | 
  
  
  
    
      | Day One Group Assignment Part Two | 
        
        Automated taxonomic name linking facilitates discovery, review, and interpretation, of interaction recordsKeeping track of data provenance/origins can be trickySpecialized search indexes like GloBI can help facilitate data discoveryAutomated linking and index processes are likely imperfect and subjective | 
  
  
  
    
      | Getting Interaction Data |  | 
  
  
  
    
      | Working with the Whole Dataset |  | 
  
  
  
    
      | Exploring By Pointing and Clicking | 
        
        Web tools are for exploring indexed data and providing feedbackWeb tools facilitate communication within biodiversity data communityWeb tools are dynamic and subject to change | 
  
  
  
    
      | Working with Data Sources | 
        
        GloBI is built using existing data sourcesData sources are continously and automatically indexed by GloBIGloBI provides automated reviews of data sources | 
  
  
  
    
      | Taxonomic Name Review | 
        
        Taxonomic name linking facilitates discovery, review, and interpretation, of interaction recordsGloBI uses a versioned taxonomic name map to map verbatim names into known taxonomic schemesGloBI attempts to provide reasonable links using a controlled and iterative processGloBI taxonomic name linking process is likely imperfect and subjective | 
  
  
  
    
      | Interaction Data Record Review |  | 
  
  
  
    
      | Day Two Pre-workshop Assignment |  | 
  
  
  
    
      | Day Two Group Assignment Part Two | 
        
        Working with big datasets often requires different tools and skillsData processing introduces errors and biasMany tools are suited for small datasets only |