Issues

Business model

Basic elements of operational (not development) cost

• Amount of data from the institution
  
  • this affects the processing time that needs to be allocated as well as the increment to the size of the index
• Frequency of update (again based on the processing and oversight/validation required for indexing)
• Support
  • providing feedback on bad data, especially to people new to ontologies and RDF
  • addressing performance issues at the distributed data sources (especially if harvesting degrades the function of their production VIVO app)
  • there will have to be a startup fee with some number of hours of support included, and then the ability to redirect further support to a list of consultants or companies willing to provide help

Relationship of services to sponsorship

It will be much cleaner to separate sponsorship from participation in production services.

• You sponsor to support the effort, as well as influence and hasten its development
• You sign up for a service if you want your data to be included in that service

Areas that may get messy

• Founding sponsors may expect not to be nickel & dimed
• Business model could have a fee scale based on data size

Limits to what we can charge

• The code is all open – universities may prefer to run their own (in which case you request that they sponsor to help keep the code updated)
• Service providers may decide they could host competitive search services, with their own value added in tweaks to relevance ranking, etc.
• As the price goes up, a cost benefit analysis will steer people to other options including custom Google search appliances, etc.

Technical Risks

Indexing is too slow and interferes with performance on the site being indexed

Relevance ranking proves intractably messy

Some people will be hard to please