Managing the Data Exchange Relationship

Michael Scofield
Manager, Data Asset Development
ESRI, Inc.

Monday 1:00pm - 4:15pm
Half Day Tutorial
Level: Intermediate

When two distinct legal parties agree to transfer data, they create a relationship, even for a short while. In that relationship are a host of expectations on each side, some of which are assumed, and not articulated or confirmed. Those expectations need to be understood, and articulated in language which is clear to all parties. The source and acquiring parties must be in agreement on numerous details including the kinds of data and information, logical data architecture, physical form and media, documentation and meaning, currency, data quality, updates and refresh issues, ownership, usage, liability and so on.

Lurking in each of these topics are potential points of failure in the data (and the relationship). Some mitigating strategies we will consider include:

- Spelling out all expectations about data.
- Developing language, words, & models to enhance precision of communication about data expectations.
- Rigorous testing of data prior to purchase
- Strengthening relationship through cooperative data testing strategies such as offering to test their updates, and establishing yourself as a consulting (to them) expert in DQ.