The Washington State Transformation Framework (WA-Trans) provides a model for aggregating different statewide data sets that might provide a good blueprint for nationwide efforts. I recently interviewed Tami Griffin, the WA-Trans project manager, about the approach that she’s taking to pull together the best up-to-date data on roads, railways, ferries, aviation, ports, and non-motorized transportation infrastructure in her state.

This effort is a methodical and stepped approach that emphasizes incremental data improvement over time. When asked about pulling in data with perhaps questionable quality, Griffin responded:

The strategy has always been to bring data quality issues to the light of day, and then use information and positive feedback to create pressure for change and improvement. A lot of local governments are doing the very best they can, and they will do better if they are given an ability and a motivation to do better.

One of the things that we do is we produce reports and give them back to the data providers about their data, and it tells them things that can be improved, but we don’t make judgements about what we see. We just tell them things like, “you have this network that is not connected to other networks.” Or, “your linear reference system has these characteristics, some of which may be anomalies.” And then they can decide if those are things they need to fix. A lot of times they’re really thankful, because they just don’t have that information.

The WA-Trans effort has been recognized by NSGIC as a potential model for ‘Transportation for the Nation.’ And I think it provides a good model for other national data sets that need to be aggregated from many different data holders.

One of the more compelling aspects of this application is the data transformation work that is accomplished with Safe Software’s FME Server. The automated data QA/QC effort takes a lot of the pain out of the maintenance of the system, and ensures that only the best and newest data is added each time. This incremental improvement over time makes the collection of local data at varying quality a possibility, rather than resorting to an unrealistic,  extremely costly and time-consuming effort to raise all providers to the same level at once.

Read the full interview here.

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