In the business of quality assurance one requires a meticulous demeanor. From a data quality standpoint - identifying the defects or errors in data is a primary first step. In
Quality Is a Decision, I alluded to the abundance of data that is being generated and to the importance of managing that quality from the get go. In this blog I look at a helpful tool to do just that.
ESRI’s Data Reviewer Extension helps achieve this goal by centralizing and managing geospatial data - while capitalizing on the inherent tools that are already part of the massive ArcGIS Desktop geoprocessing persona. Data Reviewer has been part of the PLTS (Production Line Tool Set) arsenal for some time now. It dates back to the early nineties when it was known as QCVIEW. In July of last year, the Data Reviewer team began blogging on the ArcGIS Resource Center, pushing its importance and relevance to the forefront.
Data Reviewer follows the error life cycle path of reviewing, correcting, and verifying data in numerous ways, embedding this concept into the nuts and bolts of its functionality. Although several of the geoprocessing tools in Arc Tool Box facilitate the validity of your data, Data Reviewer brings it all to you in one place or the workspace of your choice.
There are many features that make Data Reviewer a great tool for use in Quality Assurance initiatives, but there are some key components that showcase its incredible value. The first is its data checks. Both attribute and geometry checks can be run – individually or in batch and in a multitude of combinations that can all be used to identify errors in data. For those not so common queries, there is also a custom option that can be written in .NET and wired in. If you are thinking of integrating your existing queries – remember that existing processes may dictate the order, sequence as well as conditions necessary to identify errors. What this means is that when re-creating your checks take some time to revisit your data model as well as your workflows.
The errors are displayed in the Reviewer table. There are standard fields that show checks, users and other pertinent information that can be grouped and sorted. You can also add key fields from your organizations data that are more meaningful. Creating templates are very useful in terms of keeping a group’s or project phase focus on relevant information and more so on the task at hand. Creating a grid plays a big part in visually controlling and identifying errors in sections. The grid is color coded in red, yellow, and green and can and should be linked the reviewer table.
As with everything you must prepare a strategy for the reviewer workspace as well as its sessions. Think of the workspace as your geodatabase location – it can be anywhere you like, with your data or in a separate database. Remember it stores the errors as, points, lines, polygons, and a main table that holds all the checks. Sessions are similar to edit sessions. Sessions can be specific phases of your workflow or a specific area. Again, planning is everything here. Your workflows, processes, business rules will drive this strategy.
ESRI offers a 60 day trial as part of their Mapping and Charting Solutions. I recommend installing
the latest service pack. A
free web training course is also available and gives a great introduction.
These are just some of the major components of Data Reviewer. There are many other advantages to using this tool and coupled with an appropriate QA/AC Program can help your organization reach your data quality goals. After all – isn’t it from the interpretation of data that information is derived, and from said information that knowledge and thus wisdom perpetuate? This cycle of intelligence is required to continually improve the quality of data and guide us in choosing wiser decision making alternatives.
