By: Robert Fleming
It is that time of year again; the Esri UC is behind us and we GIS folks have all these great ideas to chase down. Maybe you saw a cool map in the gallery that highlights data in a unique way; or went to a session about an application that your users could really benefit from. Whatever it is, the fire has been lit and we are ready to run with it. Great! That is what these events are all about – sharing ideas, learning about new techniques, and finding solutions. Now hit the brakes…
All too often, we come out running but we often forget to acknowledge that we just focused on the final product. That map you came upon was not just a few hours of work to make it look great on some glossy paper. That application was not just a few developers and designers making a great interface for the public. It represents weeks, months, or even years of building great data that analysts and developers expose through their products. Don’t get me wrong, the talents witnessed at these events are amazing; and we need great maps and apps to share our data. However, if the data is no good, who will want to use our maps and apps? What value can our products have then?
As you develop your next project, spend some time thinking about the data. Plan to foster an environment where data management is key to the strategy. How will it be stored? How will it be maintained? How will you ensure its quality? These are just a few thoughts to get started thinking about data management strategy and how it can make your product relevant.
All projects start here; and while defining a database design is rarely left out, it is important to get this step right in the beginning. What data model should be used; is the existing model good enough or should a new industry model be implemented? This answer may vary depending on your organization and project needs. It is importance to understand the end goal, which will help define the requirements and drive the database design. Designing your database correctly early on will ensure all relevant data has a place in the model. There is nothing worse than having to review every record over again because you had to add one more attribute.
Many projects use the most current data or collect new data once during the project scope. This might suffice for the initial deliverable; but the data becomes stale the day it is published. From that day forward, the value of the product begins to decrease. How can you keep your product relevant? Build data maintenance into the existing business processes. The staff from the group you built the product for often completes these processes. Be sure to include this group as a key stakeholder in your project. Get their buy-in and discuss altering their business processes to include a GIS data maintenance step. If you help them realize the value of your product, this will be a welcome addition to their processes.
Designing a great data model and keeping your database current is great. These are big steps in making your data relevant. If it meets their needs, people will want to use your product and rely on it for answers. What happens when they find errors in the data? Errors are going to happen; there is no way around it because we all make mistakes. How you handle the errors will define your data’s relevance and possibly even make it the authoritative source. Plan for regular quality control checks to ensure it meets a defined standard. These should include both automated checks for schema discrepancies and hands-on checks to verify content quality. You may also include a method for users to submit errors they have found. Implementing data quality will help establish your dataset as a trusted source.
So if your data is incomplete, outdated or full of errors your product will not be relevant no matter how great the idea was. Remember, when people use your product it is the data and the story you can tell with it that they are truly interested in. Make data a priority and stay relevant.