GISNerd is my place to write about GIS, public data, visualization, systems, and practical technology.
I have spent more than 25 years working across IT, GIS, land development, real estate, and property data. Most of that work has lived in the space between technical systems and real-world decisions. Maps, databases, parcel records, permitting workflows, web tools, reporting systems, and the many small processes that help people understand land and property.
That intersection has always been the interesting part to me.
GIS is not just about maps. It is about context. It is about taking information that is scattered across systems, records, departments, and workflows, then turning it into something people can actually use.
Today, I work as a GIS Administrator at the local government property data. My work now sits even more directly in the world of public data, property information, mapping, web applications, and internal systems. It has reinforced something I have believed for a long time: public information becomes much more valuable when it is clear, visual, accessible, and connected to the way people actually work.
That is the goal of this site.
GISNerd is not meant to be a formal portfolio. It is not meant to be a consulting pitch. It is not meant to be a place for long academic posts that nobody finishes reading.
The goal is simpler than that.
I want to document ideas, experiments, lessons, and practical examples from the kind of work I care about:
A lot of the best work in technology is not flashy. It is the quiet improvement of a workflow. A clearer map. A better search tool. A report that finally makes sense. A dashboard that helps someone see what is happening. A system that reduces friction for the people who use it every day.
That is the kind of work I want to write about here.
I am also interested in how AI fits into this. Not as a magic replacement for people, and not as a buzzword pasted onto every project. I see AI as a force multiplier. It can help with research, planning, coding, documentation, brainstorming, and execution. But it still needs direction, context, review, and judgment.
That is especially true in GIS and public data work, where accuracy matters and context matters even more.
My hope is that GISNerd becomes a useful notebook. A place where I can share what I am learning, explain what I am building, and think out loud about how GIS, data, systems, and AI are changing the way we work.
Some posts will be short. Some will be more technical. Some will be about ideas. Some will be about specific tools or workflows. The common thread will be practical value.
Spatial intelligence should not be locked away in complicated systems.
It should be clear.
It should be useful.
And when possible, it should be powered by code.