Developing an asset management GIS data maintenance methodology: Part 1 – An Overview

(This is Part 1 of a week long series of posts on the current project I am working on, to develop a reasonable GIS data maintenance strategy for Asset Management data).

I’ve been meaning to write this series of posts for a while, and now that we are in the middle of “asset management” season at work, I figured that now was as good a time as any. For the last few years, I have assisted the asset management team in my unit with GIS support. Each year, they update the civil (and sometimes electrical) infrastructure asset registers of several local municipalities. This involves unbundling upgrade projects completed in the last financial year, amongst other things.

I’m not involved in that aspect of the work, so I’m not going to try to explain what they do. On my side, this is what would normally happen:

  1. I receive data (shapefiles, spreadsheets, pdfs, CAD drawings, hard copy maps that have been drawn on)
  2. I process/convert/work some magic on the data to get it into a usable GIS format (more on that in the next post)
  3. I give back a spreadsheet containing the new shape data from the upgrades, including the GIS IDs
  4. Sometimes I’ll give a mapbook of the area, if requested.

The shape data (lengths of lines) and the unique GIS IDs per feature are integrated into the asset register, and serve as a link between the GIS and the completed register. It’s very important that this link be maintained – I’ve had to find GIS data for records on an asset register where a stakeholder at the municipality had decided to remove the GIS IDs, hence why I put “work some magic” in point number 2 in the list above.

This year is different though. We are trying to transition to an integrated system, where instead of all the data lying in random spreadsheets on the project server, and random gdbs on my server, all the data should be stored in a central location for easy access (and auditing purposes). This may seem to be an obvious approach, but there’s about 7 years worth of data which needs to be transitioned (excluding the GIS data).

It’s an enormous task, and I’ve been given control over the GIS side. That means that I get to take the data I’ve gathered over the last 3 years and push it through some sort of transformation process, while also overseeing the current tasks and carrying out some of the work which can’t be done by the Desktop team (yet). I’m also writing a Python toolbox with a set of tools to automate some of the functions, such as generating GIS IDs based on a specific convention, automating the mapbook production, and creating the correct folder structure and feature class structure per municipality.

The slideshow below is what first triggered me to write some posts on this topic:

I also saw this article, and had a subsequent conversation with the author on Twitter about it. GIS can add a great deal of value to many asset management processes (and many other fields as well, but let’s stay focussed here). I’m breaking away from my normal schedule and will be posting every day this week as follows:

  • Part 2 – Designing the workflow
  • Part 3 – Data: Processing, updating, working the magic
  • Part 4 – Data handover and the audit process
  • Part 5 – My preparation for the way forward

I’m very excited to write these posts, because I will cover everything that makes up an excellent Enterprise GIS solution: some programming stuff (more Python in my life is always better), some database stuff (SQL and file gdb), some GIS stuff (ensuring all those shapes are in the right place) and some interconnected stuff (eventually mobile apps and cloud services).

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