Mapping data flows (with fish)

Boxes, arrows, and line illustrations of IT system components
A map of the the IBM Netcool Operations Insight v1.6.0 system! We don’t need this level of technical detail (but we do have satellites).
  1. What “data” are we talking about?
  2. Who controls that data?
  3. Who can access it?
  4. Who pays for it

Who do you need in the discussion?

Like a design sprint or project kick-off, 8–10 people is a good start. You can do it with a larger group (and we have) but you might want to test it out with a few participants first to preview the sticking points. You could also give people a worksheet to fill out in advance and have them share at the meeting, or send it in if they can’t attend.

  • A research scientist, who has very specific data needs and wants to increase data collection (volume and velocity)
  • A lawyer, who needs to track and ensure compliance
  • A mid-sized vendor, who wants to be able to meet customer needs without making sixteen custom product lines
  • A fishing association, who would like to manage their own data system that connects to government services
  • A data manager, who needs to decide on APIs and handle the back-end design

What supplies do you need?

  • A white board with two colors of pens, and/or
  • Two packs of 3” x 5” stickies (great if you have two colors), or
  • A virtual display — Mural, Google Slides, the whiteboard in Zoom, Office360, etc
  • Someone to take notes
  • Someone to run the process (these last two can be the same person but it’s usually easier to have two, especially for a virtual gathering)

How long do you need?

No more than 3 hours. Take a break after 90 minutes. If it’s easy — great! End early and start fixing. If it’s way more complex than you thought, well, now you have a starting point to keep digging. Come back and try another part the next day.

Set up the mapping space

Across the top of our workspace, we’re going to write stages of the ‘data life cycle’ or ‘data value stream.’ The internet has plenty of examples of what constitutes a data life cycle (including one in the NOAA Fisheries Data Management policy). We use:

Plan | Collect | Transmit | Analyze | Share | Store

We keep Transmit in as its own step because the oceans aren’t fully wired (yet), so getting big files from boats to data centers may involve delays of days or weeks as well as postage. Look at a few examples and pick the phases you need to focus on but resist the urge to list more than seven. Cluster where you think things are fairly well agreed on; split out steps where you think there’s confusion.

Work from left to right in columns

Below your life cycle stage, start a column on the far left with the four questions:

  1. What “data” are you talking about?

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