What Infrastructure Does Civil Society Need?

I recently had the chance to look closely at the work of a group of organizations. They were different sizes, working with different communities, over different lengths of time. The smaller organizations had a harder time. They had clarity on the job ahead of them and on their own community. They didn’t have the density of data over time that allowed them to talk about their impact.

I’ve been turning this over since, and I don’t have it worked out. Here are the pieces I’m trying to fit together.

  1. What’s missing feels like the ability to try out different scenarios before you implement them in real life. It seems that is some of what data can give an organization. An ability to build scenarios, model an intervention and see its likely impact. That modeling is a tool to allow the community members to discuss and own desired impact.

  2. A small organization already has three things, and they are not the same. Data, knowledge, and expertise. I’ve been thinking hard about how they differ. Data fits in a spreadsheet, who lives here, where the roads run, what the health needs are. Knowledge fits in a document, more and more a markdown file, the foodways of a place, how people actually move through a food pantry, what’s been tried before. Expertise is something else. It’s how we read the data and the knowledge together in a particular situation, and the decisions we make as we see them come together.

  3. Two of those can be packaged. The third cannot and shouldn’t be. Data travels easily. Knowledge travels as an artifact, though it carries its context with it and lands differently somewhere else. Expertise doesn’t travel at all. At our best in civil society, expertise is what we in the community know and think—and, this matters, what we know because we work on things together. You can’t ship that. A skills file catches a little of it, the method, how a group tends to read a situation, and it helps. The rest lives in the room. So the job of any infrastructure is not to replace that judgment. It’s to give it more to work with.

  4. The tools to hold data already exist, and the picture is still never complete. Esri’s Tapestry and Living Atlas, Google’s Data Commons, Esri’s work on digital twins—these show we can assemble and serve a rich data picture, and even use it to experiment before we act. That part is real and it’s here. But take a concrete problem: feeding your neighbors. To do it well you need to know who has a commercial kitchen, who has refrigeration, who has a loading dock, and what the community’s foodways actually are. Some of that comes from the commons—demographics, roads, health data. The rest we have to gather ourselves. And gathering it is exactly the work a small organization doesn’t have the capacity for. If every group builds its picture from scratch, we’ve rebuilt the problem we started with.

  5. So the infrastructure I’m after isn’t the data. It’s the shared way in. We can’t make it every organization’s job to set this up. What the sector needs is a cheap, shared way to add local data and local knowledge to what the commons already holds—a common container and method, so one community’s effort isn’t thrown away, and so the group down the road can build on it instead of starting over. The markdown files are a hint of what the knowledge half of that might look like.

The way I’m using it, expertise is really two things: interrogating the data and the knowledge together, and then making a set of decisions aimed at doing better next time. What lets a community do that together—see what it has, see the alternatives, test them against what it knows to be true—I don’t know yet. We can build the data layer; Esri and Google largely have. Whether we can build the layer that helps a community actually decide together is the open question. It’s the part I’m really thinking on.