There’s an idea I want to write about: is information personal? I’ve been noodling for a while on what makes something an information problem vs. something else. What is the difference between data and information? In information school, we were taught that data is undifferentiated, and information is data in context. That has never quite sat well with me. I think it’s true, but I didn’t ever think it was the whole story. I think now I understand why: context is personal. Dealing with information is ultimately about dealing with individual uses of information. Information is ultimately used by an individual to satisfy an information need or create the knowledge required to do something. Data is necessarily large. Data needs to be large in order to make determinations about behavior at scale. But information is small. Information narrows down from data to be contextualized for an individual … even if there are many individuals who are similar and whose data context can be replicated many times over, at the end that information is going to enter an individual human brain and serve a purpose there. (And information comes from data; information is an instance of data, a singular representation of data.) If this is true, then information problems are those where individual bits of data need to be delivered to individuals in context. Data problems are those that are concerned with moving, storing, or analyzing large sets of data. It’s like weather vs. climate, perhaps. Today’s weather in Seattle at 2 pm on a Tuesday is information to me when I need to know how to dress or whether to take a rain coat. That same weather is a data point in larger calculations of climate — the weather in Seattle and Tacoma, Everett, Poulsbo, Bellevue, Kent, Mill Creek, Edmonds, and all the other communities in the area aggregate into a picture of regional climate. -- Also, when IAs talk about structure, we’re not talking about the specific structure of databases or repositories, though that may well be in our purview. The structure that IAs are most interested in, though, are the overall structures that reflect or illuminate a common understanding. For example, the structure of music genres that was assembled by Spotify is an example of a way of looking at music that had nothing to do with the technical representation of genres… at least until it was later codified as such. The structure needed to be explained first, then represented. --- **Relates to**: