The Unbearable Lightness of Being Open: On the Tyranny of Perfect Data
In the world of open data, we have a mantra: "Raw data now." It’s a call for governments, institutions, and corporations to release their information, unfiltered and unprocessed, into the public domain. The received wisdom is that this raw state is the purest, most honest form of data—a pristine digital artifact waiting to be analyzed and understood. But I want to push back against this notion. What if, in our zeal for purity, we’ve created a new kind of tyranny? The tyranny of perfect, yet utterly inaccessible, data.
We celebrate the act of opening the vault, but we often forget that a pile of unassembled parts is not a functioning machine. A terabyte of CSV files dumped on an FTP server, without a data dictionary, without context, without a narrative of its own collection methodology, is less a public good and more a digital cairn. It’s a monument to openness that few can actually decipher. This isn't open data; it's abandoned data.
The Burden of Interpretation
This practice places an immense and often unfair burden of interpretation onto the citizen, the researcher, the journalist. It assumes a level of technical literacy and spare time that simply doesn't exist for most people. The promise of open data is democratic access, but the reality of raw data dumps can be profoundly undemocratic. It creates a new elite—those with the skills, software, and patience to clean, parse, and make sense of the chaos.
The original custodians of this data possess the context. They know why certain fields are null, what the internal codes mean, which datasets are reliable and which are known to be buggy. By releasing it raw, they are not sharing knowledge; they are offloading the labor of creating knowledge. It’s a form of intellectual outsourcing, disguised as transparency.
True openness isn’t just about releasing the ones and zeros. It’s about releasing the story behind them. It’s the metadata, the glossaries, the explanations of oddities and errors. It’s an acknowledgment that data is not born in a vacuum; it is a product of human processes, with all the flaws and quirks that implies. A truly open dataset invites you in, explains the rules of the house, and shows you where the light switches are. A raw data dump simply pushes you through the door and locks it behind you.
Our pursuit of pristine, unmediated data is a beautiful but flawed ideal. It mistakes the medium for the message. The goal shouldn’t be to worship at the altar of the raw, but to build bridges of understanding. The most valuable open data isn't the data that is perfectly clean, but the data that is perfectly clear. Let’s stop praising the dump and start demanding the dialogue.
Notes & further reading
A few pages I came back to while writing this: