What is truth in data and information?

This topic was discussed recently, when we gathered for the EU Project Optique Summit II in Frankfurt. From a data and information point of view, trusted information should be truthful, essential, relevant and expected. But what does it really mean?

One interesting example is the code of ethics for journalists;  https://www.spj.org/pdf/ethicscode.pdf. If journalists were perfectly honest, fair and courageous in gathering, reporting and interpreting information, then we would most likely trust the written word. But that is not the case. Instead we find that journalists create and use data and information to serve special interests, they build and promote commercial and political opinions, many times based on pure economic reasons or a chance to access influence and power.

In the code of ethics one can find approaches that could lead to truthful information; test the accuracy of information against its source (authenticity), find more sources to prove the reliability of information, be generous with source references, avoid misrepresentation and distortion, never plagiarize, tell the story even when it is unpopular to do so, avoid stereotyping, support the open exchange of views, give a voice to the voiceless; official and unofficial information can be equally valid, distinguish between advocacy and news reporting and distinguish news from advertising.

I just wanted to write about this, without getting into the philosophical and mathematical theories/definitions of truth. Enough is said about that. In short one could say that truthful data has a known origin (authenticity) and its data syntax can be referenced and verified. Truthful information (data with a context) reflects an observable reality, relating it to a subjectively perceived context. Data is therefore by definition objective and information is subjective.

One last thing about truth. Everything that we observe and experience needs to be true, if we are going to interact and base our decisions on the right premises. A sensor on a spacecraft that delivers false/faulty data can cause catastrophic outcomes. A journalist that spreads false reports can alter the outcome of an election. We are constantly bombarded with misleading and untruthful information, like the food industry that claims products to be healthy when they are not. We need therefore tools that can help us to test and verify the quality, authenticity and accuracy of information. DNVGL is working to develop the ISO-8000 standard for Information Quality, that might be a step in the right direction.