Truth is the best logical conclusion, based the data you use. If your data set is not complete the best logical conclusion you draw, without all the data, may be appear true, but it can be unintentionally false.
Science, for example, is a work in progress. As new technology appears and new data is generated, the best conclusions; theories, may need to be revised, to include all the new data. Until that time, what may be seen as the truth, will be defended like dogma.
In the Jan 6 trials, not all the data is being presented. The data is being limited to that which benefits one political party over the other. However, if you assume this is all the possible data, you will draw the conclusions that the data is designed for you to draw.
In math, if you were ask to plot data points on a graph, everyone will draw the same basic curve, with the same data points. But as we add new data, the curve may change. One can us use limited data to lie but appear to tell the truth, by simply cherry picking the data that others need to use to draw their conclusions.
Here is an interesting thought experiment, I designed it several years ago, that shows how our perception of truth is dependent on the data we have.
Picture a large mural on a wall. Like in Photoshop, I mask off most of the mural; cover it up, and only allow a small window to see a small part of the mural. The goal is to infer the truth of the mural. from only windows of data.
In this small window to the mural, we can see the face of a young woman who appears to be in anguish. Based on that limited data we may conclude she is heart broken and sad at her state in life.
Next, I open the window wider and can I see she is wearing what appears to be old tattered gym clothes. This add new data to the first conclusion. We conclude she is poor and maybe homeless. This may be part of what is breaking her heart.
I open the window of data even more and notice she appears to be in a gymnasium, with other women in the background, who are in various stages of standing and stretching. Some are in nicer clothes. Now our conclusion is different. She is not homeless, but in a gym. She appears to be working out. Her shabby clothes, may mean she has just started joined and is starting to get into shape.
I open the window of data even more and now I notice this is not a gym floor, but she is on a stage. We can see now other women on the side who are dancing like ballerinas. Now we conclude she much be part of a dance troupe. We assume she may be at tryouts, since she appears straining under the pressure.
Finally, we open the window all the way open to get all the data. We notice this a major city music hall and there is a famous dance coach on stage, who is pushing our woman, who is at center stage. She is the prima ballerina, in her lucky work out clothes, trying too prefect a very difficult move.
From any of the limited windows of data, almost nobody would be able to accept the final truth of her status as a prima ballerina. Since there was not enough data to make that an easy conclusion compared to the unintentional half truth that better fits the limited data. People will often prefer the partial truth conclusions, until they can see all the data, which they may not have access to.