When Steve Jobs passed away a few days ago, the news popped up on my Mac and I read his obituaries online. Somehow that seemed both natural and fitting. There were many, many angles in those obituaries. He was a CEO, technology visionary and showman but what struck me were all the mentions of his attention to detail.
One mantra he had was along the lines of “The hard part isn’t what to put in. The hard part is to know what to leave out.” Words like that have been uttered before but they got me thinking. Whenever I run across a thought that sticks with me, I ask myself what it has to do with what I do. That is, to family history.
Gathering vs Keeping
I spent Saturday afternoon translating at a genealogy event. As a patron spontaneously said to me, “I try to get my hands on ever record that I can about my people. I can’t settle for this little.” She was certainly right, she had too little and she knew it. A great start. So, what does leaving things out have to do with genealogy? What could it have to do with genealogy? Aren’t we looking to uncover whatever possible? Shouldn’t we be gathering as much evidence as we possibly can?
The quick answer to those questions is “yes” but, as the saying goes, that isn’t the hard part. The hard part is what to leave out. One aspect of leaving out is simply cutting away what is incorrect. Collect whatever seems like it might be helpful but don’t become so attached to it that you don’t realize that the record is not useful. It might be that we do not have the right person, even if at first glance (or even second and third glance) it seemed to be correct. That might seem trivial, of course what is wrong should be left out. On the other hand, in some corners of our research it is the hardest part. Disproving what seems to be true is not trivial. Even recognizing that something may be wrong is not trivial. It is generally better to gather information that turns out to be something we don’t want than to skip things that we wish we had kept. Eventually, we need to go through and cut away what does not belong.
Leaving Data In, Leaving Data Out—The Good, the Bad and the Ugly
What about when a record itself should be applicable? It is the right person, the right family but what the record tells us is, at some level, wrong. First we pull out what each record tells us but then we need to turn those records against themselves. We need to use some of the information they give to remove other parts of the information that they give. Anytime a process becomes self-referential like that, with one part influencing another that gets cycled around and reused from the beginning, strange things can happen. On the positive side, self reference gives us consciousness and introspection but use the bad information to whittle away the good and research can go very wrong. The more difficult the problem being researched, the more careful we need to be in winnowing the wheat from the chaff. A farmer knows the difference between the wheat and the chaff from the start. A researcher needs to be able to figure out the difference between them from the wheat and the chaff themselves. If we keep too much of the chaff and use that as a model for wheat, pretty soon as we go through our data we’re left with only problems.
Once I have some data and a hypothesis for what is happening, I like to file information into three categories. The first is “the good,” what should be kept and used. The information that fits the hypothesis in some way or that seems useful but weighs against the hypothesis. For one reason or another, this is the stuff that seems relevant. The second is “the bad,” what should be kept in case it isn’t so bad after all, or kept as a warning if it really is tempting but really wrong. “The bad” often serves as something like a map to a mine field. You do not actually want the mines but you don’t want to step on them either. Finally, “the ugly,” data that is simply confusing and might go either way. It may be right, it may be wrong but whatever it is it doesn’t quite fit.
Creating
I started this post with Steve Jobs. His accomplishment can perhaps be boiled down to taking the very technical—processors, memory chips and interfaces—and creating something that people actually found beneficial, something they actually enjoyed.
When technical research transitions into creativity, when it comes to passing on a story, we simply cannot pass on all the raw data. It might be informative, it definitely has its place and should be preserved, but it would hardly be a story, let alone a gripping story. We can’t include all the caveats that we have in a story. Part of the intellectual honesty that ought to come with research is the admission that errors are possible and caveats are necessary. Yet there is no room in a story for the continuous hedging of bets. We can’t take all the interesting tangents. By definition a tangent heads off in its own direction, away from the story’s main arch. At their best they can stand on their own legs as stories of their own. There are many things that must be left out at the stage when raw data, hypotheses and logic become something more like art. Part of the art is knowing what to leave out.
A designer knows he has achieved perfection not when there is nothing to add, but when there is nothing to take away.
-Antoine de Saint Exupéry