It absolutely does. You can be a morning person, you can be a night owl, you can be late, you can be early, it can be spring, it can be fall, it can be twelve minutes to midnight, time be time, mon. And you're right - I'm trained as an engineer. I had dreams of being a designer but when I discovered that they have no control or input into the actual mechanics of a thing (other than often complicating the simple) I opted out. Slagging on designers has been a pastime of mine for decades. You sound like a designer - you're looking for capital-T Truths. I'm an engineer - everything has a fudge factor. Designers wish to make statements. Engineers wish to solve problems. I think I see where our disagreement actually lies (and it's been a hell of a debate, so thanks for your patience). I look at WGS84 and know that it's a standard that's 33 years old but that every standard that came before it has been incorporated in it and that there is a heritage of cartesian map coordinates dating back to like 200BC. And I know that the lats'n'longs from 200BC were good enough, and when they weren't, they were translated into another system that was good enough and so on and so forth. I don't need capital-T truth. I need "good enough." I know that "good enough" works well in the service of those who seek capital-T truth and I recognize that my job is to give them the tools they need for their seeking. The life-blood of many American cities was drained when we redesigned everything for the automobile. I see that as a tragedy, and I recognize that it's exactly the example the author should have used (but didn't) when describing the design of different transport systems for different cultures. The white folx out in the 'burbs got a quick way to the mall while the poor folx in the city got six lanes of vehicular oblivion between them and the park and that fuckin' sucks. It's a usage issue, it's a cartographic issue, it's a culture issue, it's a technological issue. But we're talking mapping now, we're talking data. The particulate load at GPS xxx on date X/Y/Z was nnn. That's a universal truth. It is a data point, it is a context-free fact ready to be contextualized however scientists, designers, poets, artists, whatever choose to contextualize it. The author, on the other hand, says bilious shit like this: No it's not. Go get the fuckin' data. In fact, the paragraph I listed that from is a procedural listing of ways to get the fuckin' data. My fundamental argument is that the data doesn't care. Do not assign intentions and motives to the data. People care - people care a lot, and they should care a lot. What people do with data is pretty much... science. And science policy. And therefore policy. And therefore vital. I don't think universality is the norm. I think we naturally approximate our world to the precision we need to interact with it and no more. I think from the standpoint of the article, the maps we're making now are of greater precision than we (as people) need by far... but I'm sure they aren't nearly as precise as our gadgets would use in an ideal case. And I think that the "good enough" we need can come out of the "greater precision" of the gadgets without anybody's freeze peaches being taken.But we have found a nearly-perfect way to measure time. Doesn't that say a lot?
Yet it’s difficult to use maps to address structural inequality when geospatial data aren’t equitably distributed.
I think we're inching closer to fundamental first principles. That makes it easy to get one's hackles raised, but it is also why I find this debate so interesting. (More interesting than the article, fo'sho.) Last week I had a conversation with an agency where we talked through my CV and their job pool. I told them the (abridged) story of how I ended up with urban planning: basically, I thoroughly looked at architecture but found it to be too narrow, teaching you to become a hip designer and nothing useful. I looked at civil engineering but I don't enjoy doing math and the job prospects boiled down to "you're responsible for the math, you nerd" so I knew it wasn't something for me. Urban planning, being somewhere in between and touching on topics from history to psychology to economics to demography, felt to me like a much more interesting avenue to explore. (And I still think I made the right choice.) A year ago I did a MSc bridge design course at the very school of architecture that I dismissed six years ago. I liked the course but I was so glad I didn't do that for five years - my peers knew almost nothing about physics, mechanics, economics, psychology, geography or sociology, they just knew how to think about aesthetics and the rationale behind it. They were great at that, but I was the only non-architect in the room so I witnessed all those other considerations that do fucking matter being ignored 'cuz design, bro. And even though I have only skirted with construction mechanics, I had to be the guy pointing out that a 150ft span really can't be done with a 4" bridge deck. When the professor (a veteran bridge designer) explained how the sausage gets made, he said that making the design is only a small part of the work. The rest is going back and forth with the structural engineers to actually get something resembling the original design. But that wasn't part of the course, or any course given there for that matter. Can you really separate the two like that? Is data always objective enough to be something beyond the perils of humans? As an extreme example, some local governor here came up with the term 'horsification' and a measure 'average amount of horses per acre' to quantify the demise of the countryside due to an increase in horses. You could totally do a time series analysis classifying horses with aerial photography and some ML, getting the data, but you can't deny that the data is meant to create a problem that wasn't there before. In other words: because people care, because there are people with interests and motives and intentions involved, numbers are or aren't looked at, considered and / or chosen. Whether that is oppressive or not is another story, but 'just get the data' can definitely be countered with 'for whose benefit?'. Good enough for whom? Because what's good enough might be totally different depending on who you ask.I had dreams of being a designer but when I discovered that they have no control or input into the actual mechanics of a thing (other than often complicating the simple) I opted out. Slagging on designers has been a pastime of mine for decades.
My fundamental argument is that the data doesn't care. Do not assign intentions and motives to the data. People care - people care a lot, and they should care a lot. What people do with data is pretty much... science. And science policy. And therefore policy. And therefore vital.
You just did, dude. You just pointed out that the way our society works, for better or worse, is bridge designers that think you can do a 150' span with 4" deck (which can be done, just not the way they're thinking) ...and engineers whose life work is crushing their dreams. It's unfortunate because dollars to donuts the dream-crushers actually give a shit about what the bridge looks like and, frankly, the designers do care that it works, they're just not given the body of knowledge necessary to make the relationship anything but adversarial. Screenwriting works the same way - every screenwriter is told to write what they imagine with no constraints, I guess so they can learn just how hard it is to engage a thousand people into spending a hundred million dollars on the 20,000 words you banged out alone in a Starbucks off Ventura blvd. Which isn't far off from your local governor: So let's go with our horsification standard. I'm going to measure the horsification of a stretch of the Valle Grande in New Mexico at two points, historical and current because I'm lazy. For "current" I'm going to commission a satellite pass of the Valle and hire a grad student to count "horses." In order to distinguish between "horses" and "not horses" I'm going to need grazing rights records and animal registrations. Now that I've validated my model I'm going to give my grad student the last, best sat photos of the valle we didn't commission and have him count horses using his model. I now have two data points: horsification now and horsification, say, in 2013. Now I need to quantify "demise of the countryside." Good luck with that but let's say I opt for methane emissions, tax rolls, traffic counts, I dunno. Stuff I can actually get for the year in question. I now have two points of correlation that I think demonstrate that more horses = more "demise of the countryside." Thing is, all that data actually existed already - and if I want my argument to have any weight, I need to show my work. What I actually contributed to the conversation - a method for counting horses - may turn out to be a useful tool for other purposes. Meanwhile in the process of correlating horses with urban decay I've opened up an avenue of research, made some controversial statements and otherwise advanced the debate around ranching. The article you linked literally argues that we shouldn't map shit because it hurts peoples' feelings. I think we can both agree that peoples' feelings are going to be hurt. My overarching point is that data doesn't hurt feelings. USE of data hurts feelings. "Horsification" is probably a bullshit metric, but it's a higher-order derivative of scalar data. Scalar data goes into lots of metrics, bullshit and otherwise, and when we all debate whether they're bullshit or not we all win. You're going to have a tough time convincing me that simply measuring a value is EVER bad for society.Can you really separate the two like that?
As an extreme example, some local governor here came up with the term 'horsification' and a measure 'average amount of horses per acre' to quantify the demise of the countryside due to an increase in horses. You could totally do a time series analysis classifying horses with aerial photography and some ML, getting the data, but you can't deny that the data is meant to create a problem that wasn't there before.
Extra unfortunate since this used to not be the case - constructional engineering and architecture used to be one and the same field over here. That is a valuable distinction, and I agree with you.It's unfortunate because dollars to donuts the dream-crushers actually give a shit about what the bridge looks like and, frankly, the designers do care that it works, they're just not given the body of knowledge necessary to make the relationship anything but adversarial.
The article you linked literally argues that we shouldn't map shit because it hurts peoples' feelings. I think we can both agree that peoples' feelings are going to be hurt. My overarching point is that data doesn't hurt feelings. USE of data hurts feelings.
I'm a huge fan of Robert Maillart. BUT - he had a few fall into the river, as I recall. You could get away with that in the 1920s; not so much now.