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These are the user uploaded subtitles that are being translated: 1 00:00:00,000 --> 00:00:04,585 We can talk about the procedures that are related to the definition of a GIS, 2 00:00:04,585 --> 00:00:08,520 and probably a good way to think about this is as a flowchart. 3 00:00:08,520 --> 00:00:12,250 Is if you're thinking about a procedure for analyzing data, 4 00:00:12,250 --> 00:00:15,460 the idea is that you're trying to take data and create information, 5 00:00:15,460 --> 00:00:18,580 and there is a difference between those two definitions. 6 00:00:18,580 --> 00:00:21,105 Data, I think of them as 7 00:00:21,105 --> 00:00:27,900 sort of little isolated facts that exist beyond any kind of direct interpretation. 8 00:00:27,900 --> 00:00:33,180 So, if I record the fact that the temperature was a certain amount today, 9 00:00:33,180 --> 00:00:35,300 that's a point of data; 10 00:00:35,300 --> 00:00:38,460 but then if I take that and a bunch of other data points 11 00:00:38,460 --> 00:00:41,810 and then I interpret it or transform it in some way, 12 00:00:41,810 --> 00:00:47,790 that then becomes more valuable or I have a way of seeing more through it, like, 13 00:00:47,790 --> 00:00:52,890 "If I had temperature values for July and August, 14 00:00:52,890 --> 00:00:54,710 for year after year, I could eventually make 15 00:00:54,710 --> 00:00:57,840 the conclusion that it's really warm in July and August." 16 00:00:57,840 --> 00:01:00,465 Now, I know that's pretty obvious, but the idea is that's information, 17 00:01:00,465 --> 00:01:03,715 that's something beyond just individual data points. 18 00:01:03,715 --> 00:01:07,220 So, let's just take an example like housing suitability. 19 00:01:07,220 --> 00:01:10,490 If I'm looking for a house to buy in a city that I live in, 20 00:01:10,490 --> 00:01:12,290 and I'm trying to use different criteria to 21 00:01:12,290 --> 00:01:14,895 decide where should I look for a house to buy, 22 00:01:14,895 --> 00:01:17,545 we might look at things like school locations. 23 00:01:17,545 --> 00:01:21,315 We could create a buffer of distances from those schools to say, "Well, 24 00:01:21,315 --> 00:01:23,160 I want to live within a certain distance of a school, 25 00:01:23,160 --> 00:01:27,120 say have children, and I want them to not have to travel too far to get to that school." 26 00:01:27,120 --> 00:01:29,475 So, that would be one set of criteria, 27 00:01:29,475 --> 00:01:32,855 one set of data and we can say, "Okay." 28 00:01:32,855 --> 00:01:34,700 So, now, we have one data set. 29 00:01:34,700 --> 00:01:38,420 We're going to perform one operation on it using one type of tool, 30 00:01:38,420 --> 00:01:39,650 in this case a buffer, 31 00:01:39,650 --> 00:01:41,800 and that's going to provide us with one output. 32 00:01:41,800 --> 00:01:44,075 So, this is an input, 33 00:01:44,075 --> 00:01:46,775 a tool and an output. 34 00:01:46,775 --> 00:01:49,180 Sometimes a tool, it's referred to as a function, 35 00:01:49,180 --> 00:01:51,730 and so that's the basic idea, 36 00:01:51,730 --> 00:01:54,750 the building blocks of modelling for GIS. 37 00:01:54,750 --> 00:01:57,495 In other words, performing some kind of analysis. 38 00:01:57,495 --> 00:01:58,990 We might add more things to that. 39 00:01:58,990 --> 00:02:00,730 So, we have things like property values. 40 00:02:00,730 --> 00:02:03,500 We might say, "Well, what neighborhoods have values that are within 41 00:02:03,500 --> 00:02:07,290 my price range that are affordable to me versus areas that are unaffordable?" 42 00:02:07,290 --> 00:02:08,570 So, we can use a different tool, 43 00:02:08,570 --> 00:02:10,260 in this case reclassifying, 44 00:02:10,260 --> 00:02:15,300 which will divide the data into different classes based on criteria that I'm interested. 45 00:02:15,300 --> 00:02:18,515 It could just be, like I said, affordable or unaffordable. 46 00:02:18,515 --> 00:02:21,690 We want to of course make sure that we're in a residential zone. 47 00:02:21,690 --> 00:02:23,590 We might look at crime statistics, 48 00:02:23,590 --> 00:02:26,840 and I'm just giving you a kind of a simple version here, 49 00:02:26,840 --> 00:02:30,110 but we could combine all of these things and what's known as a weighted overlay. 50 00:02:30,110 --> 00:02:31,615 In other words, looking at 51 00:02:31,615 --> 00:02:37,070 the same location with different variables and comparing those and saying, 52 00:02:37,070 --> 00:02:40,640 "Which locations across the city match all of the criteria that I'm 53 00:02:40,640 --> 00:02:44,455 interested in for my question that I'm trying to answer?" 54 00:02:44,455 --> 00:02:47,360 And the result would be a set of preferred areas 55 00:02:47,360 --> 00:02:50,240 that we could see in a map that would answer the question that we're interested in. 56 00:02:50,240 --> 00:02:53,540 And so, when we talk about procedures in a GIS, 57 00:02:53,540 --> 00:02:55,780 I know it may sound kind of vague or dry, 58 00:02:55,780 --> 00:02:56,810 but really what it is, 59 00:02:56,810 --> 00:02:59,480 is it's the steps that you're going through to take data, 60 00:02:59,480 --> 00:03:04,575 do something to it to transform it to create information that can then answer a question. 61 00:03:04,575 --> 00:03:07,075 That's really the way I think of the procedures. 62 00:03:07,075 --> 00:03:10,580 So, you may notice that there's one thing that's missing from 63 00:03:10,580 --> 00:03:14,660 our earlier definition of a GIS from this whole thing here, 64 00:03:14,660 --> 00:03:16,175 and that is people, 65 00:03:16,175 --> 00:03:18,445 and it may sound kind of funny. 66 00:03:18,445 --> 00:03:21,770 Some definitions of GIS don't include people. 67 00:03:21,770 --> 00:03:26,000 I like to include it because really people are the key ingredient. 68 00:03:26,000 --> 00:03:27,800 People like you, believe it or not, 69 00:03:27,800 --> 00:03:30,950 that you have to have someone who understands how to 70 00:03:30,950 --> 00:03:34,260 use all of this stuff in order to get something valuable, 71 00:03:34,260 --> 00:03:36,305 and productive and useful out of it. 72 00:03:36,305 --> 00:03:37,900 So, you can have the best hardware, 73 00:03:37,900 --> 00:03:40,140 best software, best data, best procedures, 74 00:03:40,140 --> 00:03:42,230 but if you don't have someone that can actually put all that 75 00:03:42,230 --> 00:03:45,730 together and work with it and create something of value, 76 00:03:45,730 --> 00:03:48,170 then the whole rest of it is pretty much useless. 77 00:03:48,170 --> 00:03:55,430 So, my goal is to be able to enable people to do these things for themselves. 78 00:03:55,430 --> 00:03:58,100 I love being able to watch people learn how to do things, 79 00:03:58,100 --> 00:04:01,220 so that they can then go off and find their own hardware, 80 00:04:01,220 --> 00:04:02,845 software, procedures, data and whatever, 81 00:04:02,845 --> 00:04:05,090 put it all together and then work with it; 82 00:04:05,090 --> 00:04:08,930 and I've also seen in organizations where they didn't have proper staff with 83 00:04:08,930 --> 00:04:12,840 proper skills and it was a lot of wasted time and energy, 84 00:04:12,840 --> 00:04:13,990 it was really inefficient. 85 00:04:13,990 --> 00:04:16,725 So, if you have the proper people with the proper training, 86 00:04:16,725 --> 00:04:18,320 skills and so on, it makes 87 00:04:18,320 --> 00:04:22,110 a huge difference in terms of the overall functioning of a GIS. 88 00:04:22,340 --> 00:04:26,064 So, that's our section on what is a GIS. 89 00:04:26,064 --> 00:04:28,730 I just wanted to give you some definitions, 90 00:04:28,730 --> 00:04:32,360 how to think about it in terms of what it can do and what it's made up of, 91 00:04:32,360 --> 00:04:35,225 give you some examples, the things like datasets and procedures. 92 00:04:35,225 --> 00:04:37,170 So, I hope that gets you thinking about it, 93 00:04:37,170 --> 00:04:39,055 and certainly we have a lot more to learn, 94 00:04:39,055 --> 00:04:41,630 but that's a great place to work from.8118

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