WEBVTT 1 00:00:00.210 --> 00:00:01.043 All right, hey folks. 2 00:00:01.043 --> 00:00:02.250 So we're gonna do what we usually do here 3 00:00:02.250 --> 00:00:03.120 is look at a few examples 4 00:00:03.120 --> 00:00:05.130 and now we're thinking about the design, 5 00:00:05.130 --> 00:00:06.720 not necessarily the chart selection, the storytelling 6 00:00:06.720 --> 00:00:07.890 et cetera, here relates about the design. 7 00:00:07.890 --> 00:00:09.270 That's what this week is all about. 8 00:00:09.270 --> 00:00:11.550 So first, looking at a plate full of plastic, 9 00:00:11.550 --> 00:00:12.840 visualizing the amount of microplastic we eat. 10 00:00:12.840 --> 00:00:13.710 This comes from Reuters. 11 00:00:13.710 --> 00:00:15.287 You know, I use their examples a lot 12 00:00:15.287 --> 00:00:16.120 'cause they do great work. 13 00:00:16.120 --> 00:00:17.760 And by the way, you'll notice all of the Reuters stories 14 00:00:17.760 --> 00:00:18.930 use the same color palette, right? 15 00:00:18.930 --> 00:00:20.940 They always have this blue and mostly white. 16 00:00:20.940 --> 00:00:22.410 Otherwise, you know, they're very consistent branding. 17 00:00:22.410 --> 00:00:24.570 Anyways, so this is a journalistic story 18 00:00:24.570 --> 00:00:26.100 explaining the fact that we eat microplastic. 19 00:00:26.100 --> 00:00:26.940 All right, well what's microplastic? 20 00:00:26.940 --> 00:00:27.780 That's probably your first question. 21 00:00:27.780 --> 00:00:29.700 Fair enough, it's my first question and they cover it. 22 00:00:29.700 --> 00:00:30.533 Here's what microplastic is. 23 00:00:30.533 --> 00:00:31.980 Sesame seeds, microplastic. 24 00:00:31.980 --> 00:00:32.940 Okay, now I know what it is. 25 00:00:32.940 --> 00:00:33.780 How much do we eat? 26 00:00:33.780 --> 00:00:35.310 They get to that very quickly. 27 00:00:35.310 --> 00:00:36.277 Every week, five grams. 28 00:00:36.277 --> 00:00:38.372 All right, what's a gram? 29 00:00:38.372 --> 00:00:39.930 What's five grams? 30 00:00:39.930 --> 00:00:40.800 Well talk to me in ounces 31 00:00:40.800 --> 00:00:41.939 'cause I'm from the US, only ounces make sense. 32 00:00:41.939 --> 00:00:43.320 Two ounces or whatever it is. 33 00:00:43.320 --> 00:00:44.700 I still don't know that is in terms of eating. 34 00:00:44.700 --> 00:00:46.170 How about you show me. 35 00:00:46.170 --> 00:00:48.210 A hot and sour soup spoon heaping full. 36 00:00:48.210 --> 00:00:49.200 All right, I get it. 37 00:00:49.200 --> 00:00:50.100 How about every month? 38 00:00:50.100 --> 00:00:51.480 Four weeks time, four times five is 20. 39 00:00:51.480 --> 00:00:53.790 So about 20 grams, 21 it turns out. 40 00:00:53.790 --> 00:00:57.030 A nice bowl, half full, okay? 41 00:00:57.030 --> 00:00:58.920 Every six months, a big cereal bowl. 42 00:00:58.920 --> 00:01:00.741 Every year, a heaping plateful. 43 00:01:00.741 --> 00:01:02.820 So not a chart insight, 44 00:01:02.820 --> 00:01:04.080 just beautifully designed photography 45 00:01:04.080 --> 00:01:05.430 with these striking colors. 46 00:01:05.430 --> 00:01:08.820 And most importantly, it's making the data relatable. 47 00:01:08.820 --> 00:01:11.940 If you had told me I eat 250 grams of plastic a year, 48 00:01:11.940 --> 00:01:12.773 I would be just sitting there 49 00:01:12.773 --> 00:01:13.950 like thinking to myself like, what's a gram? 50 00:01:13.950 --> 00:01:14.910 How many ounces is that? 51 00:01:14.910 --> 00:01:16.440 Like, I would've no clue what that even means. 52 00:01:16.440 --> 00:01:17.700 A heaping plateful. 53 00:01:17.700 --> 00:01:18.690 Are you freaking kidding me? 54 00:01:18.690 --> 00:01:19.860 Like, this is visceral. 55 00:01:19.860 --> 00:01:20.693 I get it. 56 00:01:20.693 --> 00:01:21.526 This is strong communications. 57 00:01:21.526 --> 00:01:23.131 The choirs are all over this thing, right? 58 00:01:23.131 --> 00:01:25.050 This is, like we're talking about eating stuff. 59 00:01:25.050 --> 00:01:26.094 So make it about eating stuff. 60 00:01:26.094 --> 00:01:27.660 Like, how could you do this better? 61 00:01:27.660 --> 00:01:29.160 And beautifully, simply designed. 62 00:01:29.160 --> 00:01:31.680 Okay, another example, this is from "The New York Times." 63 00:01:31.680 --> 00:01:33.588 179 reasons you don't need to panic about inflation, okay? 64 00:01:33.588 --> 00:01:35.250 This is a scrolly telling experience. 65 00:01:35.250 --> 00:01:36.690 As you scroll, the story progresses. 66 00:01:36.690 --> 00:01:37.523 I love these. 67 00:01:37.523 --> 00:01:38.356 I make these myself. 68 00:01:38.356 --> 00:01:39.600 So, here's how the price of gasoline changed each month 69 00:01:39.600 --> 00:01:41.820 throughout 2019 compared to the previous year. 70 00:01:41.820 --> 00:01:43.500 So we can see that the price of gasoline 71 00:01:43.500 --> 00:01:44.610 almost entirely went down. 72 00:01:44.610 --> 00:01:45.990 It went up a couple few months here and there, 73 00:01:45.990 --> 00:01:46.972 but then coronavirus came 74 00:01:46.972 --> 00:01:50.190 and then what happened later in the year in 2021, 75 00:01:50.190 --> 00:01:52.440 inflation and price of gasoline went bananas, right? 76 00:01:52.440 --> 00:01:53.580 So the reason I'm showing this 77 00:01:53.580 --> 00:01:55.427 is these visualizations which we will see again 78 00:01:55.427 --> 00:01:57.810 and again and again throughout the story, are very simple. 79 00:01:57.810 --> 00:01:59.790 All they are is what's called a strip plot. 80 00:01:59.790 --> 00:02:01.290 It's a bunch of strips of color, okay? 81 00:02:01.290 --> 00:02:02.640 Each one representing this yes or no, 82 00:02:02.640 --> 00:02:03.540 up or down, good or bad, 83 00:02:03.540 --> 00:02:05.190 although in this case also intensity of color, how much? 84 00:02:05.190 --> 00:02:06.023 Right? 85 00:02:06.023 --> 00:02:06.960 Now, these strips of color 86 00:02:06.960 --> 00:02:08.280 also have these little up and down pointers, right? 87 00:02:08.280 --> 00:02:10.140 But that's just a dual encoding mechanism. 88 00:02:10.140 --> 00:02:12.210 Red means bad, blue means good. 89 00:02:12.210 --> 00:02:14.400 Red means the price went up, blue means the price went down. 90 00:02:14.400 --> 00:02:15.233 So there's just dual encoding 91 00:02:15.233 --> 00:02:16.260 it with color and the direction. 92 00:02:16.260 --> 00:02:17.130 It's a good strategy. 93 00:02:17.130 --> 00:02:17.963 By the way, "The New York Times" 94 00:02:17.963 --> 00:02:18.796 doing what I mentioned earlier 95 00:02:18.796 --> 00:02:20.250 using red and blue instead of red and green. 96 00:02:20.250 --> 00:02:21.622 Now, one of the things I love about this data story 97 00:02:21.622 --> 00:02:23.670 is that the entire data story 98 00:02:23.670 --> 00:02:26.580 is exclusively using this visualization. 99 00:02:26.580 --> 00:02:28.590 These, you know, all repeated again and again and again. 100 00:02:28.590 --> 00:02:30.240 Now, I think I've made the point already, I'll say it again. 101 00:02:30.240 --> 00:02:32.160 It makes sense to keep things fresh and interesting 102 00:02:32.160 --> 00:02:33.450 for your audience. 103 00:02:33.450 --> 00:02:34.283 For your projects, 104 00:02:34.283 --> 00:02:36.510 don't show up with 10 slides of bar charts. 105 00:02:36.510 --> 00:02:39.720 But if you are doing one single task 106 00:02:39.720 --> 00:02:40.620 and you have multiple slides about it 107 00:02:40.620 --> 00:02:41.820 or in this case an entire data story 108 00:02:41.820 --> 00:02:42.810 all about that one single idea 109 00:02:42.810 --> 00:02:44.190 of how did inflation perform over time 110 00:02:44.190 --> 00:02:45.570 for a hundred different categories, 111 00:02:45.570 --> 00:02:46.706 of course you should use the same visualization. 112 00:02:46.706 --> 00:02:48.090 Otherwise, I'll be distracted trying 113 00:02:48.090 --> 00:02:49.390 to figure out why you changed that. 114 00:02:49.390 --> 00:02:50.730 To the point about, by the way, 115 00:02:50.730 --> 00:02:52.830 not using just bar charts for your projects, 116 00:02:52.830 --> 00:02:53.790 just pick something different. 117 00:02:53.790 --> 00:02:55.470 Use lollipop charts or some other option 118 00:02:55.470 --> 00:02:56.640 that does a good job for a comparison, 119 00:02:56.640 --> 00:02:57.840 assuming that's your task. 120 00:02:57.840 --> 00:02:58.920 There are other options, okay? 121 00:02:58.920 --> 00:03:00.270 All right, so another little detail 122 00:03:00.270 --> 00:03:02.430 about this data story that I love is this. 123 00:03:02.430 --> 00:03:04.410 Look at this, inline visualization. 124 00:03:04.410 --> 00:03:05.850 New category, plane tickets comes up, boom. 125 00:03:05.850 --> 00:03:07.560 This little teeny strip plot right there. 126 00:03:07.560 --> 00:03:08.393 Fantastic. 127 00:03:08.393 --> 00:03:09.226 This is a great data story. 128 00:03:09.226 --> 00:03:10.950 Really nicely done, beautifully visualized, 129 00:03:10.950 --> 00:03:12.300 very creative ideas. 130 00:03:12.300 --> 00:03:13.133 But like you see, 131 00:03:13.133 --> 00:03:14.580 the entire data story with like one exception 132 00:03:14.580 --> 00:03:16.050 is all those visuals. 133 00:03:16.050 --> 00:03:16.883 Okay? 134 00:03:16.883 --> 00:03:17.970 Here's another one from "Der Spiegel" 135 00:03:17.970 --> 00:03:20.280 looking at the recent protests in Iran. 136 00:03:20.280 --> 00:03:21.861 And so as you go through the data story, you know, 137 00:03:21.861 --> 00:03:23.970 really good data storytelling, a lot of video in here 138 00:03:23.970 --> 00:03:25.050 to sort of support what's going on. 139 00:03:25.050 --> 00:03:27.240 And then we see this map and we see the map of Iran. 140 00:03:27.240 --> 00:03:28.842 And by the way, little design comment here, 141 00:03:28.842 --> 00:03:30.360 the outline of the map, 142 00:03:30.360 --> 00:03:34.230 the border is nice, thick, high contrast black line. 143 00:03:34.230 --> 00:03:35.360 This is Iran. 144 00:03:35.360 --> 00:03:39.950 The provinces are very subtle, thinner, gray lines. 145 00:03:39.950 --> 00:03:41.490 You know, a lot of times we're using software 146 00:03:41.490 --> 00:03:42.420 to create our maps 147 00:03:42.420 --> 00:03:44.100 and the software just makes all the lines the same weight, 148 00:03:44.100 --> 00:03:45.390 the same color, et cetera. 149 00:03:45.390 --> 00:03:46.890 But we can make decisions about this. 150 00:03:46.890 --> 00:03:47.723 From a design standpoint, 151 00:03:47.723 --> 00:03:49.320 this is a lot easier to read. 152 00:03:49.320 --> 00:03:50.670 I can still see where the provinces are, 153 00:03:50.670 --> 00:03:52.050 but especially when we start layering more information 154 00:03:52.050 --> 00:03:53.490 on it like all the protests, 155 00:03:53.490 --> 00:03:55.704 I'm not distracted by the province borderers. 156 00:03:55.704 --> 00:03:57.600 So this is another scrolly telling experience, 157 00:03:57.600 --> 00:03:59.580 text scrolls by, some in-line videos scroll by, 158 00:03:59.580 --> 00:04:01.260 telling the story of these protests. 159 00:04:01.260 --> 00:04:02.826 But as I can see from the legend, the key 160 00:04:02.826 --> 00:04:06.360 the bubble size shows me how many protests there were. 161 00:04:06.360 --> 00:04:07.620 And of course the location tells me where they were. 162 00:04:07.620 --> 00:04:09.180 So yeah, Tehran is the largest bubble, 163 00:04:09.180 --> 00:04:10.410 clearly the largest population 164 00:04:10.410 --> 00:04:12.300 but they're big protests and you know smaller, 165 00:04:12.300 --> 00:04:14.160 but still decent number of protests all over the country 166 00:04:14.160 --> 00:04:15.840 which many people probably wouldn't be aware of. 167 00:04:15.840 --> 00:04:17.490 Long story short, as this story progresses 168 00:04:17.490 --> 00:04:19.860 we get a little design nuance that comes in, 169 00:04:19.860 --> 00:04:20.880 which comes in very soon. 170 00:04:20.880 --> 00:04:21.930 Here we go. 171 00:04:21.930 --> 00:04:25.140 Look at these evocative trails of blood, right? 172 00:04:25.140 --> 00:04:28.230 Bringing some emotion, some humanity into the story 173 00:04:28.230 --> 00:04:29.280 as it talks about the people, 174 00:04:29.280 --> 00:04:30.360 you know specific people whose lives 175 00:04:30.360 --> 00:04:32.730 are actually lost during these protests. 176 00:04:32.730 --> 00:04:33.600 Beautifully done. 177 00:04:33.600 --> 00:04:34.433 Great design. 178 00:04:34.433 --> 00:04:36.570 I believe that these dots are reflecting the provinces 179 00:04:36.570 --> 00:04:38.250 from which, you know, where the protests occurred 180 00:04:38.250 --> 00:04:39.746 where then these people passed 181 00:04:39.746 --> 00:04:41.820 after the protest or during the protest. 182 00:04:41.820 --> 00:04:43.906 So just, you know, nice design, very evocative. 183 00:04:43.906 --> 00:04:46.350 Part of storytelling is connecting with people emotionally. 184 00:04:46.350 --> 00:04:48.458 Not always, but this is one of the ways of doing it. 185 00:04:48.458 --> 00:04:51.360 Last but not least, visualizing the biomass of life. 186 00:04:51.360 --> 00:04:53.308 This is a great infographic, came out a couple years ago. 187 00:04:53.308 --> 00:04:54.960 What we're looking at here 188 00:04:54.960 --> 00:04:57.930 is if you took all animals, 189 00:04:57.930 --> 00:05:02.323 every animal on earth, and you weighed just their carbon. 190 00:05:02.323 --> 00:05:04.710 So that element, that actually is sort of like the core 191 00:05:04.710 --> 00:05:06.570 of all living beings, right? 192 00:05:06.570 --> 00:05:07.410 Carbon. 193 00:05:07.410 --> 00:05:09.480 Literally just weigh the carbon of all animals. 194 00:05:09.480 --> 00:05:12.777 Arthropods, it would add up to one gigaton of carbon. 195 00:05:12.777 --> 00:05:16.110 The next largest group by this weight would be fish. 196 00:05:16.110 --> 00:05:17.760 Then annelids and then da, da, da, da, da. 197 00:05:17.760 --> 00:05:18.660 Humans are down here. 198 00:05:18.660 --> 00:05:20.940 Birds make up the least of all biomass 199 00:05:20.940 --> 00:05:22.410 if you weighed their carbon, okay? 200 00:05:22.410 --> 00:05:24.006 If you just reduced us all to just carbon. 201 00:05:24.006 --> 00:05:26.700 Then, by the way, we noticed that this is actually animals. 202 00:05:26.700 --> 00:05:29.040 But look at it in context with plants. 203 00:05:29.040 --> 00:05:31.020 Ridiculously, you know, multiply this by a factor of, 204 00:05:31.020 --> 00:05:32.962 I don't even know how many, a hundred or something, 205 00:05:32.962 --> 00:05:33.870 50, 30, whatever it is. 206 00:05:33.870 --> 00:05:35.940 Bacteria, way more biomass is from bacteria 207 00:05:35.940 --> 00:05:38.160 than from animals et cetera, et cetera. 208 00:05:38.160 --> 00:05:40.410 So why do I show this one in this segment about design? 209 00:05:40.410 --> 00:05:41.243 Well, a couple things. 210 00:05:41.243 --> 00:05:43.718 One, this is using 3D charts 211 00:05:43.718 --> 00:05:45.960 and I mentioned the other day 3D is terrible, 212 00:05:45.960 --> 00:05:47.576 don't use 3D, but sometimes 3D works. 213 00:05:47.576 --> 00:05:48.780 Works here, I love it. 214 00:05:48.780 --> 00:05:49.680 Does not distract. 215 00:05:49.680 --> 00:05:51.300 I feel like I do understand the relative comparisons 216 00:05:51.300 --> 00:05:52.133 of things. 217 00:05:52.133 --> 00:05:53.070 No harm to the 3D here. 218 00:05:53.070 --> 00:05:54.870 Secondly, really nice color palette. 219 00:05:54.870 --> 00:05:56.430 You know, bright, fresh colors. 220 00:05:56.430 --> 00:05:57.810 So even though I'm all about do less minimalism, 221 00:05:57.810 --> 00:05:59.916 I love Reuters all gray, except for that one blue, 222 00:05:59.916 --> 00:06:01.320 you know, if you can pull it off 223 00:06:01.320 --> 00:06:02.478 and very few people can so be cautious. 224 00:06:02.478 --> 00:06:04.220 Some people have a really good sense of color 225 00:06:04.220 --> 00:06:06.060 and can put together a pretty diverse color palette 226 00:06:06.060 --> 00:06:06.893 and it works. 227 00:06:06.893 --> 00:06:08.933 So if you can do that, you're a very lucky person. 228 00:06:10.014 --> 00:06:10.847 Finally, I say do less. 229 00:06:10.847 --> 00:06:11.680 Yes, do less. 230 00:06:11.680 --> 00:06:12.780 Overall, this is a pretty simple design. 231 00:06:12.780 --> 00:06:13.740 It's just a bunch of cubes. 232 00:06:13.740 --> 00:06:15.120 But they weren't afraid to also put the crab 233 00:06:15.120 --> 00:06:16.794 and the barnacles and the other stuff on here. 234 00:06:16.794 --> 00:06:19.020 This is really not do less, right? 235 00:06:19.020 --> 00:06:21.608 So, thoughtful creative design 236 00:06:21.608 --> 00:06:23.970 with an overall do less spirit 237 00:06:23.970 --> 00:06:25.230 meaning that it's just cubes. 238 00:06:25.230 --> 00:06:26.520 The design is subtle still, 239 00:06:26.520 --> 00:06:27.816 the colors it's not distracting me. 240 00:06:27.816 --> 00:06:29.370 This is beautifully designed. 241 00:06:29.370 --> 00:06:30.690 And the information hierarchy is cool too. 242 00:06:30.690 --> 00:06:32.520 'Cause it starts off with animals, a thing we care about. 243 00:06:32.520 --> 00:06:33.450 And then with the sort of the punchline, 244 00:06:33.450 --> 00:06:34.776 it's like, ooh, look, 245 00:06:34.776 --> 00:06:35.609 but we're like nothing compared to bacteria, right? 246 00:06:35.609 --> 00:06:36.720 So like the way it flows vertically even makes sense. 247 00:06:36.720 --> 00:06:38.086 So good lessons in layout, good lessons in color, 248 00:06:38.086 --> 00:06:40.170 good lessons in doing less 249 00:06:40.170 --> 00:06:42.265 simultaneously with lessons in don't be too uptight 250 00:06:42.265 --> 00:06:43.321 about doing less. 251 00:06:43.321 --> 00:06:45.570 So, that's what I got for you here today. 252 00:06:45.570 --> 00:06:46.654 A bunch of really cool examples. 253 00:06:46.654 --> 00:06:49.890 I hope you've latched onto at least 5, 10, 15 little ideas 254 00:06:49.890 --> 00:06:51.304 in here that will influence the work that you do 255 00:06:51.304 --> 00:06:52.500 in your capstone project 256 00:06:52.500 --> 00:06:53.970 which is now coming up pretty darn fast. 257 00:06:53.970 --> 00:06:55.163 Can't wait to see it all.