Extinction Clock – Final Production

Sara Ro and I continued to work on our Extinction Clock for our final.

First, a recap:

We’re developing this piece to audibly present data to promote conversation and action around conservation. Our goal is to present the data and immerse the viewer. Unfortunately, essential data can go unseen and, when shown, can be overwhelming. We are exploring new ways to make this data accessible.

We call the piece Extinction Clock; however, instead of a traditional visual clock, we will be working with audio and “vocal” message from individual species. Users will dial in the clock to a specific year and listen. The clock’s dial will be linked to the population data of the species, and whatever year had the highest population density will be mapped at total volume. As the population recedes or grows, the volume will change accordingly. We will call the API data to link with our audio files. We believe that using audio of species paired with the data will help viewers feel more connected to the species and think of them as living beings rather than numbers on a chart.

Single Page Application

When the viewer clicks on a year, a herd call of African Elephants will play, and the population size will be presented. The call volume is related to the species’ global population in that given year, with the Early 1800s being at 100% and the volume decreasing throughout the years.

We decided to reference an old clock with buttons going across the top for the final build.

Problems:

We’re still facing a couple of problems. The server is working perfectly. We’re receiving the calls correctly, but we have the buttons to call the server incorrectly. We need to change the code only to ping the server during a state change. This will prevent the 100+ calls from happening each time a button is pushed. Second, our audio is not working correctly. For some reason, it is distorted. Our next step is to re-wire the amp. We’re hoping to fix these problems over the break.

Below are our process images.

Extinction Clock Progress

Sara and I are developing a new piece to audibly present data to promote conversation and action around conservation. Our goal is to not only present the data but to immerse the viewer. Unfortunately, essential data can go unseen and, when presented, can be overwhelming. We are exploring new ways to make this data accessible.

We call the piece Extinction Clock; however, instead of a traditional visual clock, we will be working with audio and “vocal” message from individual species. The clock’s dial will be linked to the population data of the species, and whatever year had the highest population density will be mapped at total volume. As the population recedes or grows, the volume will change accordingly. Users will be able to dial in the clock to a specific year and listen. We will be calling on the API data to link with our audio files. We believe that using audio of species paired with the data will help viewers feel more connected to the species and think of them as living beings rather than numbers on a chart.

Device Progress – Endangered Species Clock

The big news this week is that the Red List rejected our application for an API token. Both Sara and I reached out individually, asking for clarification. We’re also looking to NYU resources to get a token.

In the meantime, we’re looking at the Nature Reserve API as a substitution.

For the final piece, we’ve been discussing making an auditory format clock. The volume of the call will match the species population size over time. We might also add a visual display to further emphasize the data.

Packet Sniffing

This week we were tasked with practicing packet sniffing.

I used the free, open-source software WireShark . For this exercise, I ran in on my computer while logged into the NYU network, and I wasn’t using my laptop at the time, so I only sniffed 459 packets.

I thought it would be interesting to take all the HTTP data and run the IP addresses through NS Lookup on my terminal. I wanted to see the companies that my information was traveling through. To do this, I filtered by HTTP and downloaded the data to a CSV file, and I then uploaded it to google sheets and isolated the IP address.

I noticed that most of my information was going through either amazon web services or google.

Next, I ran a tutorial on WireShark that allowed me to test a nonsecure HTTP website. You can see below that I was able to find both the user name and password. It’s fascinating how easily I was able to get that information and just how vital HTTPS is.

Tracerouting

I had so much fun with this assignment! Before this week, I was completely unaware of my web searchers’ journey before popping up on my screen! It really took me back thinking about how much work has gone into me getting cat memes quickly.

For this write-up, I focused on tracing my website and google from my home network and studio. It was interesting to see how different the paths were, even though the two physical locations are only 1.5 miles away. Two things took me by surprise; first, when I traced Google from my studio, it went all the way to Austria. I do not understand that. Second, most of me searched from my home location went through Ashburn, Virginia after doing a little research I found out that Northern, Virginia contains “more than 100 data centers and more than 10 million square feet of data center space.” according to an article titled Equinix Expands in Ashburn, Plans Fleet of Four-Story Data Centers by Rich Miller. The entire article can be seen here.

Home Network:

My Website:

traceroute to 69.22.188.41 (69.22.188.41), 64 hops max, 52 byte packets

1 192.168.4.1 (192.168.4.1) 17.701 ms 4.762 ms 4.803 ms

2 * * *

3 100.41.23.156 (100.41.23.156) 11.109 ms 10.788 ms

100.41.23.154 (100.41.23.154) 10.732 ms

4 0.csi1.grcynygc-mse01-bb-su1.alter.net (140.222.3.206) 11.245 ms

0.csi1.whplnywp-mse01-bb-su1.alter.net (140.222.3.212) 11.641 ms

0.csi1.grcynygc-mse01-bb-su1.alter.net (140.222.3.206) 10.593 ms

5 * * *

6 0.ae3.br2.nyc4.alter.net (140.222.1.59) 13.313 ms

0.ae4.br2.nyc4.alter.net (140.222.1.61) 11.917 ms

0.ae3.br2.nyc4.alter.net (140.222.1.59) 14.212 ms

7 verizon-com.customer.alter.net (152.179.78.154) 12.663 ms 21.930 ms 13.422 ms

8 ae-2-3605.ear1.newyork1.level3.net (4.69.202.253) 10.972 ms

ae-1-3505.ear1.newyork1.level3.net (4.69.141.133) 13.904 ms

ae-2-3605.ear1.newyork1.level3.net (4.69.202.253) 20.201 ms

9 photoshelte.ear1.newyork1.level3.net (4.14.2.138) 13.710 ms 12.626 ms 10.113 ms

10 xe-0-2-3.cr2.nyc.bitshelter.com (63.141.214.43) 14.760 ms 12.401 ms 9.473 ms

11 le2.nyc.bitshelter.com (69.22.188.41) 12.732 ms 11.736 ms 12.085 ms

wildgeese@Alans-MacBook-Pro-2 ~ % nslookup www.google.com

Server: 68.237.161.12

Address: 68.237.161.12#53

Google

1 192.168.4.1 (192.168.4.1) 5.836 ms 4.623 ms 4.936 ms

2 * * *

3 100.41.23.154 (100.41.23.154) 11.176 ms 10.707 ms 10.386 ms

4 0.csi1.whplnywp-mse01-bb-su1.alter.net (140.222.3.212) 13.685 ms

0.csi1.grcynygc-mse01-bb-su1.alter.net (140.222.3.206) 16.654 ms

0.csi1.whplnywp-mse01-bb-su1.alter.net (140.222.3.212) 16.569 ms

5 * * *

6 * * *

7 0.et-9-0-5.gw15.nyc1.alter.net (140.222.1.81) 13.455 ms

0.et-9-0-2.gw15.nyc1.alter.net (140.222.1.43) 13.813 ms 10.820 ms

8 &#10.20.148.204.in-addr.arpa (204.148.20.6) 10.003 ms

72.14.208.130 (72.14.208.130) 11.312 ms 9.088 ms

9 108.170.248.97 (108.170.248.97) 9.775 ms 9.966 ms

10.252.243.222 (10.252.243.222) 12.378 ms

10 142.250.46.197 (142.250.46.197) 12.561 ms 11.884 ms

108.170.248.1 (108.170.248.1) 11.917 ms

11 108.170.248.20 (108.170.248.20) 11.732 ms

lga34s30-in-f4.1e100.net (142.250.64.68) 11.290 ms 16.258 ms

My Studio:

My Website

traceroute to 69.22.188.41 (69.22.188.41), 64 hops max, 52 byte packets

1 router.asus.com (192.168.50.1) 9.812 ms 1.288 ms 1.288 ms

2 * * *

3 g0-15-4-5.bstnma-lcr-22.verizon-gni.net (100.41.6.88) 11.718 ms 11.595 ms 6.344 ms

4 0.csi1.whplnywp-mse01-bb-su1.alter.net (140.222.3.212) 8.332 ms 8.549 ms

0.csi1.grcynygc-mse01-bb-su1.alter.net (140.222.3.206) 5.944 ms

5 * * *

6 0.ae4.br2.nyc4.alter.net (140.222.1.61) 8.136 ms

0.ae3.br2.nyc4.alter.net (140.222.1.59) 7.179 ms

0.ae4.br2.nyc4.alter.net (140.222.1.61) 6.820 ms

7 verizon-com.customer.alter.net (152.179.78.154) 7.322 ms 11.071 ms 9.831 ms

8 * * *

9 photoshelte.ear1.newyork1.level3.net (4.14.2.138) 13.789 ms 6.305 ms 7.508 ms

10 xe-0-2-3.cr2.nyc.bitshelter.com (63.141.214.43) 10.402 ms 13.270 ms 5.905 ms

11 le2.nyc.bitshelter.com (69.22.188.41) 8.399 ms 9.520 ms 6.887 ms

Google

traceroute to 142.250.65.196 (142.250.65.196), 64 hops max, 52 byte packets

1 router.asus.com (192.168.50.1) 23.906 ms 12.252 ms 3.303 ms

2 * * *

3 g104-0-0-30.phlapa-lcr-21.verizon-gni.net (100.41.6.240) 17.315 ms 5.793 ms 7.229 ms

4 0.csi1.whplnywp-mse01-bb-su1.alter.net (140.222.3.212) 8.899 ms

0.csi1.grcynygc-mse01-bb-su1.alter.net (140.222.3.206) 8.036 ms

0.csi1.whplnywp-mse01-bb-su1.alter.net (140.222.3.212) 17.325 ms

5 * * *

6 * * *

7 0.et-9-1-5.gw15.nyc1.alter.net (140.222.230.215) 14.260 ms

0.et-10-0-2.gw15.nyc1.alter.net (140.222.1.45) 6.558 ms

0.et-9-1-2.gw15.nyc1.alter.net (140.222.227.25) 10.936 ms

8 72.14.208.130 (72.14.208.130) 8.799 ms

&#10.20.148.204.in-addr.arpa (204.148.20.6) 7.916 ms 6.110 ms

9 108.170.248.65 (108.170.248.65) 6.724 ms 11.725 ms

10.252.164.30 (10.252.164.30) 7.819 ms

10 142.251.60.232 (142.251.60.232) 9.612 ms

142.251.60.239 (142.251.60.239) 8.807 ms

142.251.60.237 (142.251.60.237) 8.747 ms

11 142.251.60.237 (142.251.60.237) 7.265 ms

lga25s72-in-f4.1e100.net (142.250.65.196) 9.040 ms 7.949 ms

NYTimes

traceroute to 151.101.209.164 (151.101.209.164), 64 hops max, 52 byte packets

1 router.asus.com (192.168.50.1) 7.700 ms 1.245 ms 1.249 ms

2 * * *

3 g0-15-4-5.bstnma-lcr-22.verizon-gni.net (100.41.6.88) 11.749 ms 9.508 ms

g104-0-0-30.phlapa-lcr-21.verizon-gni.net (100.41.6.240) 13.217 ms

4 0.csi1.grcynygc-mse01-bb-su1.alter.net (140.222.3.206) 29.958 ms 6.361 ms 7.163 ms

5 * * *

6 0.ae2.gw13.ewr6.alter.net (140.222.8.13) 10.855 ms

0.ae1.gw13.ewr6.alter.net (140.222.8.11) 6.183 ms

0.ae2.gw13.ewr6.alter.net (140.222.8.13) 17.332 ms

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