Endangered Data

Visualizing the Changing Climate

By Zachary Norman

FOLLOWING THE 2016 elections, information scientists, librarians, and laypeople began to backup or mirror publicly-available government datasets from institutions such as the Environmental Protection Agency, the National Oceanic and Atmospheric Administration, and the National Aeronautics and Space Administration onto private servers and personal computers. This was done in response to the growing concern that data confirming the reality of anthropogenic global warming might be subject to manipulation, repression, or erasure by the Trump Administration. Endangered Data represents an algorithm that can be used to preserve and transmit this vulnerable data[1] by storing it within the pixels of digital images using an encryption method known as steganography.

Using the steganographic algorithm developed for this project, I have stored select data from the Carbon Dioxide Information Analysis Center (CDIAC) FTP Archive within each of the images shown here. The CDIAC contains data sets relevant to studies of greenhouse gases and global warming. The data I’ve chosen for these images were collected at the Trinidad Head, California measurement station. This station measures quantities of greenhouse gas species in the Earth’s atmosphere including, but not limited to: methane, nitrous oxide, CFC-12, methyl chloroform, carbon tetrachloride, and carbon monoxide.

The base image here is a photograph taken near the Trinidad Head station. The steganographic algorithm dictates that within the pixels of each of the images a year’s worth of measurement data should be stored, for the following years: 1997, 2001, 2004, 2007, 2010, 2013, and 2016. The discolorations seen in each image owe their appearance to the steganographic algorithm used to store the data, which includes measurements for various greenhouse gases. The script dictates that each character in a particular data file should be stored in a correspondent pixel in a given image. The ASCII value of that character is converted to a decimal value, and this value shifts the color of the correspondent pixel by that amount. For example, if a pixel has a red channel value of 100 and its correspondent data file character is the letter “R,” which has a decimal value of 082, then the pixel will shift by 82 bits, changing its red channel RGB value from 100 to 182. The images thus become increasingly discolored as the sequence progresses; as the average amount of methane in the atmosphere increases each year, the number of pixels used to store data also increases, proportionate to the increase in methane. Therefore, the 2016 image is more discolored than the 1997 image because the amount of methane measured in the atmosphere was greater for that year.

Endangered Data addresses three primary concerns. Firstly, it demonstrates a method by which steganography can be used to encrypt vulnerable data within the pixels of images in order to protect against attempts at manipulation or erasure. Secondly, because the data is hidden within images, it can be transmitted surreptitiously and retrieved using a decryption algorithm. Lastly, the steganography algorithm can be adjusted; the user has control over which pixels the data is stored within and by how much the color of the pixels shifts. Inverting the premise of obscuring data, the user instead helps visualize the catastrophic outcomes of global warming implied by the data itself, creating both metaphor and meaning through the image.

1 Datasets used in this project are obtained from the Carbon Dioxide Information AnalysisCenter (CDIAC) FTP Archive, which contains information on greenhouse gas measurements taken from various sites across the globe.

Zachary Norman is a multi-disciplinary artist and educator based in Salt Lake City, Utah. He is a 2019 Artist-in-Residence at the Utah Museum of Contemporary Art.