Our thesis is a cross collaboration between international relations and industrial engineering. We used a combination of database logic, programming, and Microsoft Visual Studio to organize and analyze Middle Eastern politics. Not only does the final product show raw data entry, but it also can answer complex questions about Middle Eastern relations- queries so complex that Google can’t answer them. We organized and analyzed geopolitical data to make it more accessible and easy, hopefully you enjoy!

Visualizations can be an incredibly powerful tool for communicating data. Data visualizations can summarize large data sets into one view, allow for easy comparisons between variables, and show trends or relationships in data that cannot be seen by looking at the raw data. Empirical information and by extension data visualizations are often seen as objective and honest. Unfortunately, data visualizations are susceptible to errors that may make them misleading. When visualizations are made for public audiences that do not have the statistical training or subject matter expertise to identify misleading or misrepresented data, these errors can have very negative effects. There is a good deal of research on how best to create guidelines for creating or systems for evaluating data visualizations. Many of the existing guidelines have contradicting approaches to designing visuals or they stress that best practices depend on the context. The goal of this work is to define the guidelines for making visualizations in the context of a public audience and show how context-specific guidelines can be used to effectively evaluate and critique visualizations. The guidelines created here are a starting point to show that there is a need for best practices that are specific to public media. Data visualization for the public lies at the intersection of statistics, graphic design, journalism, cognitive science, and rhetoric. Because of this, future conversations to create guidelines should include representatives of all these fields.

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on deep transcriptome sequences of adult skeletal muscle, lung, brain, and blood. The draft genome assembly for G. agassizii has a scaffold N50 length of 252 kbp and a total length of 2.4 Gbp. Genome annotation reveals 20,172 protein-coding genes in the G. agassizii assembly, and that gene structure is more similar to chicken than other turtles. We provide a series of comparative analyses demonstrating (1) that turtles are among the slowest-evolving genome-enabled reptiles, (2) amino acid changes in genes controlling desert tortoise traits such as shell development, longevity and osmoregulation, and (3) fixed variants across the Gopherus species complex in genes related to desert adaptations, including circadian rhythm and innate immune response. This G. agassizii genome reference and annotation is the first such resource for any tortoise, and will serve as a foundation for future analysis of the genetic basis of adaptations to the desert environment, allow for investigation into genomic factors affecting tortoise health, disease and longevity, and serve as a valuable resource for additional studies in this species complex.

Data Availability: All genomic and transcriptomic sequence files are available from the NIH-NCBI BioProject database (accession numbers PRJNA352725, PRJNA352726, and PRJNA281763). All genome assembly, transcriptome assembly, predicted protein, transcript, genome annotation, repeatmasker, phylogenetic trees, .vcf and GO enrichment files are available on Harvard Dataverse (doi:10.7910/DVN/EH2S9K).