Meili is a Waiakea high graduate from the Big Island. She is currently pursuing a BS in computer science. She gained an interest in computer science while taking a logic class in high school. She is particularly interested in video game development. During her free time she enjoys running, swimming, writing, reading, and playing video games.

Home Island: Big Island
Institution when accepted: University of Hawaii at Hilo

Akamai Project: Automating Astrophysics Data System (ADS) Author Affiliation Curation

Project Site: W.M. Keck Observatory

Mentors: Matthew Brown, Peggi Kamisato

Project Abstract:

W.M. Keck Observatory’s twin optical and infrared telescopes are considered two of the most scientifically productive telescopes in the world. The data collected by these telescopes are used by astronomers all over the world to advance their research. In order to examine how far Keck data reaches in the astrophysics community we wanted to determine who is using Keck data to write publications, and what institution they are affiliated with. To solve this problem we designed a web application to pull author and author affiliation data from the astrophysics data system (ADS), based on a growing list of BibCodes of articles which have used Keck data. The new system will replace the old system of using a script to communicate with the ADS website and extract the required information to a text file, which is not the desired format. The base functionality of our new application was developed using Python to communicate with the ADS application programming interface (API). The user interface consisted of a webpage developed with HTML, CSS, and JavaScript. We linked these two components of the application using a pre-built Python web server which we modified for our purposes. The data collected by the web application will then be exported into a csv file which will be added to the Keck librarian’s records. This data will show the authors of publications using Keck data, and their affiliations. Knowing who exactly is publishing articles based off of Keck data can have implications when it comes to funding. Public and private funders want to see that Keck data is being used by the general scientific community, and our application makes that information readily available.