Social Networks and Archival Context OpenRefine Plugin; Introduction of Opioid Alternatives in Addressing the Opioid Crisis
Shen, Victor, School of Engineering and Applied Science, University of Virginia
Ibrahim, Ahmed, EN-Comp Science Dept, University of Virginia
Jacques, Richard, EN-Engineering and Society, University of Virginia
Opioid crisis is a growing concern in multiple societies due to its high cost in opioid production and opioid overdose treatment plans from medical institutions. This crisis continues to persist due to the lack in awareness of other alternatives that could potentially replace opioid as the first-line treatment for pain relief. My STS research topic hopes to bring awareness to the public by introducing opioid alternatives that could be adopted as a form of pain treatment thus alleviating the opioid crisis. Moreover, my technical project focuses on a separate topic that revolves around building out a Social Networks and Archival Context (SNAC) plugin that allows users to import archival information; such as historical figures and their relationships other entities onto the SNAC database through a user friendly platform that requires little to no experience in using. The correlation between the STS research topic and the technical project ties around the concept of alleviation. By establishing the plugin, we allow our clients and users to utilize data normalization through a more convenient process that would significantly improve time efficiency for uploading archival information. In parallel, the introduction of opioid consumption alternatives brings a positive impact on combating the current opioid crisis through utilizing more cost-efficient approach to pain management.
The technical project utilizes OpenRefine, an existing open source project, for the purpose of building a standalone plugin for SNAC, an archival institution that collaborate with other institutions in building out an archival collection to allow public accessibility in sharing information. This plugin allows users to import different types of files consisting raw data on historical artifacts that will then be reconciled and uploaded onto the SNAC database within minutes compared to previous alternatives that would have taken users hours to individually upload each artifact. The plugin also effectively solved the issue of human error and data mismatch when uploading information which can further prevent more problems on the SNAC database.
My STS research revolves around the goal of spreading awareness of opioid alternatives that would potentially prevent further opioid overdose deaths. Most opioid overdose deaths are due to patients’ being prescribed opioids as a solution for their pain which can easily be replaced by a more health benefit and cost-efficient approach. As mentioned in the research paper, opioid alternatives include but are not limited to; the use of video games, non-pharmacological methods such as transcutaneous electrical nerve stimulation and acupuncture, and natural non-invasive approach such as yoga and therapeutic massage. As revealed by my research on these various of approaches, these alternatives show promising results in being a solution to the ongoing opioid crisis we face today.
In conclusion, both my research and technical projects illustrate the concept of alleviation where each individual component contributes to a technical and non-technical aspect of society, whether through a tangible approach such as the SNAC plugin or through an informative approach such as the introduction to opioid alternatives. Throughout the paper, various of sociotechnical tools were introduced in highlighting key components that may introduce further adaptation of these research thus revolutionizing our current understanding of both effective data normalization and opioid alternative methods.
BS (Bachelor of Science)
opioid crisis, SNAC, OpenRefine, plugin
School of Engineering and Applied Sciences
Bachelor of Science in Computer Science
STS Advisor: Richard D. Jacques
Technical Advisor: Ahmed Ibrahim
Technical Team Members: Charles Chang, Sandra Gould, Mark Jeong, John Perez, Peter Tran, Grace Wu, Jessica Xu
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