{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/157820"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/157820","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Database and Application Programming Interface Development for Rotational Spectroscopy","abstract":"The Species-agnostic Automated Gas Analyzer (SAAGA) project aims to automate the detection and characterization of chemical compounds in a complex chemical mixture in the gas phase through experimental rotational spectroscopy and computational tools. A database of spectroscopic data serves as the foundation of the automation pipeline for assigning spectral lines to species. While there are existing databases available for use, we developed our custom database, named SAAGAdb, and an application programming interface (API) to access the database to fulfill the needs of SAAGA. SAAGAdb is designed to store structured, high quality spectroscopic data of all species not limited to astrochemically relevant ones, enabling convenient data manipulation, integration into future automation pipelines, deployment, and maintenance. We implemented software development best practices, including software development life cycle, continuous integration/continuous delivery, and version control, to develop a PostgreSQL database with a Python API built on Django with RDKit integration. The product passed all unit tests and was successfully seeded with data. With the flexibility provided by the Django framework as well as detailed documentation of the software, SAAGAdb and its API can be easily improved and expanded in the future to suit the needs of the SAAGA project.","abstract_html":"The Species-agnostic Automated Gas Analyzer (SAAGA) project aims to automate the detection and characterization of chemical compounds in a complex chemical mixture in the gas phase through experimental rotational spectroscopy and computational tools. A database of spectroscopic data serves as the foundation of the automation pipeline for assigning spectral lines to species. While there are existing databases available for use, we developed our custom database, named SAAGAdb, and an application programming interface (API) to access the database to fulfill the needs of SAAGA. SAAGAdb is designed to store structured, high quality spectroscopic data of all species not limited to astrochemically relevant ones, enabling convenient data manipulation, integration into future automation pipelines, deployment, and maintenance. We implemented software development best practices, including software development life cycle, continuous integration/continuous delivery, and version control, to develop a PostgreSQL database with a Python API built on Django with RDKit integration. The product passed all unit tests and was successfully seeded with data. With the flexibility provided by the Django framework as well as detailed documentation of the software, SAAGAdb and its API can be easily improved and expanded in the future to suit the needs of the SAAGA project.","abstract_has_math":false,"creators":["Cheung, Jasmine So Yee"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. 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With the flexibility provided by the Django framework as well as detailed documentation of the software, SAAGAdb and its API can be easily improved and expanded in the future to suit the needs of the SAAGA project."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Database and Application Programming Interface Development for Rotational Spectroscopy"]}]}],"canonical_facts":{"dc:contributor.advisor":["McGuire, Brett"],"dc:contributor.department":["Massachusetts Institute of Technology. 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SAAGAdb is designed to store structured, high quality spectroscopic data of all species not limited to astrochemically relevant ones, enabling convenient data manipulation, integration into future automation pipelines, deployment, and maintenance. We implemented software development best practices, including software development life cycle, continuous integration/continuous delivery, and version control, to develop a PostgreSQL database with a Python API built on Django with RDKit integration. The product passed all unit tests and was successfully seeded with data. With the flexibility provided by the Django framework as well as detailed documentation of the software, SAAGAdb and its API can be easily improved and expanded in the future to suit the needs of the SAAGA project."],"dc:description.degree":["S.M."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/157820"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Database and Application Programming Interface Development for Rotational Spectroscopy"],"dc:type":["Thesis"],"thesis:degree_name":["Master","Master of Science in Chemistry"]},"updated_at":"2026-07-22T22:21:34Z"}