Long-Term, High-Resolution Urban Aerosol Database for Research, Education and Outreach
A proposal in response to NASA MUREP PBI/HBCU Data Science Equity, Access and Priority for Research and Education (DEAP)
NASA DEAP is a NASA funded project between Morgan State University (MSU), UMBC, Howard University (HU), and NASA GSFC. will address all three objectives:
1. “Develop the research capacity and infrastructure of HBCU/PBIs to address Data Science strategic areas of importance and value to NASA’s mission and national priorities.”
Aerosols are important part of NASA’s climate research mission. Faculties and researchers from four institutions will work closely to develop a prototype aerosol dataset that is open and expandable, which not only will increase the Earth science data research capacity at HBCUs and an MSI, but also provide a base for future research development by adding NASA’s data to Morgan’s data science research, and adding new tools and skillsets in AI/ML in atmospheric research at MSU, Howard, and UMBC.
2. “Facilitate a broad impact base of research collaborations amongst HBCU/PBIs for developing and sharing skill development in Data Science.”
The Center for Equitable Artificial Intelligence and Machine Learning Systems at MSU specifically proposes to host an “Equitable Data Science Applications Workshop” in the third year of the proposed study. The workshop will leverage Morgan’s existing data expertise, as well as share research experiences in the current study. Additionally, the workshop will facilitate information exchanges and continue learning among fellow faculties and students. We plan to invite students and faculties from both collaborating institutions and other HBCUs who are interested in data science applications.
3. “Promote additional opportunities for continuous learning through collaboration in producing tutorials and participating in peer learning experiences in data analytics, computing, software development and data management, and finding innovative ways for students to be trained in Data Science.”
one of our project goals is to develop a temporally continuous and spatially uniform database with user friendly analytical tools and interactive graphics in order to reduce the data usage barrier for non-experts such as media, high school teachers, and public health officials. We also propose to incorporate this unique dataset in both data science and atmospheric science undergraduate teaching. We will further reach out to fellow faculties at MSU in different departments such as health, environmental sciences, geography, and journalism, by demonstrating and guest lecturing using the dataset and associated tools developed in the project.