The Scientific Software Engineering Center (SSEC) at the University of Washington works with researchers across various disciplines to build robust software that bolsters inquiry and builds community. The resulting tools are open source and reusable, designed to sustain discovery beyond SSEC’s involvement in the projects. Further information and links to each of our projects can be found below.
GNATSS is an open-source software for processing Global Navigation Satellite Systems - Acoustic (GNSS-A) data for seafloor horizontal positioning. The software is a redevelopment of existing FORTRAN codes and shell scripts developed by C. David Chadwell for processing data including measurements made with Wave Gliders.
SSEC Engineer(s): Don Setiawan
Short description: Advancing Research and Collaboration in Seafloor Deformation
Website: https://escience.washington.edu/offshore-geodesy/
Project status: Under Development
Programming language: Python
Bug-tracking: https://github.com/uw-ssec/offshore-geodesy/issues
Git repository: https://github.com/uw-ssec/offshore-geodesy
NoisePy is a Python package designed for fast and easy computation of ambient noise cross-correlation functions. It provides additional functionality for noise monitoring and surface wave dispersion analysis.
SSEC Engineer(s): Carlos Garcia Jurado Suarez
Short description: Ambient Field Seismology in Python
Website: https://escience.washington.edu/noisepy/
Project status: Under Development
Programming language: Python
Bug-tracking: https://github.com/noisepy/NoisePy/issues
Git repository: https://github.com/noisepy/NoisePy
Echopype is a package built to enable interoperability and scalability in ocean sonar data processing. These data are widely used for obtaining information about the distribution and abundance of marine animals, such as fish and krill. Our ability to collect large volumes of sonar data from a variety of ocean platforms has grown significantly in the last decade. However, most of the new data remain under-utilized. echopype aims to address the root cause of this problem - the lack of interoperable data format and scalable analysis workflows that adapt well with increasing data volume - by providing open-source tools as entry points for scientists to make discovery using these new data.
SSEC Engineer(s): Don Setiawan
Short description: Enabling interoperability and scalability in ocean sonar data analysis.
Website: http://escience.washington.edu/echopype/
Project status: Active
Programming language: Python
Bug-tracking: https://github.com/osoceanacoustics/echopype/issues
Git repository: https://github.com/osoceanacoustics/echopype
Cerebral organoids are derived from induced or natural stem cells, including from mouse or human cells, within a laboratory setting. While their potential is astounding, they are currently only accessible to a select number of prestigious labs. SSEC is collaborating with researchers from UC Santa Cruz to democratize and scale access to WetAI, an online platform which enables remote experimentation for researchers, educators, and students.
SSEC Engineer(s): Cordero Core, Don Setiawan
Short description: Collaborative Neurobiology Research Platform
Website: https://escience.washington.edu/wetai/
Project status: Under Development
Programming language: Python, Github Codespaces
Git repositories:
- Braingeneerspy: https://github.com/braingeneers/braingeneerspy
- Braingeneers Docker Images: https://github.com/braingeneers/braingeneers-docker-images
- Braingeneers Research Template: https://github.com/braingeneers/research-template Education organization: https://github.com/Braingeneers-Education
Genetic testing is routinely relied upon to detect illegal trafficking of wildlife, the introduction of invasive species and pathogens, and monitor disease spread or outbreaks that can devastate the health of our ecosystems and communities. But few commercial diagnostic developers, who focus on only a small number of human diseases, feel an incentive to address the huge need for new tests. This leads to a limited number of commercially available tests that are heavily restricted to centralized laboratories, resulting in the global challenge of neglected diagnostics.
SSEC is working with Conservation X Labs to build an easy-to-use platform that enables researchers to rapidly create genetic tests for every pest, pathogen, or species in the field. This new platform and corresponding tools will enable the community to better monitor and protect vulnerable ecosystems.
SSEC Engineer(s): Aniket Fadia
Short description: Democratizing Genetic Testing
Website: https://escience.washington.edu/ssec-2023-neglected-diagnostics/
Project status: Under Development
Programming language: Python
Bug-tracking: https://github.com/uw-ssec/neglected-diagnostics/issues
Git repository: https://github.com/uw-ssec/neglected-diagnostics
