We believe in a future where biomedical scientists have access to the most advanced computational tools to conduct research and can build upon, extend, and adapt these tools to meet their needs.
We believe in a future where biomedical scientists have access to the most advanced computational tools to conduct research and can build upon, extend, and adapt these tools to meet their needs. With the Essential Open Source Software for Science (EOSS) program, we set out to support the maintenance, development, and community engagement of the most critical open source tools that researchers use on a daily basis — and to make the work of their creators and maintainers visible, recognized, and fundable.
In December 2019, we awarded 32 grants to support some of the most widely used open source software tools across biomedicine, as well as projects that provide foundational capabilities for data analysis, modeling, and data visualization. We’re now expanding our support for scientific open source software with 23 grants from the second funding cycle of the EOSS program. These grants represent a combined $8.8 million in funding and bring the total number of funded proposals to 55.
In the second RFA cycle, we received a total of 194 proposals, which were evaluated by CZI staff and external expert reviewers for their impact, project quality, feasibility, and the value of diversity, equity, and inclusion efforts. We highly value reuse of software as an indicator of impact. Proposals were evaluated for how widely used and useful they are in their relevant communities, as well as the health and maturity of their open source and community engagement practices.
These new grants extend the reach of the EOSS program to now include open source tools used in clinical medicine, two established libraries for biomedical workflows and pipelines, foundational support for real-time collaboration in notebooks, and widely used libraries to accelerate data analysis via parallel computing, graph analysis, and multidimensional data representation. We are also expanding our support to domain-specific open source software by funding widely-used tools in single cell biology, bioinformatics, genomics, imaging, and neuroscience. Read more about the projects we are funding in the second cycle of this program.
“Open source enables the democratization of science, allowing state-of-the-art computational methods to be implemented and extended anywhere in the world.” -Grantee William Noble, University of Washington, Percolator project.
Attendees at CZI’s Essential Open Source Software for Science kickoff meeting in Berkeley, CA. Photos by Scott Murphy/CZI.
Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments. Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.
Breakdown of a DBT Slack debate on the state of open-source alternatives to Fivetran and whether an OSS approach is more relevant than commercial software. In this article, we want to discuss the second point and go over the different points mentioned by each party. The first point will come in another article.
In this article, we want to discuss the second point and go over the different points mentioned by each party. The first point will come in another article. It’s more relevant to discuss whether an OSS approach makes sense before drilling down into the different alternatives.
Let’s talk about Open Data : According to the International Open Data Charter(1), it defines open data as those digital data that are made available with the technical.
Open source today is a word that often include a lot of things, such as open knowledge (Wikimedia projects), open hardware (Arduino, Raspberry Pi), open formats (ODT/ODS/ODP) and so on.