Rae Knowler is an Open Data developer based in Zurich with 13 years of experience translating scientific rigor into pragmatic web and API solutions. A materials scientist by training (BA/MSci, University of Cambridge), Rae pivoted into open data and backend web development, contributing meaningful fixes and enhancements to high-profile open-source projects like CKAN and its harvesting extension. At Liip she helps run the Open Data Guild, focusing on data harvesting, tagging consistency, authentication and templating issues that improve data quality and portal reliability. Rae combines a research mindset with hands-on Python and PHP work, often tackling subtle bugs and performance bottlenecks that make data platforms more robust and usable.
13 years of coding experience
St Bernard's High School for Girls, Westcliff-on-sea, Essex
BA and MSci, Natural Sciences (Materials Science and Metallurgy), BA and MSci, Natural Sciences (Materials Science and Metallurgy) at University of Cambridge
Contributions:1 review, 15 commits, 2 PRs in 6 years 9 months
Contributions summary:Rae primarily contributed to the backend logic of the CKAN extension, focusing on data harvesting and tag management. They implemented configuration options for tag munging, ensuring consistency with other extension configurations. Additionally, the user addressed a bug in the harvest queue by fixing the object retrieval mechanism and optimized performance. The contributions indicate a focus on improving the stability and configuration of the extension.
CKAN is an open-source DMS (data management system) for powering data hubs and data portals. CKAN makes it easy to publish, share and use data. It powers catalog.data.gov, open.canada.ca/data, data.humdata.org among many other sites.
Role in this project:
Back-end Developer
Contributions:1 review, 5 commits, 10 PRs in 5 years 8 months
Contributions summary:Rae primarily contributed to bug fixes and enhancements within the CKAN codebase. Their work involved modifying back-end code in Python, specifically addressing issues related to facet titles, user authentication, and data dictization. Additionally, the user made adjustments to the templating system and updated tests to reflect the code changes. These modifications improved data presentation, fixed potential bugs, and corrected data count discrepancies within the application.
portalspythondatadata-catalogdbpedia
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