Overview
The article introduces Shan He, a senior data visualization engineer at Uber, who played a pivotal role in developing kepler.gl, an open-source geospatial framework. It explores her journey from architecture to data visualization, the significance of open-source tools, and how kepler.gl empowers users to create insightful maps from geospatial data.
What You'll Learn
1
How to leverage kepler.gl for visualizing large-scale geospatial data
2
Why open sourcing tools like kepler.gl benefits the developer community
3
How to contribute to open-source projects effectively
Key Questions Answered
What is kepler.gl and how does it function?
kepler.gl is a web-based application designed for visualizing large-scale geospatial data. Users can easily create maps by uploading CSV or JSON files, enabling fast exploration and interaction with the data. It supports rendering over 1 million points, allowing users to filter and aggregate data visually.
What challenges does Shan He face in open sourcing software?
Shan He mentions that the emotional challenge of open sourcing software is the visibility of one's code, which can be critiqued by others. Additionally, there is pressure to ensure that the code behind visually appealing tools is robust and well-structured, which can be daunting for many developers.
How did Shan He transition from architecture to data visualization?
Shan He transitioned from architecture to data visualization by combining her interests in design and computer science. She began taking computer science classes and sought opportunities to apply her design skills in coding, ultimately leading her to a research position in data visualization at MIT before joining Uber.
Technologies & Tools
Frontend
Kepler.gl
Used for visualizing large-scale geospatial data in the browser.
Frontend
Deck.gl
A WebGL-powered framework that kepler.gl is built upon.
Key Actionable Insights
1Consider exploring kepler.gl for your next geospatial data project to simplify the visualization process.kepler.gl allows users to create insightful maps without extensive coding knowledge, making it accessible for data scientists and engineers alike.
2Engage with the open-source community by contributing to projects like kepler.gl to enhance your skills and network.Contributing to open-source projects can provide valuable experience, improve your coding abilities, and connect you with like-minded professionals in the field.
3Utilize visualization tools to quickly validate hypotheses and gain insights from data.By using tools like kepler.gl, you can streamline the data exploration process, allowing for faster decision-making and more effective data-driven strategies.
Common Pitfalls
1
One common pitfall in open sourcing software is the fear of having one's code critiqued publicly.
This fear can stem from the desire to maintain a good reputation as a developer. To mitigate this, it's important to focus on writing clean, maintainable code and to seek feedback from trusted peers before making it public.
Related Concepts
Data Visualization Techniques
Open-source Software Development
Geospatial Data Analysis