Berlin Wall Archive
Idea ConceptionVisualizing big data has always been an interest of mine and frequently found myself exploring various data visualization techniques. This, combined with my travels around the world, led me to revisit a long-standing fascination—the Berlin Wall. I became curious about how to systematically track and display the locations of Berlin Wall segments that have been scattered across the globe, and painted over since the fall of the wall in 1989. My goal was to combine data and art in a compelling way, experimenting with different methods to bring this information to life.
Berlin Wall Site
Collecting DataUpon initial research there were several legacy sites containing partial records of Berlin Wall segments worldwide, including location markers, images, and descriptions. Using Beautiful Soup, a Python package for web scraping, I compiled an initial dataset from publicly available sources. With this volume of data the goal moved over to ensuring consistency and removing duplicates posed an additional challenge, requiring some manual intervention. The biggest hurdle, though, was sourcing high-quality images of each segment—essential to creating an immersive and visually compelling experience.
Sourcing Images The images define the experience—curating a high-quality visual archive was crucial to the project’s success. However, automating image sourcing through web scraping yielded inconsistent and often unusable results. I quickly shifted to manually sourcing images online, carefully investigating each segment to find the best available photographs. Some segments had well-documented images that were easy to collect, while others required deeper research. Over time, I refined my search strategy—skipping poorly photographed segments and prioritizing sources with high-quality, straight-on images. When necessary, I also noted additional links or references for better-documented results. This manual curation process was time-consuming but ultimately key to making the visualization both accurate and impactful.
UI and UX Design
When designing the interface for this project, my focus was on creating multiple ways to engage with the data while balancing macro-level insights with individual storytelling.
To achieve this, I incorporated two primary viewing modes:
- Digital Image Viewer – A structured, qualitative viewing experience that presents Berlin Wall segments side by side, as if they were still standing together. This gallery-style format emphasizes the unique characteristics of each segment—graffiti, weathering, and preservation—while maintaining a sense of continuity.
- Globe View – A geospatial approach that maps each segment onto an interactive 3D globe, visualizing the wall’s global dispersion post-1989. This view provides a systemic perspective, allowing users to explore patterns in distribution and the historical impact of relocation efforts.
By integrating both viewing modes, the design bridges big data visualization with emotional resonance, transforming scattered historical artifacts into a unified, interactive experience that highlights both scale and individual narratives in a single, accessible format.
Sharing Data With the MVP site now created here I look forward to sharing the contents of my findings with the world.
Berlin Wall Site