Researching the evolution of distributed systems
Ripple has invested heavily in research and development, with a view to advance the conversation around digital assets, smart contracts, and distributed ledgers. Ripple has been at the vanguard of high-profile litigation with the SEC, and is often looked to as a thought leader despite often receiving criticism regarding its centralised structure and the relationship between its success and that of XRP.
Ripple wanted to better understand and be able to visualise the evolution of digital ledgers over time, the growth and trends visible from transaction data, and the development of smart contract structures since 2014. They sponsored MDRx’s research to utilise our deep understanding of data science and distributed systems.
We ingested vast quantities of transaction, smart contract and code commit data. We achieved this through a combination of publicly available datasets augmented with our client’s own information.
We then used Raphtory, an open-source platform for distributed real-time temporal graph analytics, which allowed us to load and process large dynamic datasets across time. We created a time series analysis, and derived insights from this that allowed us to construct and test hypotheses around the developments and trends that emerged over time, including their origins. We used predictive analytics to make data-backed suggestions as to the likely future state of the market, many of which supported Ripple’s ongoing discourse.
The end-to-end data pipeline was mostly written in Python, all by our talented London-based engineers.
We wrote up an academic-leaning paper to document our work and conclusions and included accessible data visualisation to convey the key learnings to readers of varying degrees of experience and knowledge.
- Charting history: We demonstrated the origins of blockchain technologies and other distributed systems, together with those of cryptoassets
- Data-backed discourse: We empowered Ripple to continue leading the global conversation around the nature of and benefits associated with cryptoassets, backed by quantifiable, evidence-based data
- Visualisation for all: We visualised our findings in an accessible manner, equipping Ripple to storytell to readers of all levels
- Predictive analytics: We made evidence-backed predictions for the future state of the market, including adoption curves and engineering trends