My research examines the complexity of different types of software ecosystems from micro- to macro-level perspectives using emerging computational and visual analytic approaches. My core argument is that the scale, scope, and evolving dynamics of software ecosystems demand novel data-driven research methods and that we can support our understanding and augment decision making through interactive visual analytic approaches.
Some of my recent and ongoing studies include the examination of API and SDK ecosystems , digital platforms , digital infrastructures , dynamics of developer ecosystems , software alternatives , microservices , and global software startup ecosystems . Our investigations are enabled and driven by large-scale, heterogeneous (structured and unstructured) publicly available and proprietary data. Since the goal of my research is to create actionable insights, and not just archival knowledge, my lab develops interactive, visual, human-centered tools (e.g., ecoxight, graphiti, epheno, pulse, etc.) that enable exploration, discovery, and sensemaking of the structure and dynamics of such software ecosystems. A set of sample (static) visualizations at different software ecosystem levels is shown below.
Figure 1. Digital Infrastructure Configurations (Software Tools/Framework Level)
Figure 2. Hidden Platforms and Software Alternatives (Product-Level)
Figure 3. Partnerships in the Microservices Industry (Firm-Level)
There are many exciting open research opportunities in the study of software businesses, platforms, and ecosystems using visual analytics and machine learning that would be worthy of further discussion.