EntSciLab | Understanding the Complexity of API Ecosystems
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Rahul C. Basole, Professor, Director, Georgia Institute of Technology, Stanford University, Tennenbaum Institute, College of Computing, School of Interactive Computing, PhD, Visualization, Analytics, Ecosystem
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Understanding the Complexity of API Ecosystems

Digital transformation is driven and accelerated by the rapid emergence of application programming interfaces (APIs). The Computational Enterprise Science Lab actively curates different datasets associated with the structure, dynamics, and performance of the API ecosystem and conducts data-driven analyses and visualizations about firm- and ecosystem-level activities.

Valuable insights can be gained by applying visual analytic techniques to understand complex, emerging ecosystem dynamics and evolving enterprise strategies. One such context is the application programming interface (API) ecosystem. APIs have grown dramatically in the past five years. These bits of code act as digital control points that set the terms for which data and services can be efficiently shared or “called” over the Internet.

 

While open APIs promise to create value, boost productivity, and offer strategic advantages for firms that embrace their use, they are not deployed evenly across firms or industry sectors. What sectors have attracted the most APIs? And what firms are situated at the core of the API ecosystem and which remain at the periphery? To better understand the broader structure of the API ecosystem, we leveraged a comprehensive curated dataset of more than 11,000 APIs and 6,000 mashups, across 329 sectors in one of our early studies of the API ecosystem. We converted the API data into a mashup network, where nodes represent APIs and edges represent if two APIs have been used jointly in a mashup. Edges are scaled proportional to the total number of mashups: the thicker the line, the more mashups were created using the corresponding two APIs. We then computed important network properties, including various centrality measures, to understand the position, prominence, and influence of APIs in the network. Finally, we visualized this network, identified and colored subcommunities , and sized nodes according to their influence (see Figure below). The network analysis reveals many interesting sectoral and firm-level differences.

For more information of our work on APIs and API ecosystems, please refer to our recent publications or contact the PI at basole@gatech.edu.

Related Publications

journal
Revealing the API ecosystem and enterprise strategy via visual analytics

PC Evans, RC Basole
Communications of the ACM 59 (2), 26-28
 doi     pdf

 

journal
Accelerating Digital Transformation: Visual Insights from the API Ecosystem

RC Basole
IEEE IT Professional 18 (6), 20-25
 doi     pdf

 

book chapter
On the Evolution of Service Ecosystems: A Study of the Emerging API Economy

RC Basole
Handbook of Service Science, Volume II, (eds. PP Maglio, CA Kieliszewski, JC Spohrer, K Lyons, L Patrício and Y Sawatani) 1-19
 pdf

 

conference
Visualizing the Geography of Platform Boundary Resources: The Case of the Global API Ecosystem
J Huhtamäki, RC Basole, K Still, M Russell, M Seppänen
2017 50th Hawaii International Conference on System Sciences (HICSS)
 doi     pdf

 

journal
The Digital Platform: A Research Agenda
M De Reuver, C Sørensen, RC Basole
Journal of Information Technology 33(2), 124-135
 doi     pdf