The OpenCPU System: Towards a Universal Interface for Scientific Computing through Separation of Concerns

TL;DR

The paper proposes a universal, language-independent API for scientific computing by separating domain concerns from implementation details, exemplified by the OpenCPU system built on HTTP and R.

Contribution

It introduces a conceptual framework for separating concerns in scientific computing and presents OpenCPU as an implementation that enables interoperability and scalability.

Findings

OpenCPU provides a simple, abstracted interface for statistical analysis.

Separation of concerns improves interoperability across programming languages.

The system addresses key bottlenecks in scalable scientific computing.

Abstract

Applications integrating analysis components require a programmable interface which defines statistical operations independently of any programming language. By separating concerns of scientific computing from application and implementation details we can derive an interoperable API for data analysis. But what exactly are the concerns of scientific computing? To answer this question, the paper starts with an exploration of the purpose, problems, characteristics, struggles, culture, and community of this unique branch of computing. By mapping out the domain logic, we try to unveil the fundamental principles and concepts behind statistical software. Along the way we highlight important problems and bottlenecks that need to be addressed by the system in order to facilitate reliable and scalable analysis units. Finally, the OpenCPU software is introduced as an example implementation that builds on HTTP and R to expose a simple, abstracted interface for scientific computing.