2014/06/03 by Jeroen Ooms, Ooms, Jeroen · 1 voice · 1 citation
Computer Science · Decision Sciences · Mathematics · #Advanced Database Systems and Queries #Computation (stat.CO) #Data Analysis with R #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Mathematical Software (cs.MS) #Scientific Computing and Data Management #Software Engineering (cs.SE) #cs.MS #cs.SE #stat.CO
paper · pdf · doi:10.48550/arxiv.1406.4806
openalex publication_date 2014/06/03 · arxiv created 2014/06/04 · arxiv published 2014/06/04 · arxiv updated 2014/06/04 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28
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.