Year: 2018
Type: article
Abstract: Efficiently producing transparent analyses may be difficult for beginners or tedious for the experienced. This implies a need for computing systems and environments that can efficiently satisfy reproducibility and accountability standards. To this end, we have developed a system, R package, and R Shiny application called adapr (Accountable Data Analysis Process in R) that is built on the principle of accountable units. An accountable unit is a data file (statistic, table or graphic) that can be associated with a provenance, meaning how it was created, when it was created and who created it, and this is similar to the 'verifiable computational results' (VCR) concept proposed by Gavish and Donoho. Both accountable units and VCRs are version controlled, sharable, and can be incorporated into a collaborative project. However, accountable units use file hashes and do not involve watermarking or public repositories like VCRs. Reproducing collaborative work may be highly complex, requiring repeating computations on multiple systems from multiple authors; however, determining the provenance of each unit is simpler, requiring only a search using file hashes and version control systems.
Source: The R Journal
DOI: 10.32614/rj-2018-001
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
Awards: G1143455775, Mays Cancer Center at UT Health SA, G2361851875, Institute for Integration of Medicine & Science: A Partnership to Improve Health, G6655026610, Institute for Integration of Medicine & Science: A Partnership to Improve Health, G8345979365, Bayesian Approaches to Model Selection for Survival Data, G9000324485, San Antonio Nathan Shock Center of Excellence in the Biology of Aging, San Antonio Claude D. Pepper Older Americans Independence Center
OpenAlex ID: W2804498007
