# archivist: An R Package for Managing, Recording and Restoring Data Analysis Results

## TL;DR

The paper introduces the archivist R package, which enhances data analysis management by archiving, sharing, and restoring R objects along with their metadata, relations, and context to improve reproducibility and collaboration.

## Contribution

It presents new functionalities for managing R objects and their metadata, extending reproducible research with object retrieval, validation, and pedigree tracking capabilities.

## Key findings

- Enables archiving and sharing R objects with metadata and relations.
- Supports retrieval and validation of objects for reproducibility.
- Allows interactive exploration and pedigree tracking of R objects.

## Abstract

Everything that exists in R is an object [Chambers2016]. This article examines what would be possible if we kept copies of all R objects that have ever been created. Not only objects but also their properties, meta-data, relations with other objects and information about context in which they were created. We introduce archivist, an R package designed to improve the management of results of data analysis. Key functionalities of this package include: (i) management of local and remote repositories which contain R objects and their meta-data (objects' properties and relations between them); (ii) archiving R objects to repositories; (iii) sharing and retrieving objects (and it's pedigree) by their unique hooks; (iv) searching for objects with specific properties or relations to other objects; (v) verification of object's identity and context of it's creation. The presented archivist package extends, in a combination with packages such as knitr and Sweave, the reproducible research paradigm by creating new ways to retrieve and validate previously calculated objects. These new features give a variety of opportunities such as: sharing R objects within reports or articles; adding hooks to R objects in table or figure captions; interactive exploration of object repositories; caching function calls with their results; retrieving object's pedigree (information about how the object was created); automated tracking of the performance of considered models, restoring R libraries to the state in which object was archived.