# Encouraging reusability of computational research through Data-to-Knowledge Packages - A hydrological use case

## TL;DR

This paper introduces a new package format to make computational research easier to reuse, demonstrated through a hydrology example.

## Contribution

The D2K-Package is introduced to enhance reusability by bundling data, code, and tools for easier understanding and reuse.

## Key findings

- The D2K-Package includes data, code, virtual labs, and workflows to support reproducibility and reuse.
- A hydrological use case demonstrates the package's feasibility and integration into the research cycle.
- The package helps reduce the effort required to understand and reuse complex analyses.

## Abstract

The growing demand for reproducible research is based on the expectation that publishing research in this form will enable its reuse and the generation of new knowledge. However, reproducibility alone does not guarantee these benefits. Users still need to make considerable efforts to understand the data and analysis code before they can reuse these components in other contexts. To address this challenge, we introduce the Data-to-Knowledge Package (D2K-Package), a collection of research materials including source code and open FAIR data, virtual labs, web API services, and computational workflows. The D2K-Package’s core is the reproducible basis composed of the data and source code on which an analysis is based. This core is designed such that the other components can be derived from it. The main goal of the package is to help researchers generate new knowledge by facilitating the understanding and encouraging the reuse of reproducible research. We demonstrate the applicability of the D2K-Package with a hydrological use case which can be also used for testing, and discuss its seamless integration into the research cycle.

Researchers often collect data and analyse it using appropriate methods in order to answer a specific research question. The research results are then published in scientific articles. If other researchers have access to the data and the analysis used and can achieve the same results as in the article, this is called “reproducible research”. One of the main advantages of reproducible research is that other scientists can continue the work and reuse the materials. However, publishing the materials in a reproducible manner is a challenge for the developer of the analysis. In addition, reusing the material for others is a difficult task as the analysis can become very complex.

In this paper, we introduce the Data-to-Knowledge package (D2K-Package), which contains the data and analysis in a reproducible manner, as well as other components that help other researchers understand and reuse the analysis. One of these components is a workflow that visualizes the steps of the analysis pipeline as a first entry point. To demonstrate the feasibility of the D2K-Package, we applied the idea to a real use case in hydrology.