Investigating the Cross-Cutting effects of Open Research Data from National Repositories: the EASY case study

By Tim Willense & Vincent Traag, CWTS

Introduction

The EASY case study investigates the impact of data availability on its usage by researchers. It explores whether data shared through national repositories experiences higher uptake compared to other platforms like international or disciplinary repositories. Focused on the EASY repository managed by DANS in the Netherlands, the study analyzes datasets from the SSH, with a specific emphasis on Dutch research. By utilizing DataCite, it correlates data with related publications to assess citation rates, providing insights into the effectiveness of national repositories in promoting data dissemination and scholarly collaboration.

Why was this particular study selected to support testing and operationalization of Open Science indicators?

This study on the cross-cutting effects of open research data from a national repository, specifically focusing on the EASY database, was chosen to support testing and operationalization of Open Science indicators for several reasons. The case study's unique focus on data availability and its impact on data use aligns closely with some of the core objectives of Open Science. By investigating whether scientists exhibit different usage patterns based on the repository from which data is made available, the study provides a nuanced understanding on some of the dynamics involved. The EASY database, managed by DANS in the Netherlands, stands out as a case due to its commitment to the FAIR principles, making it an ideal candidate for assessing the effectiveness of open data repositories. This enables this case study to leverage insights for refining Open Science indicators related to data sharing practices.

Why do you think this is study is important for the broader Open Science context? 

In the broader Open Science context, this study holds importance for multiple reasons. Firstly, it addresses a critical gap in understanding the relationship between open data repositories, data reuse, and data referencing. The investigation into the effectiveness of open data repositories in making research data openly available contributes valuable insights. Additionally, by examining how data is referenced in research and its compliance with open data reuse and repositories, the study provides a foundation for developing more effective Open Science practices. Understanding these dynamics is crucial for fostering a transparent, collaborative, and accessible research environment, aligning with the overarching principles of Open Science.

How will this study contribute to the main aims of the project? 

The EASY case study significantly contributes to the main aims of the PathOS project by offering insight into the impact pathways of open science. Specifically, the study sheds light on the impact pathway of open data repositories on open data reuse. By examining factors such as accessibility, findability, data quality, and the role of various contextual elements, the case study highlights mechanisms within the broader open science system. This understanding is pivotal for refining and operationalizing Open Science indicators, providing a comprehensive view of how data repositories influence data uptake and reuse.

What kind of impact is expected to be generated by the results/outcomes of the study for different stakeholder groups? 

• Government: While not directly affected, governments that provide funding for building national data repositories, will have a keen interest in the results. Insights from the study can inform future decisions regarding funding allocation and the development of national-level data repositories.
• National data repository: The results would be of interest to the national data repository by offering valuable insights into its usage.
• Scientists: Scientists who contribute data to repositories will benefit from understanding the differences in data uptake across various repositories. The study's outcomes can guide scientists in making informed decisions about where to share their data for optimal visibility and impact within the research community.

The CWTS team