Research data holds immense potential that extends well beyond the completion of a research project. By sharing your data with others, you're not only fostering collaboration but also offering a valuable resource for those interested in building upon your findings and expanding the horizons of knowledge. Moreover, many funding agencies now mandate the sharing and preservation of research data as part of the data management plan.
Here are some compelling reasons why sharing research data is beneficial:
Expands Scientific Inquiry: Shared data opens new avenues for scientific exploration and investigation, allowing researchers to delve deeper into existing research questions or explore entirely new ones.
Encourages Diversity of Analysis: By providing access to your data, you invite diverse perspectives and methodologies, enriching the analysis and interpretation of the data.
Sparks Innovation: Shared data can inspire novel ideas and innovative research directions, catalyzing advancements in various fields of study.
Facilitates Hypothesis Testing: Others can use your data to test alternative hypotheses or conduct further analyses, contributing to the robustness and reliability of research findings.
Supports Future Studies: Shared data serves as a foundation for future studies, enabling researchers to build upon existing datasets and explore new avenues of inquiry.
Fosters Exploration: Researchers can explore new research questions or topics that may not have been initially considered by the original data collector, leading to unforeseen discoveries and insights.
Educational Resource: Shared data serves as a valuable educational resource for aspiring researchers, providing real-world examples for learning data analysis techniques and research methodologies.
There are many options available for sharing and preserving your research data. Ensuring that data are usable and understandable by others requires some thought and planning. You may choose to use, services such as an institutional repository, external repositories, data centers, or journal publishers. Another option is to make your data sharable through a project website.
There are various ways to share research data, including:
Institutional Repository Services
The Library manages an institutional repository designed to collect, preserve, and disseminate digital versions of faculty publications and research data. This repository significantly enhances the visibility and accessibility of faculty work. By archiving your research in the institutional repository, you can increase its impact and reach a broader audience. The Library will collaborate with you to secure the necessary author rights for self-archiving your current and future publications.
Other Ways to Share Research Data
Data Repositories: Deposit data in disciplinary or institutional repositories specifically designed for storing and sharing research data. Examples include Dryad, Figshare, and Zenodo.
Subject-Specific Archives: Submit data to subject-specific archives or databases tailored to a particular field or research area. These archives often have specialized metadata standards and domain-specific search capabilities.
Journal Supplementary Materials: Include datasets as supplementary materials when publishing research articles in scholarly journals. Many journals encourage or require authors to provide access to underlying data to support transparency and reproducibility.
Data Journals: Publish datasets in data journals that specialize in publishing datasets and data articles. Data journals focus on the description, curation, and peer review of datasets, providing a platform for sharing data independently of research articles.
Collaborative Platforms: Collaborate with colleagues and research partners through collaborative platforms or project-specific websites to share data within research teams or collaborative projects. Platforms like GitHub, GitLab, and Google Drive facilitate version control and collaboration on data and code.
Data Supplements: Provide data supplements or data packages alongside research publications, including datasets, code, documentation, and other relevant materials necessary to reproduce the research findings.
Data Citations: Cite datasets in research publications and include Digital Object Identifiers (DOIs) or other persistent identifiers to facilitate attribution and enable others to easily locate and access the data.
Data Sharing Platforms: Utilize data sharing platforms and networks that facilitate data discovery, access, and collaboration across disciplines, such as DataONE, DataCite, and the Open Science Framework (OSF).