Publish a Data Note in All Life
Maximize the potential of your research data with Data Notes
Effective data sharing extends beyond simply depositing your dataset in a repository. Maximize the visibility and impact of your research data and gain extra credit for your work with Data Notes.
What is a Data Note?
Data notes concisely describe your research data to increase the visibility and transparency of your research, and are peer-reviewed to support the reuse of valuable research data. They include:
- Dataset rationale, protocol, and validation details
- Information about any limitations of the dataset
- Information on where and how to access the dataset, as part of a Data Availability Statement
- Reference to the dataset using a formal citation
- Where applicable, cite and summarize any previous publications that use the data presented
Data Notes do not include any analyses or conclusions, but promote the discoverability and potential reuse of research data by providing a detailed description of the dataset itself. This gives credit to data producers with a citable, peer-reviewed publication, and supports new research collaborations across disciplines.
All Life is a multidisciplinary open access journal accepting submissions of data notes for peer review across a broad scope of subjects in the life sciences. Visit the Aims & Scope page to explore the subject-led sections.
2020 Impact Factor 2.000
Five-Year Impact Factor 4.888
-Journal Citation Reports®
WEB OF SCIENCE® Indexed
235K Annual Article Downloads
Why publish a Data Note in All Life?
Publishing a data note in All Life allows you to:
- Maximize the potential of your research data by being transparent about how and why your research data was created and where it is stored.
- Gain appropriate credit for your research data with a citable, peer-reviewed publication.
- Share information about your scientific datasets in a highly discoverable, useable and reproducible way .
- Foster new collaborations across disciplines by helping others to find, use and reproduce your datasets.
- Support FAIR data principles and comply with funder mandates for open data if this is required by your funder, institution, or employer.
Before you submit your research, please read and adhere to our our Instructions for Authors.