One important aspect of research data management is data sharing and reuse. This post introduces a few common data licenses that enable data creators to explain what users may or may not do with a given work.
This week we share a simple but important practice about organizing data files and documents for submitting papers to journals.
Springer Nature and Digital Science jointly released The State of Open Data 2021 Report. What's in it?
We are pleased to announce the launch of DMPTool@HKUST, a data management plan (DMP) writing platform at HKUST.
In the recent RDM Symposium for HKUST researchers, we had a lively seminar on data integrity and publishing with two talks. Last week we summarized the first talk; this post reports the second part.
Data is the pillar of integrity in published research. How do journal editors detect integrity issues? How can publishers support integrity? A recent seminar for HKUST researchers brought up a good discussion.
Datasets cannot speak for themselves. It is the way that you describe your research data and the methodology that matters.
Environment data poses specific challenges to researchers in data management. Networked sensors collect voluminous data that require systematic planning in workflow, storage and dissemination. Prof. NING Zhi (ENVR) illustrated good data practices with environment big data.
Increasingly, researchers are expected to actively manage their research data throughout the life-cycle of scholarly interest. Learning research data management best practices has become essential, especially for early career researchers.
