↓ Skip to main content

A metadata schema for data objects in clinical research

Overview of attention for article published in Trials, November 2016
Altmetric Badge

Mentioned by

1 blog
15 X users
1 Google+ user
1 YouTube creator


14 Dimensions

Readers on

51 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
A metadata schema for data objects in clinical research
Published in
Trials, November 2016
DOI 10.1186/s13063-016-1686-5
Pubmed ID

Steve Canham, Christian Ohmann


A large number of stakeholders have accepted the need for greater transparency in clinical research and, in the context of various initiatives and systems, have developed a diverse and expanding number of repositories for storing the data and documents created by clinical studies (collectively known as data objects). To make the best use of such resources, we assert that it is also necessary for stakeholders to agree and deploy a simple, consistent metadata scheme. The relevant data objects and their likely storage are described, and the requirements for metadata to support data sharing in clinical research are identified. Issues concerning persistent identifiers, for both studies and data objects, are explored. A scheme is proposed that is based on the DataCite standard, with extensions to cover the needs of clinical researchers, specifically to provide (a) study identification data, including links to clinical trial registries; (b) data object characteristics and identifiers; and (c) data covering location, ownership and access to the data object. The components of the metadata scheme are described. The metadata schema is proposed as a natural extension of a widely agreed standard to fill a gap not tackled by other standards related to clinical research (e.g., Clinical Data Interchange Standards Consortium, Biomedical Research Integrated Domain Group). The proposal could be integrated with, but is not dependent on, other moves to better structure data in clinical research.

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 22%
Student > Ph. D. Student 5 10%
Other 5 10%
Student > Bachelor 4 8%
Librarian 4 8%
Other 9 18%
Unknown 13 25%
Readers by discipline Count As %
Computer Science 8 16%
Social Sciences 7 14%
Medicine and Dentistry 6 12%
Agricultural and Biological Sciences 4 8%
Nursing and Health Professions 2 4%
Other 9 18%
Unknown 15 29%