Title |
Structuring research methods and data with the research object model: genomics workflows as a case study
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Published in |
Journal of Biomedical Semantics, September 2014
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DOI | 10.1186/2041-1480-5-41 |
Pubmed ID | |
Authors |
Kristina M Hettne, Harish Dharuri, Jun Zhao, Katherine Wolstencroft, Khalid Belhajjame, Stian Soiland-Reyes, Eleni Mina, Mark Thompson, Don Cruickshank, Lourdes Verdes-Montenegro, Julian Garrido, David de Roure, Oscar Corcho, Graham Klyne, Reinout van Schouwen, Peter A C ‘t Hoen, Sean Bechhofer, Carole Goble, Marco Roos |
Abstract |
One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 2 | 18% |
Sweden | 1 | 9% |
Norway | 1 | 9% |
Philippines | 1 | 9% |
Unknown | 6 | 55% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 8 | 73% |
Scientists | 2 | 18% |
Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 3% |
Brazil | 2 | 2% |
United States | 2 | 2% |
Spain | 2 | 2% |
Canada | 1 | 1% |
France | 1 | 1% |
Netherlands | 1 | 1% |
Russia | 1 | 1% |
Unknown | 74 | 85% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 23 | 26% |
Student > Ph. D. Student | 11 | 13% |
Student > Master | 9 | 10% |
Student > Bachelor | 8 | 9% |
Professor | 7 | 8% |
Other | 16 | 18% |
Unknown | 13 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 36 | 41% |
Biochemistry, Genetics and Molecular Biology | 10 | 11% |
Agricultural and Biological Sciences | 7 | 8% |
Business, Management and Accounting | 3 | 3% |
Medicine and Dentistry | 3 | 3% |
Other | 12 | 14% |
Unknown | 16 | 18% |