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Principles for data analysis workflows
- Source :
- PLoS Computational Biology, Vol 17, Iss 3, p e1008770 (2021), PLoS Computational Biology
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- A systematic and reproducible “workflow”—the process that moves a scientific investigation from raw data to coherent research question to insightful contribution—should be a fundamental part of academic data-intensive research practice. In this paper, we elaborate basic principles of a reproducible data analysis workflow by defining 3 phases: the Explore, Refine, and Produce Phases. Each phase is roughly centered around the audience to whom research decisions, methodologies, and results are being immediately communicated. Importantly, each phase can also give rise to a number of research products beyond traditional academic publications. Where relevant, we draw analogies between design principles and established practice in software development. The guidance provided here is not intended to be a strict rulebook; rather, the suggestions for practices and tools to advance reproducible, sound data-intensive analysis may furnish support for both students new to research and current researchers who are new to data-intensive work.
- Subjects :
- FOS: Computer and information sciences
Data Analysis
0301 basic medicine
Science and Technology Workforce
Economics
Computer science
Social Sciences
Design elements and principles
Careers in Research
Workflow
Computer Science - Computers and Society
0302 clinical medicine
Biology (General)
Data Management
Careers
Ecology
Software Development
Software Engineering
Research Assessment
Reproducibility
Professions
Computational Theory and Mathematics
Modeling and Simulation
Engineering and Technology
Raw data
Employment
Computer and Information Sciences
Science Policy
Process (engineering)
QH301-705.5
Research and Analysis Methods
Phase (combat)
Education
Computer Software
03 medical and health sciences
Cellular and Molecular Neuroscience
Computers and Society (cs.CY)
Genetics
Humans
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Software Tools
business.industry
Data Science
Software development
Computational Biology
Data science
030104 developmental biology
Labor Economics
People and Places
Scientists
Population Groupings
business
Software
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 15537358
- Volume :
- 17
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- PLoS Computational Biology
- Accession number :
- edsair.doi.dedup.....cbc3882d54aca1d584144702831cb7a4