Why Open Drug Discovery Needs Four Simple Rules For Licensing Data And Models
Antony J. Williams, John Wilbanks, and Sean Ekins | PLoS Computational Biology | September 27, 2012
Abstract
When we look at the rapid growth of scientific databases on the Internet in the past decade, we tend to take the accessibility and provenance of the data for granted. As we see a future of increased database integration, the licensing of the data may be a hurdle that hampers progress and usability. We have formulated four rules for licensing data for open drug discovery, which we propose as a starting point for consideration by databases and for their ultimate adoption. This work could also be extended to the computational models derived from such data. We suggest that scientists in the future will need to consider data licensing before they embark upon re-using such content in databases they construct themselves.
- Tags:
- Academic Publishing
- accessibility
- ACToR
- ChEMBL
- ChemIDPlus
- ChemSpider
- closed data
- cloud
- Creative Commons (CC)
- data licensing
- data quality
- drug discovery
- guidelines
- healthcare
- intellectual property
- interoperability
- licenses
- medicine
- metadata
- Open Access
- Open Data
- open drug discovery
- Open Knowledge Definition (OKD)
- openness
- Panton Principles
- Peter Murray-Rust
- privacy
- PubChem
- Public Domain
- quantitative structure activity relationship (QSAR)
- research
- Scientific databases
- scientists
- Login to post comments