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Internet and the World Wide Web have made possible unimaginable levels of information sharing and collaboration in science, as well as in other human activities. In life science, software-based collaboration occurs at different scale levels, from small collocated scientific groups to large international communities. It also happens in various ways, from tight-interaction in ontology design to crowd-sourced data annotation and analysis. The idea of the web of data has been particularly successful in the biomedical field, given its potential to ease integration and exploration of large, complex, and heterogeneous data sets. Advanced knowledge representation and data exchange standards have been widely used for such purpose. These same approaches are applied in developing collaboration models and software to support such models.
In this special issue we want to explore the intersection between the above themes and gather an outlook of current efforts and solutions to promote collaboration in life sciences through software tools, open data standards, advanced representation of the semantics of data, and collaboration models. Potential topics include, but are not limited to:
- Ontology-driven collaboration software for life science
- Collaboratories in the biomedical field
- Crowdsourcing experiences and projects, semantics-based models, and applications for crowdsourcing in life science
- Collaborative biomedical data generation, exchange, and integration
- Distributed biomedical data annotation and analysis
- Ontologies and models to support collaboration in life science
- Practices and tools in bio-ontology development and applications
- Collaborative annotation and review of biomedical literature, nanopublications
- Collaboration in biomedical education and training, advanced semantic models for life science education applications
- Software tools to fund raise biomedical research projects
More details here. Send in your contribute!
