Resources
Open Science
The list of the top 50 Journals/Proceedings in Robotics, indicating their publication OA model (Gold, Green or Hybrid) and the workflow of publication in the different models to access OA is available for download here.
Research data should be freely accessible to everyone – for scientists as well as for the general public.
The SNSF agrees with this principle. Since October 2017, researchers have to include a data management plan (DMP) in their funding application for most of the funding schemes. At the same time, the SNSF expects that data generated by funded projects are publicly accessible in digital databases provided there are no legal, ethical, copyright or other issues (1).
Open data is the idea that some data should be freely available to everyone to use and republish as they wish, without restrictions from copyright, patents or other mechanisms of control (2).
The SNSF values research data sharing as a fundamental contribution to the impact, transparency and reproducibility of scientific research. In addition to being carefully curated and stored, the SNSF believes research data should be shared as openly as possible.
The SNSF therefore expects all its funded researchers:
- to store the research data they have worked on and produced during the course of their research work,
- to share these data with other researchers, unless they are bound by legal, ethical, copyright, confidentiality or other clauses, and
- to deposit their data and metadata onto existing public repositories in formats that anyone can find, access and reuse without restriction.
Research data is collected, observed or generated factual material that is commonly accepted in the scientific community as necessary to document and validate research findings.
References:
(1) SNSF policy on Open Research Data
(2) Auer S., Bizer C., Kobilarov G., Lehmann J., Cyganiak R., Ives Z. (2007). DBpedia: A Nucleus for a Web of Open Data. In: Aberer K. et al. (eds), The Semantic Web. ISWC 2007, ASWC 2007. Lecture Notes in Computer Science, vol 4825. Springer, Berlin, Heidelberg. doi: 10.1007/978-3-540-76298-0_52
(3) Wilkinson, Mark D.; Dumontier, Michel; Aalbersberg, IJsbrand Jan; Appleton, Gabrielle; et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data. 3: 160018. doi: 10.1038/sdata.2016.18