Open linked data
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Open linked data is an idea of a new way of organising data. Each piece of data has a URI which is used as an identifier. Pieces of data can be linked semantically together.
There is a need for a open data policy. What should it be like?
- It must improve international competitiveness of the countries that apply it.
- It must be global.
- It must reward for sharing information.
- It must be tempting to participate, not something that replaces something important you already have but should give up.
- It must be easy to understand.
- It must be based on open assessment.
- It must save public money.
Today, a typical experiment can simultaneously measure hundreds to thousands of individual features (e.g. genes) in dozens of biological conditions, resulting in gigabytes of data that need to be processed, analyzed and potentially reproduced.
Multiple ongoing open-source, community-based projects have emerged that enable researchers to share study protocols, experiment constructs, resulting data sets, as well as complete and fully reproducible data analysis pipelines.
Experimental and computational groups need to work together when developing novel assays, standards and analysis tools ensuring that all steps leading to the results of a study are optimized and reproducible.
The availability of open-acess, high-quality and reproducible data, will also lead to more powerful analyses (or meta-analyses) where multiple data sets are combined to generate new knowledge.
Funding agencies, publishers and researchers need to set strict C&R policies that would allow rapid revealation and correction of scientific errors instead of giving birth to new scientific projects and clinical trials based on erroneous results.
Conclusions come from Huang and Gottardo 
- Open science
- The Ball (an information ecosystem)
- Yhdistetty avoin tieto Suomessa (seminaari 26.3.2010)
- HILA Open Oy
- Julkinen data -opas: julkistamistilaisuus
- Antti Poikola: Julkishallinnon avoin data
- LabArchives and BioMed Central: a new platform for publishing scientific data
- Yunda Huang and Raphael Gottardo. Comparability and reproducibility of biomedical data. Brief Bioinform (2012) doi:10.1093/bib/bbs078 First published online: November 27, 2012