This move can be seen in the implementation of platforms where dynamic consent is used to solve the traditional problem of consent (Kaye et al. 2011), as well as in cases where patient organisations take the lead in implementing data sharing initiatives, such as PEER (Novas 2007).
Although funders consider that data sharing increases the benefits that have been made to the public in research [ 39] and researchers can see the benefit of sharing some kinds of data [ 40], there are also disadvantages to implementing data sharing policies.
The number of available neuroscience resources (databases, tools, materials, and networks) available via the Web continues to expand, particularly in light of newly implemented data sharing policies required by funding agencies and journals.
Biotechnology and Biological Sciences Research Council [ 6], the Wellcome Trust and the Sanger Institute have implemented data sharing policies.
For many researchers, the first step is examining the policies of similar projects or consulting with leaders in the field who have designed or implemented data sharing systems [ 28].
Many of these challenges are already being addressed through ELSI harmonization initiatives aiming to implement data sharing codes of conduct and policies [ 32] and are encouraged by empirical studies indicating that research participants generally support wide data sharing for research purposes given that privacy and confidentially concerns are appropriately handled and secured [ 33- 35].
To illustrate some of the challenges of implementing data-sharing principles, we focus on three key issues in the data pipeline - study recruitment, data release and data access.
The BioSharing forum works at the global level to build stable linkages between funders, implementing data-sharing policies and well-constituted standardization efforts in the biosciences domain to expedite communication and achieve harmonization and mutual support.
The ISB has made substantial commitments to such activities, in collaboration with the BioSharing initiative (14; www.biosharing.org), operating at a global level to build stable linkages between journals and funders, and implementing data-sharing policies and standardization efforts in the biosciences.
The findings identified five shared visualisation strategies that represent the ways implemented to process data sharing and knowledge to arrive at the desired level of understanding.
Nature Biotechnology, for example, has published over 20 papers on standards, often after soliciting an open review by the broader community; BioMed Central leads a 'Publishing Open Data Working Group' [ 7] to stimulate debate among authors, publishers, funders, and librarians to identify mutually agreeable ways for implementing data sharing/deposition policies.
