Biology Reference
In-Depth Information
a culture of appropriate data sharing remains perhaps the
single greatest impediment to the rapid development of the
integrative techniques described above. Even in cases where
significant effort has gone into providing data in the most
comprehensive fashion (e.g., the TCGA projects), repro-
ducing results of others from such data often remains elusive
[63]
. As problematic are review processes that may delay
the release of a critical dataset by years.
To evolve toward a more generative scientific society,
technical and cultural changes are necessary. For biology to
achieve the same level of integration as electronics,
astronomy, and economics, new standards and annotations
will be required. Reward structures for career advancement
and peer recognition that are based on being a first or last
author, and the need to own intellectual property around
biologic insights, must also be re-examined. Emerging
efforts such as Sage Bionetworks (
http: //www.sagebase.
formation, providing ways of openly sharing large-scale
data, computing on those data, representing models derived
from the data for others to query and validate, and even
proposing governance structures and new types of informed
consents that break down many of the barriers that
currently exist to openly sharing patient data. Of course,
such efforts will need to well demonstrate the advantages of
sharing data, models, and tools to further our understanding
of disease beyond what any lab could have done individ-
ually, if they are to prove convincingly to researchers more
generally that their future competitiveness depends on
openly sharing data and results.
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