GloPID-R Roadmap for Data Sharing in PHEs | Page 26

QUALITY: CHALLENGES
& POTENTIAL SOLUTIONS
QUALITY
DATA SHARING
PRINCIPLE
T
he minimum quality standard of data must be ensured by the provider
while data users must also ensure that data processing, analysis and
interpretation are conducted with an equal or greater application of quality
standards. Appropriate and recognised data standards should be adhered to,
while all relevant meta-data, assumptions and experimental details should
be provided with the data. This will ensure that any work conducted from
the data takes into account the context in which the data was originally
produced. The treatment and transfer of data must also be conducted with
appropriate security measures.
COMPLEXITY
Issues with data completeness, quality and
accessibility are all highlighted through the
case studies. Compatibility between different
datasets has also provided a barrier to effective
data sharing.
There is a clear highlighted need for capacity
strengthening in data management (including
all aspects from collection to analysis) in en-
demic countries to improve data quality. The
use of standardised data collection protocols
along with data handling and data collection
manuals would improve standardisation. The
use of existing pathogen specific platforms or
development of a comprehensive global plat-
form for data sharing could provide standardi-
sation and facilitate coordination, which would
help address complexity.
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