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Big data raises challenges on veracity, on all aspects of the workflow, on extracting meaningful information, and on sharing information.
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Data security raises challenging issues including scalable data security administration, management and integration of heterogeneous data security policies, and the security of data when hosted on clouds and managed on sensor networks.
In the last years, the introduction of ChIP-Seq data raises new challenges for motif discovery problem from the perspective of data scale.
One of the key research strengths of the Case Register – the capacity to interrogate free text as well as structured data – raises particular challenges for anonymisation, given the complexity and extent of free text in the clinical database (PJS).
This raises challenges around reducing latency as data moves from server to server.
However, it raises challenges for both patients and providers.
The ubiquitous collection of personal data raises unprecedented privacy challenges.
The tremendous size of real-world graph data raises series of challenges in efficient graph management and query processing.
However, the fact that they still largely ignore the majority of the sequence data raises the obvious challenge of better exploitation of this extra information.
The complex structures and the lack of vector representations for the brain network data raise major challenges for data mining.
The wide usage of location aware devices, such as GPS-enabled cellphones or PDAs, generates vast volumes of spatiotemporal streams of location data raising management challenges, such as efficient storage and querying.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com