Recent works agree on the need to study the Map-Reduce model for identifying its limitations and pertinence for implementing data processing algorithms like relational operators (i.e., join).
Therefore, new data analytics stacks have emerged as environments that provide the necessary underlying infrastructure for giving access to data collections and implementing data processing workflows to transform them and execute data analytics operations (statistics, data mining, knowledge discovery, computational science processes) on top of them.
This paradigm shift with respect to the access and manipulation of information creates new challenges by requiring highly specialized skill, such as implementing data-processing pipelines, to be accessible to a much wider audience.
In the context of bioinformatics, there are several frameworks to help implement data-processing pipelines; although a full comparison is beyond the scope of this article, we mention a few that relate to our work: (i) Snakemake (Köster and Rahmann, 2012) written as a Python domain-specific language (DSL), which has a strong influence from 'make' command.
The SSIE strategy reduces the computational complexity to ensure real-time processing of hyperspectral images, while the DSP platform implements data processing automatically on the unmanned device.
The results of applying the REST constraints to information processing elements, like data analysis algorithms, leads to a change in the way of thinking, modelling, implementing, and perceiving data processing.
Network processors (NPs) are an emerging field of programmable processors that are optimized to implement data plane packet processing networking functions.
The smart actuators aim at replacing the traditional drives (spindles and feed-drives) and enable to add data processing abilities to implement monitoring and control tasks.
AEB designed and implemented the database, front end web interface, and implemented all data processing.
It is noted that network processors (NPs) are an emerging field of programmable processors that are optimized to implement data plane and packet processing networking functions.
We implemented a data processing system based on classical post-refinement techniques, adapted to specific properties of XFEL diffraction data.
