Introduction defining context and scope

(Scientific Data) Processing or Analytics is a quite vast domain including any activity or process that performs a series of actions on dataset(s) to distil information (add citation SIGMOD Record paper). It is particularly important in scientific domains especially with the advent of the 4^th Paradigm and the availability of “big data” (add a citation to 4th paradigm book). Almost any Research Infrastructure is called to deal with some sort of scientific data processing tasks. Data analytics methods are drawn on multiple disciplines including statistics, quantitative analysis, data mining, and machine learning. Very often these methods might require computing intensive infrastructures to produce their results in a suitable time, because of the data to be processed (e.g. huge in volume or heterogeneity) and/or because of the complexity of the algorithm/model to be elaborated/projected. Moreover, these methods being devised to analyse dataset(s) and produce other “data”/information (than can be considered a dataset) are strongly characterised by the “typologies” of such input and output.

This technology review focuses on the following aspects:

• ...
• Data processing enactment platforms;
• Scientific Workflow Management Systems;
• ...

Change history and amendment procedure

The review of this topic will be organised by  in consultation with the following volunteers: . They will partition the exploration and gathering of information and collaborate on the analysis and formulation of the initial report. Record details of the major steps in the change history table below.For further details of the complete procedure see item 4 on the Getting Started page.

Note: Do not record editorial / typographical changes. Only record significant changes of content.

Sources of information used

Two-to-five year analysis

State of the art

Trends

Subsequent headings for each trend (if appropriate in this HL3 style)

Problems to be overcome

Sub-headings as appropriate in HL3 style (one per problem)

Details underpinning above analysis

Sketch of a longer-term horizon

Relationships with requirements and use cases

Summary of analysis highlighting implications and issues

Bibliography and references to sources