Interactive Data Exploration of Distributed Raw Files: A Systematic Mapping Study

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URI: http://hdl.handle.net/10498/21347
DOI: 10.1109/ACCESS.2018.2882244
ISSN: 2169-3536
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2019Department
Ingeniería InformáticaSource
IEEE Access - 2019 - Volume: 7 p. 10691 - 10717Abstract
When exploring big amounts of data without a clear target, providing an interactive experience
becomes really dif cult, since this tentative inspection usually defeats any early decision on data structures
or indexing strategies. This is also true in the physics domain, speci cally in high-energy physics, where
the huge volume of data generated by the detectors are normally explored via C++ code using batch
processing, which introduces a considerable latency. An interactive tool, when integrated into the existing
data management systems, can add a great value to the usability of these platforms. Here, we intend to
review the current state-of-the-art of interactive data exploration, aiming at satisfying three requirements:
access to raw data les, stored in a distributed environment, and with a reasonably low latency. This paper
follows the guidelines for systematic mapping studies, which is well suited for gathering and classifying
available studies.We summarize the results after classifying the 242 papers that passed our inclusion criteria.
While there are many proposed solutions that tackle the problem in different manners, there is little evidence
available about their implementation in practice. Almost all of the solutions found by this paper cover a
subset of our requirements, with only one partially satisfying the three. The solutions for data exploration
abound. It is an active research area and, considering the continuous growth of data volume and variety,
is only to become harder. There is a niche for research on a solution that covers our requirements, and the
required building blocks are there.
Subjects
Big data applications; data analysis; data engineering; data exploration; database systems; interactive systems; systematic mapping studyCollections
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