Authors:
Daniel Staegemann
;
Matthias Volk
;
Alexandra Grube
;
Johannes Hintsch
;
Sascha Bosse
;
Robert Häusler
;
Abdulrahman Nahhas
;
Matthias Pohl
and
Klaus Turowski
Affiliation:
Magdeburg Research and Competence Cluster Very Large Business Applications, Faculty of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany
Keyword(s):
Big Data, Taxonomy, Literature Review, Classification, Categorisation, Systematization, Data Characteristics, Structured, Analysis.
Abstract:
As big data is a rather young, but growing discipline, lots of confusion about the general nature of this term exists. Consequently, multiple research endeavours to discover unique characteristics, technologies, techniques and their interconnections were conducted, resulting in comprehensive classification approaches. For this purpose, various taxonomies on big data exist in literature. However, due to the multitude of approaches and partial contradictions, no real clarification is achieved. To overcome this issue, a systematic literature review was conducted, which identifies and analyses big data taxonomies. As a result, a classification of those taxonomies is proposed, which additionally tracks sub-domains that are not yet covered by the existing taxonomies so far. Eventually, the publication at hand serves as a starting point for further taxonomy related research endeavours in the big data domain.