A concept of Generic Workspace for Big Data Processing in Humanities

Abstract

Big Data challenges often require application of new data processing paradigms (like MapReduce), and corresponding software solutions (e. g. Hadoop). This trend causes a pressure on both cyber-infrastructure providers (to quickly integrate new services) and infrastructure users (to quickly learn to use new tools). In this paper we present the concept of DARIAH Generic Workspace for Big Data Processing in eHumanities which alleviates the aforementioned problems. It establishes a common integration layer, thus enables a quick integration of new services, and by providing unified interfaces, allows the users to start using new tools without learning their internal details. We describe the overall architecture and implementation details of the working prototype. The presented concept is generic enough to be applied in other emerging cyber-infrastructures for humanities.

A general perspective of Big Data: applications, tools, challenges and trends

“…Literature on Big Data had a growth of more than 150 % from 2012 to 2014. Research papers addressed the challenges of capturing [75], storing [76,77], searching [78], sharing [23], analyzing [9,79] and visualizing [80,81] Big Data sets in several fields such as Computer Science [82,83]; Mathematics [63]; Business, Management and Accounting [41]; Engineering [84]; Physics and Astronomy [85,86]; Biochemistry, Molecular Biology and Genetics [87]; Medicine [88]; Social Sciences [89,90]; Materials Science [24]; Decision Sciences [91], and Arts and Humanities [92]. It is important to consider the distribution of papers by publisher to determine the paper focus: the challenge addressed by the works and the domain considered.…”