Open access semantic aware business intelligence

4Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The vision of an interconnected and open Web of data is, still, a chimera far from being accomplished. Fortunately, though, one can find several evidences in this direction and despite the technical challenges behind such approach recent advances have shown its feasibility. Semantic-aware formalisms (such as RDF and ontology languages) have been successfully put in practice in approaches such as Linked Data, whereas movements like Open Data have stressed the need of a new open access paradigm to guarantee free access to Web data. In front of such promising scenario, traditional business intelligence (BI) techniques and methods have been shown not to be appropriate. BI was born to support decision making within the organizations and the data warehouse, the most popular IT construct to support BI, has been typically nurtured with data either owned or accessible within the organization. With the new linked open data paradigm BI systems must meet new requirements such as providing on-demand analysis tasks over any relevant (either internal or external) data source in right-time. In this paper we discuss the technical challenges behind such requirements, which we refer to as exploratory BI, and envision a new kind of BI system to support this scenario. © Springer International Publishing Switzerland 2014.

Cite

CITATION STYLE

APA

Romero, O., & Abelló, A. (2014). Open access semantic aware business intelligence. In Lecture Notes in Business Information Processing (Vol. 172 LNBIP, pp. 121–149). Springer Verlag. https://doi.org/10.1007/978-3-319-05461-2_4

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free