A conceptual review of XBRL in relation to Big Data

Adam Krisko

Publikation: KonferencebidragPaperForskningpeer review


The technological developments of the last couple of decades have led to remarkable changes in the role of data within society. Data continues to grow, and the advances in the field of information technology (IT) further accelerate the process. This unfolding phenomenon has resulted in the emergence of high-volume, high-velocity and high-variety data sets, commonly referred to as ‘Big Data’. The existence of Big Data constantly challenges those working with data, and demands cost-effective and innovative techniques of subtracting useful information from it. Recent literature reveals the increasingly important role of Big Data within the accounting domain, by discussing the potential benefits and challenges the expansion in the volume, velocity, and variety of accounting data carries. One of the possible responses to the potential changes Big Data might foster within accounting is the utilisation of eXtensible Business Reporting Language (XBRL). XBRL is an open standard, free of license fees electronic language for communicating financial and business information. Storing data in XBRL format enables it to be machine-readable, and standardises the financial terms through XBRL taxonomy. Mainly due to these attributes XBRL has been developing into the global data standard for business financial reporting over the last few years. The purpose of this conceptual paper is to analyse the literature available on the topic in order to identify and discuss the opportunities and issues XBRL carries in relation to Big Data. In particular, I seek to answer the following question: how can the relationship between XBRL and Big Data be defined and conceptualised according to existing literature? The results of the literature review are derived through a concept-centric analysis, thus the outcome of the analysis is a conceptual typology that organises and summarises the body of knowledge on XBRL in relation to Big Data, and reveals the critical knowledge gaps along with an agenda for future research.
Publikationsdatoapr. 2016
StatusUdgivet - apr. 2016
Begivenhed2nd Academic International Conference on Business, Marketing and Management - Harvard University, Boston, USA
Varighed: 5 apr. 20167 apr. 2016
Konferencens nummer: AICBMM 201628171331


Konference2nd Academic International Conference on Business, Marketing and Management
NummerAICBMM 201628171331
LokationHarvard University

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