Authors:
Ignacio Santos
1
and
Elena Castro
2
Affiliations:
1
Carlos III Univesity of Madrid, Spain
;
2
Carlos III University of Madrid, Spain
Keyword(s):
XBRL (eXtensible Business Reporting Language), XML (eXtensible Markup Language) Taxonomy, XDT (XBRL Dimensional Taxonomy), Conceptual data model, MDM (Multidimensional data Model).
Related
Ontology
Subjects/Areas/Topics:
B2B, B2C and C2C
;
Communication and Software Technologies and Architectures
;
Databases and Datawarehouses
;
e-Business
;
Enterprise Information Systems
;
Internet Technology
;
Metadata and Metamodeling
;
Protocols and Standards
;
Social and Legal Issues
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
System Integration
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
;
XML and Data Management
Abstract:
Over the past ten years, there has been a significant increasing of the development of XML and Data Warehouse (DW) applications, and, in turn, more and more applications need to interact, and with different technologies. In parallel, the economic data in the last ten years have also evolved, increasingly companies and financial institutions need more information, in addition, this information must be reliable and on time. Nowadays, it is taking a significant rise for XBRL standard, based on XML. This language is mainly used in accounting reports and this consists of a set of taxonomies, which define different accounting regulations of a specific report. XBRL is becoming a global de facto standard. XBRL reports are created from various sources and are validated at source, so that, this is syntactically correct. XBRL represents business information, and it is multidimensional, and therefore the logical destination is a DW. This paper aims to analyze the data model of XBRL and its sema
ntics, and how to map this data model to the Multidimensional Data Model (Conceptual Model) and in turn to the Logical Model, either ROLAP (Relational OLAP), MOLAP (Multidimensional OLAP), or HOLAP (Hybrid OLAP), so they can be analyzed by business users.
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