Integrating XBRL data with textual information in Chinese: A semantic web approach

• Use text analytics and semantic web techniques to combine soft and hard data.
• Our text analytics method allows a knowledge structure for automated data retrieval.
• The combined information is relevant for decision-making and meets specific needs.
• Our system is an extendable prototype to link soft information with financial data.
• Suggest a method to associate XBRL instances with textual disclosures in MD&A.

Due to formatting differences, the difficulties of processing the textual disclosures and integrating them with quantitative financial data are well documented in the literature. Using a design science methodology, this paper describes a method that automatically extracts relevant textual data from annual reports published in Chinese. These extracted words are then mapped to a knowledge framework we proposed. This paper shows that it is technologically feasible to reorganize the MD&A contents into any given knowledge structure to improve the search capability, readability, and cohesiveness of the MD&A contents. Finally, we demonstrate a prototype system that uses semantic web technology to achieve information integration that presents XBRL formatted accounting data with relevant textual disclosures together to assist user decision making.