@article{Acosta Bragança_Caetano da Silva_Bernardino Piraja Gomes_2022, title={Data Mapping for XBRL: A Systematic Literature Review}, volume={90}, url={https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/7956}, abstractNote={<p>It is evident the growth of the use of eXtensible Business Reporting Language (XBRL) technology in the context of financial reports on the Internet, either for its advantages and benefits or by government impositions, however, the data to be transported by this language are mostly stored in structures defined as database, some relational other NoSQL. The need to integrate XBRL technology with other data storage technologies has been growing continuously, and research is needed to seek a solution for mapping data between these environments. The possible difficulties in integrating XBRL with other technologies, relational database or NoSQL, CSV files, JSON, need to be mapped and overcome. Generating XBRL documents from the database can be costly, since there is no native alternative that the database manager system exports from the database manager system, the data in XBRL. For this, specific third-party systems are needed to generate XBRL documents. Generally, these systems are proprietary and have a high cost. Integrate these different technologies adds complexity, since these documents do not connect to the database manager system. These difficulties cause performance and storage problems and in cases of large data, such as data delivery to government agencies, complexity increases. Thus, it is essential to study techniques and methods that allow us to infer a solution to perform this integration and/or mapping, preferably in a generic way, that includes the XBRL data structure and the main data models currently used, i.e.  Relational DBMS, NoSQL, JSON or CSV files. It is expected, in this work, through a systematic literature review, to identify the state of the art concerning the mapping of XBRL data.</p>}, number={1}, journal={American Scientific Research Journal for Engineering, Technology, and Sciences}, author={Acosta Bragança, Henderson and Caetano da Silva, Paulo and Bernardino Piraja Gomes , Nacles}, year={2022}, month={Oct.}, pages={124–143} }