Abstract
Current digital financial information is generated by data located in a distributed but linked environment. In this sense, semantic technologies and linked data allow files and data alike to be first-class web resources and promote information distribution and knowledge sharing within a global, open-standard space known as the Data Web. This chapter proposes FINALGRANT as an alternative solution to analyzing and visualizing digital financial data. The tool retrieves XBRL-based financial data and transforms them into RDF triples through a process inspired in the linked data principles. FINALGRANT identifies and addresses some limitations of financial statements, such as the lack of a semantic property to interlink the data and make it navigable and the challenge of accessing information through Internet protocols, such as HTTP, to navigate among data and interconnect them with external data sources. Similarly, FINALGRANT can search for financial ratios and processes fundamental or classical analysis calculations to support fund investment decisions.
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Notes
- 1.
Sarbanes-Oxley: http://www.sec.gov/about/laws.shtml#sox2002.
- 2.
U.S. SEC: http://www.sec.gov/.
- 3.
XBRL: http://www.xbrl.org/.
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Acknowledgements
The authors are grateful to the National Technological Institute of Mexico for supporting this work. This research was also sponsored by the National Council of Science and Technology (CONACYT) and the Secretariat of Public Education (SEP) through PRODEP.
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Sánchez-Cervantes, J.L., Alor-Hernández, G., Salas-Zárate, M.d.P., García-Alcaraz, J.L., Rodríguez-Mazahua, L. (2018). FINALGRANT: A Financial Linked Data Graph Analysis and Recommendation Tool. In: Valencia-García, R., Paredes-Valverde, M., Salas-Zárate, M., Alor-Hernández, G. (eds) Exploring Intelligent Decision Support Systems. Studies in Computational Intelligence, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-74002-7_1
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