Semantic Integration Approach to Efficient Business Data Supply Chain: Integration Approach to Interoperable XBRL

As an open standard for electronic communication of business and financial data, XBRL has the potential of improving the efficiency of the business data supply chain. A number of jurisdictions have developed different XBRL taxonomies as their data standards. Semantic heterogeneity exists in these taxonomies, the corresponding instances, and the internal systems that store the original data. Consequently, there are still substantial difficulties in creating and using XBRL instances that involve multiple taxonomies. To fully realize the potential benefits of XBRL, we have to develop technologies to reconcile semantic heterogeneity and enable interoperability of various parts of the supply chain. In this paper, we analyze the XBRL standard and use examples of different taxonomies to illustrate the interoperability challenge. We also propose a technical solution that incorporates schema matching and context mediation techniques to improve the efficiency of the production and consumption of XBRL data

An Ontological Approach to XBRL Financial Statement Reporting

As a standard for the exchange, transmission, and reporting of accounting and financial data, XRBL goes a long way towardstandardization. However, as the extent of contemporary financial markets is now global, XBRL reporting must transcend oraccommodate differences in reporting standards. While XBRL has been of great help in standardizing the presentation of theU.S. GAAP and IASB standards, reconciling meaning between these standards is still a manual and error-prone affair. As awide variety of stakeholders, spanning countries and cultures, will likely take part in digesting XBRL-formatted financialreports; how will they participate at an appropriate level that is meaningful for them? This paper focuses on an ontologicalapproach towards solving this problem by offering an XBRL ontology architecture for translation between XBRL formats.The architecture is explained, evaluation criteria offered, and future research towards realizing artifacts which use thisarchitecture are proffered

Multimedia Annotation Interoperability Framework

Multimedia systems typically contain digital documents of mixed media types, which are indexed on the basis of strongly divergent metadata standards. This severely hamplers the inter-operation of such systems. Therefore, machine understanding of metadata comming from different applications is a basic requirement for the inter-operation of distributed Multimedia systems. In this document, we present how interoperability among metadata, vocabularies/ontologies and services is enhanced using Semantic Web technologies. In addition, it provides guidelines for semantic interoperability, illustrated by use cases. Finally, it presents an overview of the most commonly used metadata standards and tools, and provides the general research direction for semantic interoperability using Semantic Web technologies

Using SPIN to formalise Accounting Regulations on the Semantic Web

Spohr D, Cimiano P, McCrae J, O'Riain S. Using SPIN to formalise Accounting Regulations on the Semantic Web. Presented at the First International Workshop on Finance and Economics on the Semantic Web in conjunction with the 9th Extended Semantic Web Conference.The eXtensible Business Reporting Language (XBRL) has standardised nancial reporting and provide a machine-interpretable for- mat that makes nancial and business reports easier to access and con- sume. Leveraging XBRL with Open Linked Data for purposes such as multi-dimensional regulatory querying and investigation requires XBRL formalisation as RDF. This paper investigates the use of o-the-shelf Se- mantic Web technologies to formalise accounting regulations specied in XBRL jurisdictional taxonomies. Specically the use of the SPARQL In- ferencing Notation (SPIN) with RDF to represent these accounting reg- ulations as rule constraints, not catered for in the RDF abstract model is investigated. We move beyond previous RDF to XBRL transformations and investigate how SPIN enhanced formalisation enables inferencing of nancial statement facts associated with nancial reporting concepts and sophisticated consistency checks, which evaluate the correctness of reported nancial data with respect to the calculation requirements im- posed by accounting regulation. The approach illustrated through two use cases demonstrates the use of SPIN to meet central requirements for nancial data and regulatory modelling

A semantic Bayesian network for automated share evaluation on the JSE

Advances in information technology have presented the potential to automate investment decision making processes. This will alleviate the need for manual analysis and reduce the subjective nature of investment decision making. However, there are different investment approaches and perspectives for investing which makes acquiring and representing expert knowledge for share evaluation challenging. Current decision models often do not reflect the real investment decision making process used by the broader investment community or may not be well-grounded in established investment theory. This research investigates the efficacy of using ontologies and Bayesian networks for automating share evaluation on the JSE. The knowledge acquired from an analysis of the investment domain and the decision-making process for a value investing approach was represented in an ontology. A Bayesian network was constructed based on the concepts outlined in the ontology for automatic share evaluation. The Bayesian network allows decision makers to predict future share performance and provides an investment recommendation for a specific share. The decision model was designed, refined and evaluated through an analysis of the literature on value investing theory and consultation with expert investment professionals. The performance of the decision model was validated through back testing and measured using return and risk-adjusted return measures. The model was found to provide superior returns and risk-adjusted returns for the evaluation period from 2012 to 2018 when compared to selected benchmark indices of the JSE. The result is a concrete share evaluation model grounded in investing theory and validated by investment experts that may be employed, with small modifications, in the field of value investing to identify shares with a higher probability of positive risk-adjusted returns

Understanding RegTech for digital regulatory compliance

This chapter explores the promise and potential of Regulatory Technologies (RegTech), a new and vital dimension to FinTechFinTech. It draws on the findings and outcomes of a five-year research programme to highlight the role that RegTech can play in making regulatory complianceCompliance more efficient and effective. The chapter presents research on the Bank of England/Financial Conduct Authority (FCA) RegTech Sprint initiative, whose objective was to demonstrate how straight-through processing of regulations and regulatory complianceCompliance reporting using semantically enabled applications can be made possible by RegTech. The chapter notes that the full benefits of RegTech will only materialise if the pitfalls of a fragmented Tower of Babel approach are avoided. Semantic standards, we argue, are the key to all this

An Ontology for Sustainability Reporting Based on Global Reporting Initiative (GRI) G4

The aim of this research is to fill the gap by developing ontology for Sustainability Reporting based on GRI G4 Guidelines. The chief research question is: What is the best approach to developing an Ontological Model for the knowledge domain Sustainability Reporting? The main objective of this research is to develop such ontology for Sustainability Reporting based on GRI G4.The developed ontology for Sustainability Reporting was validated by applying it to existing business data

A flexible model for the semi-automatic location of services

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, julio de 200

Linked Data para la generación de conocimiento financiero a partir de la extracción de información semiestructurada

En la actualidad, la información es generada por datos ubicados en un entorno distribuido pero vinculado. Con relación a esta premisa, las tecnologías semánticas y Linked Data, proporcionan un paradigma en el que no sólo los documentos, sino que también los datos son recursos de primera clase en la Web, permitiendo su extensión y la compartición de conocimientos hacia un espacio global de datos basado en estándares abiertos, mejor conocido como Web de datos. En este trabajo de tesis, se presenta un modelo semántico inspirado en los principios de Linked Data que ofrece una alternativa de solución a los problemas de integración de datos que se manifiestan en los Estados financieros publicados por las empresas bajo el estándar XBRL a través de la Web. En este sentido, mediante el modelo semántico se identifican y subsanan ciertas limitaciones existentes en las Hojas de Balance, Cuentas de resultados y Estados de flujos de efectivo. Entre estas limitaciones destacan la falta de una semántica que permita la integración de sus datos para hacerlos navegables, la dificultad para el acceso a los mismos a través de protocolos asociados a Internet como el HTTP para la navegación e interconexión con otras fuentes de información, y la carente capacidad para la búsqueda de ratios financieros, así como el procesamiento de cálculos permitan un análisis fundamental o clásico que sirva de apoyo a la toma de decisiones. El modelo semántico, se integra de taxonomías financieras basadas en la norma US-GAAP, y es el soporte fundamental de una base de conocimientos financieros reutilizable inspirada en Linked Data. En relación con lo anterior, la investigación que se realiza en este trabajo de tesis se sintetiza a través de la solución que se proporciona a las hipótesis que en ella se plantean, y mediante la que se busca demostrar que el modelo semántico tiene la capacidad para poblar una base de conocimientos financieros a partir de la integración de fuentes de datos externas, facilitar la reutilización de sus datos con terceros a través de Linked Data, ayudar a mejorar la calidad estructural de los datos financieros y comprobar que este modelo también facilita el análisis fundamental financiero para apoyar la toma de decisiones tanto automatizada como por parte de las personas.At present, the information is generated by data located in a distributed environment but linked. In relation to this premise, semantic and Linked Data technologies provide a paradigm in which not only documents but also the data are first-class resources on the Web, allowing its extension and sharing of knowledge towards a global space data based on open standards, better known as Web of data. In this thesis, a semantic model based on the principles of Linked Data that provides an alternative solution to the problems presented data integration that are manifested in the financial statements published by the company under the XBRL standard through Web. In this sense, using the semantic model are identified and remedied certain limitations in Balance Sheets, Income Statements and Cash Flow Statements. These limitations include the lack of a semantics that allow the integration of their data to make it navigable, difficulty accessing them through associated Internet protocols like HTTP for navigation and interconnection with other sources of information and lacking ability for search of financial ratios, as well as processing calculations that allow a fundamental or classical financial analysis that supports the decision making. The semantic model integrated financial taxonomies based on US-GAAP standard, and is the main support base of reusable financial knowledge inspired Linked Data. In connection with this, the research conducted in this thesis is synthesized through the solution provided to the hypothesis raised therein, and by which seeks to demonstrate that the semantic model has the ability to financial populate a knowledge base from the integration of external data sources, facilitating the reuse of data with third parties via Linked data, help improve the structural quality of financial data and verify that this model also facilitates analysis financial crucial to support decision-making both automated and by the people.Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: Juan Bautista Llorens Morillo.- Secretario: Carlos Ángel Iglesias Fernández.- Vocal: Manuel Fernández-Utrilla Migue