Richard T. Redmond

A semantic approach to monitor business process

Finding an effective method for managing and evaluating the performance of business processes is a key element for e-business success.

Ontology based integration of XBRL filings for financial decision making

In 2008, the US Securities and Exchange Commission (SEC) mandated all tier-1 public companies to report their financial statements in eXtensible Business Reporting Language (XBRL). XBRL has the potential to improve the efficiency and accuracy of financial disclosures, and thereby reduce costs. However, semantic heterogeneity across XBRL filings poses a challenge for individual (non-institutional) investors seeking to make inter-firm comparisons using XBRL data. In order to extend the benefits of XBRL to individual investors, this paper presents a design artifact, Ontology-based Framework for XBRL-mapping and Decision-making (OFXD), which provides interoperability between different XBRL filings. Specifically, OFXD resolves the semantic heterogeneity of the element and context definitions in various XBRL filings and generates an XBRL ontology - XBRLOnt. The results of this study show that the proposed design artifact is capable of addressing semantic heterogeneities between different XBRL filings. Using the concepts of the information value chain, this paper discusses the implications of XBRL interoperability on financial decision-making. We address the semantic heterogeneity issue and thereby improve the usability of XBRL data.We propose an Ontology-based Framework for XBRL-mapping and financial decision-making (OXFD).OXFD maps semantic heterogeneous XBRL elements and provides rules to calculate financial ratios.The results show the generalizability of our artifact for different XBRL filings.

Using Ontological Reasoning for an Adaptive E-Commerce Experience

As e-commerce applications proliferates the Web, the authors are often overwhelmed by the task of sifting through the copious volumes of information. Since the nature of foraging for information in such digital spaces can be characterized as the interaction between internal task representation and the external problem domain, the authors look at how expert systems can be used to reduce complexity of the task. They describe a conceptual framework to analyze user interactions based on mental representations. They also detail an expert system implementation using the ontology language OWL to express the semantics of the representations and the rule language SWRL to define the rule base for contextual reasoning. The chapter illustrates how an expert system can be used to guide users in an e-commerce setting by orchestrating a cognitive fit between the task environment and the task solution.

Extending Loosely Coupled Federated Information Systems Using Agent Technology

Different FIPA-compliant agent development platforms are available for developing multiagent systems. FIPA compliance ensures interoperability among agents across different platforms. Although most agent implementation platforms provide some form of white- and yellow-page functionalities to advertise and identify agent roles and descriptions, there are no clear architectural standards that define how an agent community can effortlessly adapt to operate in a federated information system (FIS) where new content sources are constantly added or changes are made to existing content sources. This article presents a framework based on the semantic Web vision to address extensibility in a loosely coupled FIS.

Integrating Data Mining and On-line Analytical Processing for Intelligent Decision Systems

Data Mining (DM) and On-Line Analytical Processing (OLAP) are powerful methods to model relationships in databases and analyze vast amounts of data. However, little research exists in developing methods to integrate the DM and OLAP to develop an Intelligent Decision Support System (IDSS). This study proposes a model to integrate DM and OLAP to build accurate and dynamic models of the process and to provide analytical views of the data. The integrated system uses DM to discover the complex relationships hidden in large volumes of data. This data is organized and presented for decision-making using OLAP for which multidimensional views are created by the results from the relationships discovered by mining the data. The model is applied to a complex manufacturing process control problem.

PAST: Viewing the programming process

A software package called PAST (Programmer Assessment Software Tools) is described. PAST was designed as a research and diagnostic tool to analyze how programmers develop and test program code. PAST uses line changes between successive compiles to estimate a programmer’s cognitive processing. Line changes are highlighted and graphically presented between any two versions or compiles. Summary graphs and statistics across all versions also are provided. Applications of PAST for expanding our understanding of programming and applying it to research, teaching, and learning are discussed.

Measuring change in the programming process

A type of data (change data) associated with the programming process is defined. Change data is defined as the set of changes made to a program during program enhancement or development. Included in this set are changes made and later discarded. A collection of measures which are derived from change data are developed. Special attention is given to program language independence when isolating changes made to programs. A methodology for gathering change data is presented and insights into the meaning of these data are provided. The ease of gathering change data is shown through an example case. Potential application areas for use of change data and the associated measures are suggested.