X-IM Framework to Overcome Semantic Heterogeneity Across XBRL Filings

2020 | Journal of the Association for Information Systems | Citations: 0

Authors: Liu, Dapeng; Etudo, Ugochukwu; Yoon, Victoria

Abstract: Semantic heterogeneity in XBRL precludes the full automation of the business rep ... Expand

Abstract: Semantic heterogeneity in XBRL precludes the full automation of the business reporting pipeline, a key motivation for the SEC’s XBRL mandate. To mitigate this problem, several approaches leveraging Semantic Web technologies have emerged. While some approaches are promising, their mapping accuracy in resolving semantic heterogeneity must be improved to realize the promised benefits of XBRL. Considering this limitation and following the design science research methodology (DSRM), we develop a novel framework, XBRL indexing-based mapping (X-IM), which takes advantage of the representational model of representation theory to map heterogeneous XBRL elements across diverse XBRL filings. The application of representation theory to the design process informs the use of XBRL label linkbases as a repository of regularities constitutive of the relationships between financial item names and the concepts they describe along a set of equivalent financial terms of interest to investors. The instantiated design artifact is thoroughly evaluated using standard information retrieval metrics. Our experiments show that X-IM significantly outperforms existing methods. Collapse

Topics: electronic data interchange knowledge representation accounting Python web page

Methods: ontological modelling machine learning experiment design artifact financial report

Theories: representation theory theory of ontological clarity sociotechnical systems theory

How Semantics and Pragmatics Interact in Understanding Conceptual Models

2014 | Information Systems Research | Citations: 37

Authors: Bera, Palash; Burton-Jones, Andrew; Wand, Yair

Abstract: Underlying the design of any information system is an explicit or implicit conce ... Expand

Abstract: Underlying the design of any information system is an explicit or implicit conceptual model of the domain that the system supports. Because of the importance of such models, researchers and practitioners have long focused on how best to construct them. Past research on constructing conceptual models has generally focused on their semantics (their meaning), to discover how to convey meaning more clearly and completely, or their pragmatics (the importance of context in model creation and use), to discover how best to create or use a model in a given situation. We join these literatures by showing how semantics and pragmatics interact. Specifically, we carried out an experiment to examine how the importance of clear semantics in conceptual models—operationalized in terms of ontological clarity—varies depending on the pragmatics of readers' knowledge of the domain shown in the model. Our results show that the benefit of ontological clarity on understanding is concave downward (follows an inverted-U) as a function of readers' prior domain knowledge. The benefit is greatest when readers have moderate knowledge of the domain shown in the model. When readers have high or low domain knowledge, ontological clarity has no apparent benefit. Our study extends the theory of ontological clarity and emphasizes the need to construct conceptual models with readers' knowledge in mind. Collapse

Topics: problem solving knowledge representation semantic network IT career database system

Methods: conceptual modelling hierarchical linear modeling experiment statistical hypothesis test ontological modelling

Theories: theory of ontological clarity semiotic theory speech act theory

Construct Redundancy In Process Modelling Grammars: Improving The Explanatory Power Of Ontological Analysis

2013 | European Conference On Information Systems | Citations: 2

Authors: Fickinger, Tobias; Recker, Jan

Abstract: Conceptual modelling supports developers and users of information systems in are ... Expand

Abstract: Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature. Collapse

Topics: knowledge representation usability

Methods: ontological modelling business process modeling business process model and notation modeling language design science

Theories: general systems theory theory of ontological clarity

A Research Note on Representing Part-Whole Relations in Conceptual Modeling

2012 | Management Information Systems Quarterly | Citations: 0

Authors: Allen, Gove N.; March, Salvatore T.

Abstract: Empirical research is an important methodology for the study of conceptual model ... Expand

Abstract: Empirical research is an important methodology for the study of conceptual modeling practices. The recently published article "Representing Part-Whole Relations in Conceptual Modeling: An Empirical Evaluation" (Shanks et al. 2008) uses the lens of ontology to study a relatively sophisticated aspect of conceptual modeling practice, the representation of aggregation and composition. It contends that some analysts argue that a composite should be represented as a relationship while others argue that a composite should be represented as an entity. We find no evidence of such a dispute in the data modeling literature. We observe that composites are objects. By definition, all object-types should be represented as entities. Therefore, using the relationship construct to represent composites should not be seen as a viable alternative. Additionally, we found significant conceptual and methodological issues within the study that call its conclusions into question. As a way to offer insight into the requisite methodological procedures for research in this area, we conducted two experiments that both explicate and address the issues raised. Our results call into question the utility of using ontology as a foundation for conceptual modeling practice. Furthermore, they suggest a contrary but at least equally plausible explanation for the results reported by Shanks et al. In conducting this work we hope to encourage dialogue that will be beneficial for future endeavors aimed at identifying, developing, and evaluating appropriate foundations for the discipline of conceptual modeling. Collapse

Topics: knowledge representation enterprise information system problem solving website

Methods: experiment conceptual modelling design science unified modeling language Bunge ontology

Theories: theory of ontological clarity

The Hole in the Whole: A Response to Allen and March

2012 | Management Information Systems Quarterly | Citations: 4

Authors: Shanks, Graeme; Weber, Ron

Abstract: Allen and March provide a critique of one of our papers in which we argue compos ... Expand

Abstract: Allen and March provide a critique of one of our papers in which we argue composites should be represented as entities/objects in a conceptual model rather than relationships/associations (Shanks et al. 2008). They contend we have addressed a non-issue. Furthermore, they argue our theoretical rationale and empirical evidence have flaws. In this paper, we provide a response to their arguments. We show that the issue we address is substantive. We show, also, that our theoretical analysis and empirical results are robust. We find, instead, that Allen and March's theoretical arguments and empirical evidence have flaws. Collapse

Topics: problem solving knowledge representation database system website

Methods: conceptual modelling experiment design science unified modeling language Bunge ontology

Theories: theory of ontological clarity

On the Specification of Part-Whole Relations in Conceptual Modeling: An Empirical Study

2011 | Americas Conference on Information Systems | Citations: 0

Authors: Wang, Yonggui; Xu, Dongming; Rohde, Fiona H

Abstract: Part-whole relation (PWR), as a fundamental element to model the real world, has ... Expand

Abstract: Part-whole relation (PWR), as a fundamental element to model the real world, has long been concerned by researchers and practitioners. Theoretical work has been undertaken to develop the classifications of distinct types of part-whole relations (PWRs) and their properties in an attempt to clarify their semantics. There is no empirical evaluation, however, that supports whether it is necessary to specify distinct types of PWRs and their properties in conceptual modeling. In this light, this study first designs a specific representation of PWRs through a systematic review of the literature, and then by employing the theory of ontological clarity and the theory of cognitive fit, empirically compares its performance with that of conventional representation of PWRs. The findings are expected to enrich the growing body of knowledge that supports the usefulness of ontological and cognitive theories, and provide empirical evidence regarding how to model the PWRs for practitioners. Collapse

Methods: literature study

Theories: theory of ontological clarity cognitive fit theory cognitive theory