Veda C. Storey

Bio: Veda C. Storey is an academic researcher from J. Mack Robinson College of Business. The author has contributed to research in topics: Computer science & Ontology (information science). The author has an hindex of 18, co-authored 55 publications receiving 5769 citations. Previous affiliations of Veda C. Storey include Pennsylvania State University & Georgia State University.

Business intelligence and analytics: from big data to big impact

Abstract: Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.

A semiotic metrics suite for assessing the quality of ontologies

Abstract: A suite of metrics is proposed to assess the quality of an ontology. Drawing upon semiotic theory, the metrics assess the syntactic, semantic, pragmatic, and social aspects of ontology quality. We operationalize the metrics and implement them in a prototype tool called the Ontology Auditor. An initial validation of the Ontology Auditor on the DARPA Agent Markup Language (DAML) library of domain ontologies indicates that the metrics are feasible and highlights the wide variation in quality among ontologies in the library. The contribution of the research is to provide a theory-based framework that developers can use to develop high quality ontologies and that applications can use to choose appropriate ontologies for a given task.

Big data technologies and Management

Abstract: The era of big data has resulted in the development and applications of technologies and methods aimed at effectively using massive amounts of data to support decision-making and knowledge discovery activities. In this paper, the five Vs of big data, volume, velocity, variety, veracity, and value, are reviewed, as well as new technologies, including NoSQL databases that have emerged to accommodate the needs of big data initiatives. The role of conceptual modeling for big data is then analyzed and suggestions made for effective conceptual modeling efforts with respect to big data.

Genres of inquiry in design-science research: justification and evaluation of knowledge production

Abstract: Recognizing that design is at the core of information systems development has led to a design-science research paradigm where differing kinds of knowledge goals give form to differing kinds of knowledge processes within a single study This paper analyzes knowledge production in design-science research to explain how an endogenous form of pluralism characterizes such studies, making it problematic to associate any design-science study with a single view of knowledge production Instead, a design-science research study exhibits up to four different modes of reasoning, called genres of inquiry These genres are derived from two dualities that contrast differing knowledge goals and differing knowledge scope in the knowledge production process The first duality arises from the sometimes seemingly contradictory knowledge goals of science versus design The second duality reflects the contradiction between the scope of the knowledge produced, which may be idiographic or nomothetic The evolutionary and iterative nature of a design-science study compels different knowledge goals and scope at different moments throughout a project Because of this momentary nature, a single design-science study can be associated with multiple genres of inquiry This understanding of the variety in the genres of inquiry advances the discourse on the nature of design-science research and the justification and evaluation of its outcomes Consequently, a corresponding set of criteria for knowledge justification and evaluation is provided for each genre of inquiry

Business intelligence and analytics: from big data to big impact

Abstract: Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.