Vijay Khatri

Understanding Conceptual Schemas: Exploring the Role of Application and IS Domain Knowledge

Although information systems (IS) problem solving involves knowledge of both the IS and application domains, little attention has been paid to the role of application domain knowledge. In this study, which is set in the context of conceptual modeling, we examine the effects of both IS and application domain knowledge on different types of schema understanding tasks: syntactic and semantic comprehension tasks and schema-based problem-solving tasks. Our thesis was that while IS domain knowledge is important in solving all such tasks, the role of application domain knowledge is contingent upon the type of understanding task under investigation. We use the theory of cognitive fit to establish theoretical differences in the role of application domain knowledge among the different types of schema understanding tasks. We hypothesize that application domain knowledge does not influence the solution of syntactic and semantic comprehension tasks for which cognitive fit exists, but does influence the solution of schema-based problem-solving tasks for which cognitive fit does not exist. To assess performance on different types of conceptual schema understanding tasks, we conducted a laboratory experiment in which participants with high- and low-IS domain knowledge responded to two equivalent conceptual schemas that represented high and low levels of application knowledge (familiar and unfamiliar application domains). As expected, we found that IS domain knowledge is important in the solution of all types of conceptual schema understanding tasks in both familiar and unfamiliar applications domains, and that the effect of application domain knowledge is contingent on task type. Our findings for the EER model were similar to those for the ER model. Given the differential effects of application domain knowledge on different types of tasks, this study highlights the importance of considering more than one application domain in designing future studies on conceptual modeling.

Design, development, and assessment of mobile applications: the case for problem-based learning

This paper describes efforts to develop a pedagogical environment that seeks to influence the learning experiences of students as mobile applications end users, developers, and decision makers. Specifically, via a collaborative effort involving industry sponsors, university technology services, and multiple academic units engaged in information technology education, a graduate-level course called Mobile Applications Development (MAD) was created. The core innovativeness of MAD lies in its delivery structure as a problem-based learning course-centered on emerging technologies like mobile technology-that brings together students with diverse backgrounds from different academic units across the campus. MAD culminates in an industry-sponsored competition, where student teams present their mobile solution to a panel of expert judges from industry and higher education. Via MAD and the associated competitions, students, faculty, and institutional partners can explore the opportunities and challenges associated with mobile technologies. This paper discusses how problem-based learning principles guided the design and implementation of MAD. A multiperspective assessment of the success of MAD is offered. Finally, key lessons learned and guidance to assist other educators are also offered

Connecting IT Services Operations to Services Marketing Practices

The importance of building relationships with customers and trust in the services provider is well documented in the marketing literature. Conceptually, we extend this logic to the context of internal information technology (IT) services operations through the notion of the service delivery chain. The purpose of the study is to examine how key service mechanisms in operational IT implementation are related to employee perceptions of actual system benefits and trust in the IT services provider. We report on a study with 380 employees of 14 bank affiliates that were recently acquired by a bank holding company. The focus of the study is on postimplementation trust rather than preimplementation or initial trust, and the service provider is viewed as the object of trust rather than the technology. Our findings suggest that training, trial, and social influence are key service mechanisms an IT services provider can use to stimulate trust in the IT services provider and the realization of system benefits.

A comprehensive framework for modeling set-based business rules during conceptual database design

Business rules are the basis of any organization. From an information systems perspective, these business rules function as constraints on a database helping ensure that the structure and content of the real world sometimes referred to as miniworld--is accurately incorporated into the database. It is important to elicit these rules during the analysis and design stage, since the captured rules are the basis for subsequent development of a business constraints repository. We present a taxonomy for set-based business rules, and describe an overarching framework for modeling rules that constrain the cardinality of sets. The proposed framework results in various types constraints, i.e.. attribute, class, participation, projection, co-occurrence, appearance and overlappinq, on a semantic model that supports abstractions like classification, generalization/specialization, aggregation and association. We formally define the syntax of our proposed framework in Backus-Naur Form and explicate the semantics using first-order logic. We describe partial ordering in the constraints and define the concept of metaconstraints, which can be used for automatic constraint consistency checking during the design stage itself. We demonstrate the practicality of our approach with a case study and show how our approach to modeling business rules seamlessly integrates into existing database design methodology. Via our proposed framework, we show how explicitly capturing data semantics will help bridge the semantic gap between the real world and its representation in an information system.

Supporting User-Defined Granularities in a Spatiotemporal Conceptual Model

Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because under-specifying the granularity can restrict an application, affect the relative ordering of events and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularity-based spatiotemporal conceptual model is straightforward to use and is comprehensive.

DISTIL: A Design Support Environment for Conceptual Modeling of Spatio-temporal Requirements

We describe DISTIL (DIstributed design of SpaTIo-temporaL data), a web-based conceptual modeling prototype system that can help capture the semantics of spatio-temporal data. Via DISTIL, we describe an annotation-based approach that divides spatio-temporal conceptual design into two steps: first capture the current reality of an application using a conventional conceptual model without considering the spatial aspects, and only then annotate the schema with the spatio-temporal semantics of the application. A database development team can use DISTIL to capture and validate their spatio-temporal data requirements. Using DISTIL we demonstrate that the annotation-based approach for capturing spatio-temporal requirements is straightforward to implement, satisfies ontology-based and cognition-based requirements, and integrates seamlessly into the existing database design methodologies.

Customizing the Representation Capabilities of Process Models: Understanding the Effects of Perceived Modeling Impediments

Process modeling is useful during the analysis and design of systems. Prior research acknowledges both impediments to process modeling that limits its use as well as customizations that can be employed to help improve the creation of process models. However, no research to date has provided a rich examination of the linkages between perceived process modeling impediments and process modeling customizations. In order to help address this gap, we first conceptualized perceived impediments to using process models as a “lack of fit” between process modeling and another factor: (1) the role the process model is intended for; and (2) the task at hand. We conducted a case study at two large health insurance carriers to understand why the lack of fit existed and then show different types of process modeling customizations used to address the lack of fit and found a variety of “physical” and “process” customizations employed to overcome the lack of fits. We generalize our findings into propositions for future research that examine the dynamic interaction between process models and their need to be understood by individuals during systems analysis and design.

GeoCosm: A Semantics-Based Approach for Information Integration of Geospatial Data

Information integration implies access to distributed information sources without interfering with the autonomy of the underlying data sources. Integration of distributed geospatial data requires a mechanism for selecting the data sources and performing data processing operations on the selected sources efficiently. We describe a semantics-based information integration approach that uses a spatio-temporal semantic model to define the geospatial information content of the sources, employs a conflict resolution ontology to resolve semantic heterogeneity, and uses geospatial metadata to help the users evaluate usefulness of the available data sources. We show how the captured metadata can be used for efficient query planning. Based on our proposed approach, we are developing GeoCosm, a web-based prototype that would help integrate autonomous distributed heterogeneous geospatial data.

Information use in solving a well-structured IS problem: the roles of IS and application domain knowledge

While the application domain is acknowledged to play a significant role in IS problem solving, little attention has been devoted to formal analyses of what role it plays, why and how it makes a difference, and in what circumstances. The theory of dual-task problem solving, which formalizes and generalizes the role of both the IS and application domains in IS problem solving, responds to these issues. The theory, which is based on the theory of cognitive fit, can be used to identify supportive, neutral, and conflicting interactions between the two types of knowledge, depending on problem structure. We used this theory to determine how IS and application domain knowledge support the solution of schema-based problem-solving tasks. Although such tasks are well-structured and therefore can be solved using IS domain knowledge alone, they are not fully structured. They require knowledge transformation, which is aided by application domain knowledge. Further, in well-structured tasks, IS and application domain knowledge play independent roles, with no interaction between the two. Analysis of verbal protocol data from the perspective of information use showed that problem solution is aided by both better IS knowledge and better application knowledge.

Infomediation for E-business enabled Supply Chains: A Semantics Based Approach

Infomediation refers to a virtual space where the buyers and sellers can meet, negotiate, and form business relationships. We describe an infomediary-based approach that uses a semantic model to define the information space. Along with the semantic model, we employ an ontology that enables semantic data integration. XML is an emerging standard data format for cross-platform information exchange—our architecture leverages the power of XML to facilitate information exchange. Using these techniques, we are developing a web-based tool to integrate participants in an electronic marketplace. Our approach supports interoperability between loosely coupled virtual partners and enables customization of information for multiple users and devices.