Sudha Ram

Design science in information systems research

Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanitys projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services.

Information systems interoperability: What lies beneath?

Interoperability is the most critical issue facing businesses that need to access information from multiple information systems. Our objective in this research is to develop a comprehensive framework and methodology to facilitate semantic interoperability among distributed and heterogeneous information systems. A comprehensive framework for managing various semantic conflicts is proposed. Our proposed framework provides a unified view of the underlying representational and reasoning formalism for the semantic mediation process. This framework is then used as a basis for automating the detection and resolution of semantic conflicts among heterogeneous information sources. We define several types of semantic mediators to achieve semantic interoperability. A domain-independent ontology is used to capture various semantic conflicts. A mediation-based query processing technique is developed to provide uniform and integrated access to the multiple heterogeneous databases. A usable prototype is implemented as a proof-of-concept for this work. Finally, the usefulness of our approach is evaluated using three cases in different application domains. Various heterogeneous datasets are used during the evaluation phase. The results of the evaluation suggest that correct identification and construction of both schema and ontology-schema mapping knowledge play very important roles in achieving interoperability at both the data and schema levels.

Semantic conflict resolution ontology (SCROL): an ontology for detecting and resolving data and schema-level semantic conflicts

Establishing semantic interoperability among heterogeneous information sources has been a critical issue in the database community for the past two decades. Despite the critical importance, current approaches to semantic interoperability of heterogeneous databases have not been sufficiently effective. We propose a common ontology called semantic conflict resolution ontology (SCROL) that addresses the inherent difficulties in the conventional approaches, i.e., federated schema and domain ontology approaches. SCROL provides a systematic method for automatically detecting and resolving various semantic conflicts in heterogeneous databases. SCROL provides a dynamic mechanism of comparing and manipulating contextual knowledge of each information source, which is useful in achieving semantic interoperability among heterogeneous databases. We show how SCROL is used for detecting and resolving semantic conflicts between semantically equivalent schema and data elements. In addition, we present evaluation results to show that SCROL can be successfully used to automate the process of identifying and resolving semantic conflicts.

Research Commentary: An Agenda for Information Technology Research in Heterogeneous and Distributed Environments

Application-driven, technology-intensive research is critically needed to meet the challenges of globalization, interactivity, high productivity, and rapid adaptation faced by business organizations. Information systems researchers are uniquely positioned to conduct such research, combining computer science, mathematical modeling, systems thinking, management science, cognitive science, and knowledge of organizations and their functions. We present an agenda for addressing these challenges as they affect organizations in heterogeneous and distributed environments. We focus on three major capabilities enabled by such environments: Mobile Computing, Intelligent Agents, and Net-Centric Computing. We identify and define important unresolved problems in each of these areas and propose research strategies to address them.

Multi-user view integration system (MUVIS): an expert system for view integration

A description is given of the architecture and development of a knowledge-based system called MUVIS (multiuser view integration system) to support the design of distributed object-oriented databases. MUVIS is implemented using an object-oriented development environment. It assists database designers in representing user views and integrating these views into a global conceptual view. The view integration component is decoupled from the view modeling component. The underlying data model, the semantic data model, treats all parts of the design as objects, thereby reducing the complexity of the integration.<<ETX>>

Conceptual Modeling - ER 2006

Keynote Papers.- Suggested Research Directions for a New Frontier - Active Conceptual Modeling.- From Conceptual Modeling to Requirements Engineering.- Web Services.- A Context Model for Semantic Mediation in Web Services Composition.- Modeling Service Compatibility with Pi-calculus for Choreography.- The DeltaGrid Abstract Execution Model: Service Composition and Process Interference Handling.- Quality in Conceptual Modeling.- Evaluating Quality of Conceptual Models Based on User Perceptions.- Representation Theory Versus Workflow Patterns - The Case of BPMN.- Use Case Modeling and Refinement: A Quality-Based Approach.- Aspects of Conceptual Modeling.- Ontology with Likeliness and Typicality of Objects in Concepts.- In Defense of a Trope-Based Ontology for Conceptual Modeling: An Example with the Foundations of Attributes, Weak Entities and Datatypes.- Explicitly Representing Superimposed Information in a Conceptual Model.- Modeling Advanced Applications.- Preference Functional Dependencies for Managing Choices.- Modeling Visibility in Hierarchical Systems.- A Model for Anticipatory Event Detection.- XML.- A Framework for Integrating XML Transformations.- Oxone: A Scalable Solution for Detecting Superior Quality Deltas on Ordered Large XML Documents.- Schema-Mediated Exchange of Temporal XML Data.- A Quantitative Summary of XML Structures.- Semantic Web.- Database to Semantic Web Mapping Using RDF Query Languages.- Representing Transitive Propagation in OWL.- On Generating Content and Structural Annotated Websites Using Conceptual Modeling.- Requirements Modeling.- A More Expressive Softgoal Conceptualization for Quality Requirements Analysis.- Conceptualizing the Co-evolution of Organizations and Information Systems: An Agent-Oriented Perspective.- Towards a Theory of Genericity Based on Government and Binding.- Aspects of Interoperability.- Concept Modeling by the Masses: Folksonomy Structure and Interoperability.- Method Chunks for Interoperability.- Domain Analysis for Supporting Commercial Off-the-Shelf Components Selection.- Metadata Management.- A Formal Framework for Reasoning on Metadata Based on CWM.- A Set of QVT Relations to Assure the Correctness of Data Warehouses by Using Multidimensional Normal Forms.- Design and Use of ER Repositories: Methodologies and Experiences in eGovernment Initiatives.- Human-Computer Interaction.- Notes for the Conceptual Design of Interfaces.- The User Interface Is the Conceptual Model.- Towards a Holistic Conceptual Modelling-Based Software Development Process.- Business Modeling.- A Multi-perspective Framework for Organizational Patterns.- Deriving Concepts for Modeling Business Actions.- Towards a Reference Ontology for Business Models.- Reasoning.- Reasoning on UML Class Diagrams with OCL Constraints.- On the Use of Association Redefinition in UML Class Diagrams.- Optimising Abstract Object-Oriented Database Schemas.- Panels.- Experimental Research on Conceptual Modeling: What Should We Be Doing and Why?.- Eliciting Data Semantics Via Top-Down and Bottom-Up Approaches: Challenges and Opportunities.- Industrial Track.- The ADO.NET Entity Framework: Making the Conceptual Level Real.- XMeta Repository and Services.- IBM Industry Models: Experience, Management and Challenges.- Community Semantics for Ultra-Scale Information Management.- Managing Data in High Throughput Laboratories: An Experience Report from Proteomics.- Policy Models for Data Sharing.- Demos and Posters.- Protocol Analysis for Exploring the Role of Application Domain in Conceptual Schema Understanding.- Auto-completion of Underspecified SQL Queries.- iQL: A Query Language for the Instance-Based Data Model.- Designing Under the Influence of Speech Acts: A Strategy for Composing Enterprise Integration Solutions.- Geometry of Concepts.

Who does what: Collaboration patterns in the wikipedia and their impact on article quality

The quality of Wikipedia articles is debatable. On the one hand, existing research indicates that not only are people willing to contribute articles but the quality of these articles is close to that found in conventional encyclopedias. On the other hand, the public has never stopped criticizing the quality of Wikipedia articles, and critics never have trouble finding low-quality Wikipedia articles. Why do Wikipedia articles vary widely in quality? We investigate the relationship between collaboration and Wikipedia article quality. We show that the quality of Wikipedia articles is not only dependent on the different types of contributors but also on how they collaborate. Based on an empirical study, we classify contributors based on their roles in editing individual Wikipedia articles. We identify various patterns of collaboration based on the provenance or, more specifically, who does what to Wikipedia articles. Our research helps identify collaboration patterns that are preferable or detrimental for article quality, thus providing insights for designing tools and mechanisms to improve the quality of Wikipedia articles.

HyperIntelligence: the next frontier

The authors discuss how mental models may be used to organize an individuals thoughts while forming a plan. A hypermedia system, SPRINT, is described which supports an explicit representation of a mental model as a network of associations among the elements of a strategic plan.

Database fragmentation and allocation: an integrated methodology and case study

Distributed database design requires decisions on closely related issues such as fragmentation, allocation, degree of replication, concurrency control, and query processing. We develop an integrated methodology for fragmentation and allocation that is simple and practical and can be applied to real-life problems. The methodology also incorporates replication and concurrency control costs. At the same time, it is theoretically sound and comprehensive enough to achieve the objectives of efficiency and effectiveness. It distributes data across multiple sites such that design objectives in terms of response time and availability for transactions, and constraints on storage space, are adequately addressed. This methodology has been used successfully in designing a distributed database system for a large geographically distributed organization.