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The purpose of this paper is to compare fundamental concepts from the grounded theory approach to social science research and concepts from entity‐relationship diagramming, a technique used to model data from the field of systems analysis, and propose that entity‐relationship diagramming can be a useful tool for grounded theory researchers.

The paper compares and contrasts concepts from the two different fields, demonstrating the construction of an entity‐relationship diagram from data from an existing grounded theory research project, and the correspondence between the data model constructs and the grounded theory constructs.

A strong correspondence was found between these two sets of concepts and suggests that the entity‐relationship diagramming technique may be a useful addition to the social scientist's toolkit when carrying out research using the grounded theory approach.

The paper bridges two distinct fields – information systems and grounded theory – and proposes a novel way for qualitative researchers to analyse and depict data.

Modelling complex knowledge resources can be problematical as there is currently no formalism that can represent the nature of the data‐seeking process at a conceptual level. The purpose of this paper is to develop a knowledge representation formalism, the functional entity relationship diagram (FERD), which comprises a set of extensions to the industry standard entity relationship diagram established by Chen.

The research uses a design science approach to extend the existing ER formalism using the question‐answering (QA) paradigm. It is an extension of standard data modelling theory and is consistent with category theory.

The authors defined the functional entity, an encapsulated data resource that acts as a QA system and enumerated a typology of nine functional entities generated from two established principles to produce a modelling framework that can depict all existentially quantifiable relations, and demonstrated a satisficing extension to that framework (non‐Aristotelian functional entities) for those situations that do not permit such relations. Further, the authors discussed the system of knowledge mixins for qualifying the relations, and presented an adjunct to the framework, cartographic functional entities, to permit formally verifiable documentation.

Future research will address the pragmatic/sociological dimensions of FERD modelling, and test its utility in field case studies.

The FERD conceptualisation incorporates traditional IS modelling as one aspect of a richer modelling system, and thereby includes all of traditional IS repositories as first class, unmediated sources of knowledge. The establishment of standard types of functional entities can provide a framework for the methodical conversion of the declarative design level to the imperative implementation level. It thus has significant practical implications for the management and use of knowledge in organisations.

The research is original and provides a valuable contribution to conceptual modelling and representation of complex knowledge systems.

The purpose of this paper is to consider the nature of community information (CI) and proposes a data model, based on the entity-relationship approach adopted in the Functional Requirements for Bibliographic Records (FRBR), which may assist with the development of future metadata standards for CI systems.

The two main data structure standards for CI, namely the element set developed by the Alliance of Information and Referral Systems (AIRS) and the MARC21 Format for CI, are compared by means of a mapping exercise, after which an entity-relationship data model is constructed, at a conceptual level, based on the definitions of CI found in the literature.

The AIRS and MARC21 data structures converge to a fair degree, with MARC21 providing for additional detail in several areas. However, neither structure is systematically and unambiguously defined, suggesting the need for a data model. An entity-relationship data modelling approach, similar to that taken in FRBR, yielded a model that could be used as the basis for future standards development and research. It was found to effectively cover both the AIRS and MARC21 element sets.

No explicit data model exists for CI, and there has been little discussion reported about what data elements are required to support CI seeking.

This paper proposes a systematic scheme for synthesizing formal specification from the definitions of relational data model – entity relationship diagram and their data dictionaries. The formal specification of both structural and behavioral properties of relational data model is generated in Z schemas. In our approach, the mandatory structural constraints – the uniqueness of primary key, foreign keys, and referential integrity constraints among the relations in the model, are preserved. We propose a set of transformation rules to produce Z schemas of the states and primitive operations – cascade insertion, deletion, and updating. Moreover, a composition technique of constructing the composite operations is presented by using requirements particle networks. The revision of the formal specification can be easily conducted with the mathematical proofs of the properties of the data model using Z prover tool.

This research conducted two experiments to understand the performance (correctness and efficiency) of novice database designers, and perceptions of ease of use and preferences of two approaches for modeling relational databases: the semantic‐oriented approach (top‐down, e.g. using the entity‐relationship model) and the logical‐oriented approach (bottom‐up, view decomposition, focusing only on the logical model). The findings indicated that in experiment 1, semantic‐oriented treatments performed better in a complex, written‐text case; logical‐oriented treatments were better in a simple, tabular‐form case. The same situation happened in experiment 2 though the differences were not statistically significant.

Describes an innovative pictorial representation of business rules which clarifies the interrelationships of data entities and semantic constraints to enhance the communication among different levels of management. This pictorial representation scheme can be implemented using a set of microcomputer‐based CASE tools, and the result provides a comprehensive view of all aspects of management activity.

Although systems analysis for designing information systems shares much in common with business process mapping there are critical differences. Systems analysis methodology produces a logical model, which omits all extraneous detail (in a somewhat similar spirit to business process re‐engineering). The approach is based on two views: entity‐relationships for data modelling and data flow diagramming for representing functions (which is used in a similar context to process in BPR terminology). A third view using an event driven process network, which serves as a macro representation complementing the other two views, is advocated.

The purpose of the paper is to obtain insight into, and provide practical advice for, event‐based conceptual modeling.

The paper analyzes a set of event concepts and uses the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static information models.

The paper characterizes events as short‐duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can be used to integrate dynamic modeling of processes and static modeling of information structures.

The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used to improve dynamic and static modeling.

The purpose of this paper is to compare the use of two Object-Relational models against the use of a post-Relational model for a realistic application. Although real-world applications, in most cases, can be adequately modeled by the Entity-Relationship (ER) model, the transformation to the popular Relational model alters the representation of structures common in reality, like multi-valued and composite fields. Alternative database models have been developed to overcome these shortcomings.

Based on the ER model of a medical application, this paper compares the information representation, manipulation and enforcement of integrity constraints through PostgreSQL and Oracle, against the use of a post-Relational model composed of the Conceptual Universal Database Language (CUDL) and the Conceptual Universal Database Language Abstraction Level (CAL).

The CAL/CUDL pair, although more periphrastic for data definition, is simpler for data insertions, does not require the use of procedural code for data updates, produces clearer output for retrieval of attributes, can accomplish retrieval of rows based on conditions that address composite data with declarative statements and supports data validation for relationships between composite data without the need for procedural code.

To verify, in practice, the conclusions of the paper, complete implementation of a CAL/CUDL system is needed.

The use of the CAL/CUDL pair would advance the productivity of database application development.

This paper highlights the properties of realistic database-applications modelling and management that are desirable by developers and shows that these properties are better satisfied by the CAL/CUDL pair.

A plethora of BPR methodologies have appeared in the literature during recent years, however, most of them present serious limitations mainly due to the need for a multi‐disciplinary approach. In this paper we present an overview of existing work in the area of BPR with the aim of highlighting the different categories of BPR methodologies identified in the literature, their focus on the redesign process and the general BPR principles that emerge from them. We also present a BPR methodology called Agent Relationship Morphism Analysis (ARMA) that goes beyond the limitations of the existing BPR methodologies taking a holistic view of the organisation. In ARMA the modelling of the business environment is achieved with the use of three perspectives: the structural, behavioural and process. The use of these three perspectives provides insight to the relationship between organisational structure and organisational processes.