User-database Interaction Research Articles

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A field study of database communication issues peculiar to users of a voice activated medical tracking application

This paper investigates database communication issues peculiar to users of a voice activated medical tracking application (VAMTA). Specifically, this study investigates voice activated user–database interaction, in terms of user gender, speech speed in words per minute (WPM) and technical computer experience of the users. A VAMTA device is employed to help solve the business and clinical needs of medical personnel, and to help them facilitate communication and interaction with database systems and designers, who are interested in improving technical specifications. The VAMTA device was integrated into a Dragon Naturally Speaking commercial system. The ability of the VAMTA to interact effectively and efficiently with the database of medical patient signs and symptoms has enhanced the productive usage of database systems that are vital components of the medical organization information systems. In this paper, we address the communication issues in voice activated user–database interaction and the philosophical perspectives of database modeling, by identifying gender and experience factors as important barriers and issues that must be further investigated to improve communication between user and database systems. Our research studies the impact of user's gender, speech speed in WPM and user's computer experience on the performance of a speech recognition system. We also investigated the interactive effects of gender and user, user and WPM, and gender and WPM. Our research investigates 33 users; a voice activated medical tracking application and a mobile healthcare fieldwork environment. The field study suggests that VAMTA can be applied to either an emergency medical services or preventative care setting. We illustrate that the user's gender and computer experience has a significant impact ( p < 0.05) on the use of voice interface as an input to a medical database of patient signs and symptoms. WPM and the interaction of gender and WPM show a weak impact ( p < 0.10) on system performance.

Modelling Situated Actions in Collaborative Hypertext Databases

The need to model users' dynamic behaviour in Computer Supported Cooperative Work (CSCW) systems arises in many contexts. This study developed a probabilistic model of the usage of an awareness-maintaining mechanism in a collaborative hypertext database system. Longitudinal time series data of user-database interaction were studied. The study found that the recurring patterns in the occurrences of the awareness-seeking event were related to several contextual aspects of the CSCW system studied. The context-behaviour relationship is captured by a Poisson regression model. The analytical method can be applied to the study of situated actions in other CSCW systems.

Cognitive Mapping Techniques for User–Database Interaction

In this paper, we first develop a framework of user-database interaction. Based on this framework, we then provide a discussion on how notable human factors influence various dimensions of user-database interaction. Following that, we propose using cognitive mapping techniques to overcome some cognitive and behavioral biases during user-database interaction. Three popular cognitive mapping techniques-causal mapping, semantic mapping, and concept mapping-are introduced as techniques to elicit an individual's belief systems regarding a problem domain. Through an example database application, we demonstrate how to use these cognitive mapping techniques to improve user-database interaction. Finally, we discuss the implications of this research for technical communicators during user-database interaction analysis and design.

Introduction to the Special Issue on Communication Issues in User–Database Interaction

Research on user–database interaction studies the communication issues among users with various roles, such as end-user, requirement analyst, database designer, query programmer, as well as between users and databases through various database management systems. Many topics are included. Common topics include the formal languages used in database models and queries, with focus on designer and user writing effectiveness and efficiency, as well as end-user comprehension and problem solving capabilities. Research results are generally applicable to the communication processes for users, user training, and the design of database management systems, such as query interfaces and choice of database models.

Effects of Query Complexity and Learning on Novice User Query Performance With Conceptual and Logical Database Interfaces

Users see the database interface as the database system. A good interface enables them to formulate queries better. The semantics communicated through the interface can be classified according to abstraction levels, such as the conceptual and logical levels. With the conceptual interface, interaction is in terms of real-world concepts such as entities, objects and relationships. Current user-database interaction is mainly based on the logical interface, where interaction is in terms of abstract database concepts such as relations and joins. Many researchers argue that end users will perform better with the conceptual interface. This research tested this claim, as well as the effects of query complexity and learning, on the visual query performance of users. The experiment involved three tests: an initial test, a retention test and a relearning test. The results showed that, for complex queries, conceptual interface users achieved higher accuracy, were more confident in their answers, and spent less time on the queries. This is persistent across retention and relearning tests.

A visual object-relationship query language for user–database interaction

User–database interaction has a direct and immediate effect on the effectiveness and efficiency of database end users. Traditional query languages like SQL and QBE require end users to understand the underlying data structure in the database. This is a burden on end users, especially novice end users who have little technical knowledge or understanding of database. To alleviate the need for end users to know the logical database organization, this paper proposes the use of an object–relationship (OR) model and a formal high-level visual query language as the interface. Using this interface, end users communicate only domain knowledge with the system without the need to specify the storage structure or search strategies. The end users deal only with the conceptual model of the database and not the actual physical implementation of the database. To demonstrate the expressive power of the visual query language, this paper also provides a proof to show that it is relationally complete and hence is as powerful as traditional languages such as SQL.

User-database interaction at the knowledge level of abstraction

Despite the widespread popularity of relational databases, it is still very difficult for trained users to formulate relational queries. The major cause of this difficulty is the fact that the user and the database system are forced to communicate using constructs that are not closely related to the user's world. This paper proposes and develops a new level of user-database interaction, the knowledge-level (KL) interface, where the user and the database system exchange only knowledge from the user's world. The data structure used in the database is fully hidden from the user. Under the new KL approach, the database system is no longer seen as a store of data. Rather, it is an agent to hold domain knowledge and provide it upon request. It is shown that the KL interface is in many ways better than the relational interface. Users of the KL interface need to know less and perform fewer data manipulation operations than users of the relational interface.

The effect of a database feedback system on user performance

Abstract There are two main approaches to improving the effectiveness of database interfaces. One is to raise the level of abstraction for the content of the user-database interaction. The relational model belonging to the logical level has replaced the hierarchical and network models that belong to the lower physical level. It is likely that the relational model will eventually be replaced by models belonging to the even higher conceptual level, such as entity relationship models and object-oriented models. The second approach is to enhance the actual interaction process. This can be done by providing better feedback to the user. Feedback can be in the form of more comprehensible error messages, and the provision of a natural language interpretation of user's query. Such a feedback system was developed, and its effectiveness tested in an experiment. The results showed that the feedback system enhanced user performance greatly. Specifically, users who used the feedback system were 12.9% more accurate than those without the feedback system. They were also 41.2% more confident of their answers, and they took 29.0% less time than those without the feedback system.

User-Database Interface: The Effect of Abstraction Levels on Query Performance

A common classification of data models is based on their abstraction levels: physical, logical and conceptual. The user-database interaction can be similarly classified. For the conceptual-level interaction, the user and the database exchange information on the user's world, e.g., information of entities, relationships, and attributes. For the logical-level interaction, the user and the database communicate based on concepts in the database system, e.g., relations and join operations. We expect users to be familiar with concepts in their world but not the concepts in the database system. This is especially so for infrequent or naive database users. The conceptual level should therefore be easier because it is semantically closer to the user. This deduction was tested in an experiment using the entity-relationship (ER) model for the conceptual-level model and the relational model for the logical-level model. The results were affirmative. The users at the conceptual level had 38 percent higher accuracy and 16 percent higher confidence than users at the logical level. The conceptual-level users took 65 percent less time than the logical-level users, and it took 33 percent less time to train them. The differences were statistically significant with p < 0.003. The huge differences indicate that noticeable improvements can be made by switching from the relational model to the ER model. The experiment also provided valuable data on errors commonly made by users.

Q-analysis of user-database interaction

This study jointly employed two research approaches in developing a process oriented methodology for studying information seeking during user-database interaction. A "time-line" structured interview technique was used to gather 26 novice-user accounts of search sessions on NEXIS. These accounts included a description of the search session, questions that occurred to users during this session, and indications on whether answers were obtained. A 17 category descriptive content analysis scheme was developed and Q-analysis was performed on the accounts as coded into this scheme. Results provide a rich description of the search process from the user's viewpoint. Searchers below the mean on a document relevance measure most frequently had questions after being in some way rebuffed by the system. Above mean searchers were also active questionners, but their questions were most frequently associated with string design rather than being rebuffed. The above mean group also rated their questions as less important than did the below mean group. In addition, above mean searchers were more active users of system help features and information provided onscreen in general.

An entity relationship menu system for microcomputers

Empirical studies have shown that relational databases are difficult to use, especially for novice users. Experimental studies have also shown that substantial improvements in user productivity can be obtained if the relational interface is replaced by an entity-relationship (ER) interface. Microcomputers and relational database products for microcomputers are increasing rapidly. It is important to enhance the user-database interaction by providing an ER interface.The design and implementation of a system that provides an entity relationship menu is described. With the objective that the system should be able to run on many microcomputers with minimal cost and changes, it was built as a front-end to dBASE. This allows it to be used by the large number of users of dBASE and dBASE compatible packages. The full implementation consists of 136 kbytes of codes. This small front-end can be easily added to a dBASE system. This system covers the full range of database interaction from database design to database retrieval. It is expected that this system will reduce the effort in developing new dBASE applications, since it already contains the basic functionality and integrity of the ER model. Being based on the ER instead of the relational model, it is also expected, as has been shown in empirical studies, to increase the user's effectiveness in interacting with the database.

Intentional resolution of privacy protection in database systems

Traditionally, privacy protection in database systems is understood to be the control over what information a given user can get from a database. This paper is concerned with another, independent, dimension of privacy protection, the control over what a user is allowed to do with a piece of information supplied to him by the database. The ability to condition the supply of information on its intended use is called here “intentional resolution” of privacy protection. The practical importance of intentional resolution is demonstrated by several examples, and its realization is discussed. It is shown that intentional resolution can be achieved, but that it involves a radical change from the traditional approach to the process of user-database interaction. In particular, it appears to be necessary for the database to impose a certain amount of control over the internal behavior of users' programs which interact with it. A model for user-database interaction which admits such a control is developed.