Using a knowledge learning framework to predict errors in database design

Conceptual data modeling is a critical but difficult part of database development. Little research has attempted to find the underlying causes of the cognitive challenges or errors made during this stage. This paper describes a Modeling Expertise Framework (MEF) that uses modeler expertise to predict errors based on the revised Bloom's taxonomy (RBT). The utility of RBT is in providing a classification of cognitive processes that can be applied to knowledge activities such as conceptual modeling. We employ the MEF to map conceptual modeling tasks to different levels of cognitive complexity and classify current modeler expertise levels. An experimental exercise confirms our predictions of errors. Our work provides an understanding into why novices can handle entity classes and identifying binary relationships with some ease, but find other components like ternary relationships difficult. We discuss implications for data modeling training at a novice and intermediate level, which can be extended to other areas of Information Systems education and training.     

Mapping Considerations in the Design of Schemas for the Relational Model

The typical design process for the relational database model develops the conceptual schema and each of the external schemas separately and independently from each other. This paper proposes a new design methodology that constructs the conceptual schema in such a way that overlappings among external schemas are reflected. If the overlappings of external schemas do not produce transitivity at the conceptual level, then with our design method, the relations in the external schemas can be realized as a join over independent components. Thus, a one-to-one function can be defined for the mapping between tuples in the external schemas to tuples in the conceptual schema. If transitivity is produced, then we show that no such function is possible and a new technique is introduced to handle this special case.     

Distributed representation learning and intelligent retrieval of knowledge concepts for conceptual design

Data-driven conceptual design is rapidly emerging as a powerful approach to generate novel and meaningful ideas by leveraging external knowledge especially in the early design phase. Currently, most existing studies focus on the identification and exploration of design knowledge by either using common-sense or building specific-domain ontology databases and semantic networks. However, the overwhelming majority of engineering knowledge is published as highly unstructured and heterogeneous texts, which presents two main challenges for modern conceptual design: (a) how to capture the highly contextual and complex knowledge relationships, (b) how to efficiently retrieve of meaningful and valuable implicit knowledge associations. To this end, in this work, we propose a new data-driven conceptual design approach to represent and retrieve cross-domain knowledge concepts for enhancing design ideation. Specifically, this methodology is divided into three parts. Firstly, engineering design knowledge from the massive body of scientific literature is efficiently learned as information-dense word embeddings, which can encode complex and diverse engineering knowledge concepts into a common distributed vector space. Secondly, we develop a novel semantic association metric to effectively quantify the strength of both explicit and implicit knowledge associations, which further guides the construction of a novel large-scale design knowledge semantic network (DKSN). The resulting DKSN can structure cross-domain engineering knowledge concepts into a weighted directed graph with interconnected nodes. Thirdly, to automatically explore both explicit and implicit knowledge associations of design queries, we further establish an intelligent retrieval framework by applying pathfinding algorithms on the DKSN. Next, the validation results on three benchmarks MTURK-771, TTR and MDEH demonstrate that our constructed DKSN can represent and associate engineering knowledge concepts better than existing state-of-the-art semantic networks. Eventually, two case studies show the effectiveness and practicality of our proposed approach in the real-world engineering conceptual design.     

Constraint acquisition for Entity-Relationship models

We establish search algorithms from the area of propositional logic as invaluable tools for the semantic knowledge acquisition in the conceptual database design phase. The acquisition of such domain knowledge is crucial for the quality of the target database.Integrity constraints are conditions that capture the semantics of the application domain under consideration. They restrict the databases to those that are considered meaningful to the application at hand. In practice, the decision of specifying a constraint is very important and extremely challenging.We show how techniques from propositional logic can be utilised to offer decision support for specifying Boolean and multivalued dependencies between properties of entities and relationships in conceptual databases. In particular, we use a search version of SAT-solvers to semi-automatically generate sample databases for this class of dependencies in Entity-Relationship models. The sample databases enable design participants to judge, justify, convey and test their understanding of the semantics of the future database. Indeed, the decision by the participants to specify a dependency explicitly is reduced to their decision whether there is some sample database that they can accept as a future database instance.     

Flexible control in expert systems for construction tasks

In most expert systems for constructional tasks, the knowledge base consists of a set of facts or object definitions and a set of rules. These rules contain knowledge about correct or ideal solutions as well as knowledge on how to control the construction process. In this paper, we present an approach that avoids this type of rules and thus the disadvantages caused by them.We propose a static knowledge base consisting of a set of object definitions interconnected by is-a and part-of links. This conceptual hierarchy declaratively defines a taxonomy of domain objects and the aggregation of components to composite objects. Thus, the conceptual hierarchy describes the set of all admissible solutions to a constructional problem. Interdependencies between objects are represented by constraints. A solution is a syntactically complete and correct instantiation of the conceptual hierarchy.No control knowledge is included in the conceptual hierarchy. Instead, the control mechanism will use the conceptual hierarchy as a guideline. Thus it is possible to determine in which respects a current partial solution is incomplete simply by syntactical comparison with the conceptual hierarchy. The control architecture proposed here has the following characteristics: separation of control and object knowledge, declarative representation of control knowledge, and explicit control decisions in the problem solving process. Thus, a flexible control mechanism can be realized that supports interactive construction, integration of case-based approaches and simulation methods.This control method is part of an expert system kernel for planning and configuration tasks in technical domains. This kernel has been developed at the University of Hamburg and is currently applied to several domains.     

Modeling collaboration for large-scale software system integration by formal communication models

In the development of large software systems, several synchronization points have to be passed successfully in order to achieve high-end user acceptance of the final system. In particular, the integration of conceptual design entities has turned out to be the most crucial step in software development. At this point, an explicit representation of the organizational knowledge, namely how the integration can be performed, is required. The overall organization of the integration of design entities is a set of knowledge, action (including communication), and time. The knowledge part comprises the integration procedure itself as well as the design entities. Actions are performed by the members of the project team (project leaders, developers). Each integration step has to be performed synchronized, so that each member of the development team knows concurrently the status of the integration procedure. All other individual design activities are usually performed asynchronously. According to the need for an explicit representation of the organizational knowledge for large software system design, this paper attempts tounderstand the nature of large software system integration and formallydescribes the coordination of a dispersed set of software developers. The organizational knowledge is represented by processes that occur in an asynchronous development environment. The design knowledge is assigned to logical formulas that are processed as exchanged messages among developers. Hence, the activities for integration are based on the transmission of messages. Time-critical events, such as the integration of a particular design entity into the final conceptual design of the software system, have to become common knowledge concurrently for all developers. This organizational constraint has been formalized in the communication model. Not only can the proposed framework be adapted to organizational changes in a flexible way, it can also be applied to any specific development strategy for the integration of conceptual design entities. Thus, such kind of formal communication models may provide a sound basis for cooperative CASE (computer-aided software engineering) tools.This work has been sponsored by the Max Kade Foundation, New York.     

A conceptual approach for the die structure design

A large number of decisions are made during the conceptual design stage which is characterized by a lack of complete geometric information. While existing CAD systems supporting the geometric aspects of design have had little impact at the conceptual design stage. To support the conceptual die design and the top–down design process, a new concept called conceptual assembly modeling framework (CAMF) is presented in this paper. Firstly, the framework employs the zigzag function-symbol mapping to implement the function design of the die. From the easily understood analytical results of the function-symbol mapping matrix, the designer can evaluate the quality of a proposed die concept. Secondly, a new method—logic assembly modeling is proposed using logic components in this framework to satisfy the characteristic of the conceptual die design. Representing shapes and spatial relations in logic can provide a natural, intuitive method of developing complete computer systems for reasoning about die construction design at the conceptual stage. The logic assembly which consists of logic components is an innovative representation that provides a natural link between the function design of the die and the detailed geometric design.     

An easy-maintenance,reusable approach for building knowledge-based systems: application to landscape assessment

Multiple Classification Ripple-Down Rules (MCRDR) is an extended methodology which allows an expert to build and maintain a knowledge-based system for multiple classification without technical assistance. Current MCRDR knowledge bases do not exhibit an explicit model of the relationships for the domain terms used by the expert. This is a strong impediment for both reusing and sharing of MCRDR knowledge bases, as well as for rapid development and maintenance. In this work, we describe how a domain knowledge ontological framework can be integrated with MCRDR, so providing this with explicit reusable knowledge components.     

Conceptual classes and system classes in object databases

In this paper, formal relationships between classes of objects based on semantic data models (i.e. conceptual classes) and classes of objects based on object models (i.e system classes), are established. The proposed method starts from conceptual classes and generates system classes. This method can be employed to implement semantic data models on top of currently available object oriented database systems. As a consequence, the database applications can be specified with the flexibility of a conceptual schema while the obtained implementation exploits the efficiency of an object-oriented database system. Both the correctness and the completeness of our method are demonstrated and a discussion on its complexity is provided. Received January 24, 1992 / March 6, 1997     

Multiobjective layout optimization of robotic cellular manufacturing systems

This paper proposes a multiobjective layout optimization method for the conceptual design of robot cellular manufacturing systems. Robot cellular manufacturing systems utilize one or more flexible robots which can carry out a large number of operations, and can conduct flexible assemble processes. The layout design stage of such manufacturing systems is especially important since fundamental performances of the manufacturing system under consideration are determined at this stage. In this paper, the design criteria for robot cellular manufacturing system layout designs are clarified, and objective functions are formulated. Next, layout design candidates are represented using a sequence-pair scheme to avoid interference between assembly system components, and the use of dummy components is proposed to represent layout areas where components are sparse. A multiobjective genetic algorithm is then used to obtain Pareto optimal solutions for the layout optimization problems. Finally, several numerical examples are provided to illustrate the effectiveness and usefulness of the proposed method.     

Automatic Virtual Entity Simulation of Conceptual Design Results—Part Ⅰ:Symbolic Scheme Generation and Identification

The development of new products of high quality,low unit cost,and short lead time to market are the key elements required for any enterprise to obtain a competitive advantage.For shorting the lead time to market and improving the creativity and performances of the product,a rule-based conceptual design approach and a methodology to simulate the conceptual design results generated in conceptual design process in automatical virtual entity form are presented in this paper.This part of paper presents a rule-based conceptual design method for generating creative conceptual design schemes of mechanisms based on Yan's kinematic chain regeneration creative design method.The design rules are adopted to describe the design requirements of the functional characteristics,the connection relationships and topological characteristics among mechanisms.Through the graphs-based reasoning process,the conceptual design space is expanded extremely,and the potential creative conceptual design results are then dug out.By refining the design rules,the solution exploration problem is avioded,and the tendentious conceptual design schemes are generated.Since mechanical,electrical and hydraulic subsystems can be transformed into general mechansims,the conceptual design method presented in this paper can also be applied in the conceptual design problem of complex mechatronic systems.And then the method to identify conceptual design schemes is given.     

A conceptual database design approach based on rules and heuristics

Conceptual and logical database design are complex tasks for non-expert designers. Currently, the popular data models for conceptual and logical database design are the entity–relationship (ER) and the relational model, respectively. Logical design methodologies for relational databases have relied on mathematically rigorous approaches which are impractical, or textbook approaches which do not provide the rich constructs to capture real applications. Consequently, designers have to use their intuition to develop their own rules and heuristics. There is a need, therefore, to develop practical rules and heuristics that can be used to handle the complexity of design in real applications. This paper proposes a realistic and detailed approach for conceptual design using the ER model for relational databases. The approach is based on four rules that specify the order in which various types of relationships must be modelled, three rules that pertain to detection of derived relationships, and three heuristics based on observation of constructs in real applications. The approach is illustrated by many examples.     

基于有向图的数据流图的E-R模型构建方法

建立概念模型是数据库设计的重要步骤之一,E-R模型是数据库设计中广泛采用的概念模型。本文提出利用业务分析过程中形成的数据流图,把数据流图抽象为有向图,从而构建E-R模型的方法。在大型系统数据库设计过程中,使用这一方法可以快速构建局部应用的E-R模型,大大缩短数据库设计过程中构建E-R模型所耗费的时间。实例验证了本方法在实际工程项目中的实用性和有效性。     

Representation of functional micro-knowledge cell (FMKC) for conceptual design

The conceptual design process of a complex product concerns multidisciplinary design knowledge. This paper presents an approach of consistent knowledge representation for conceptual design. Firstly, the concept of functional micro-knowledge cell (FMKC) is presented, and the knowledge representation approach of FMKC is proposed. In the function layer, the functional ontology is used to provide a rich vocabulary. By constructing the mapping relationships between the function and structure layer, a systematic knowledge representation scheme is obtained. Secondly, the functional knowledge decomposition theory is proposed to unify the resolution of knowledge representation. Finally, the FMKC is applied to a hydraulic cylinder, which demonstrates the possibility in representing the multidisciplinary knowledge for conceptual design with a unified systematic representation scheme. In addition, the FMKC can be used in knowledge fusion and design reuse for our further study.     

Associative learning using similarity knowledge bases for relational database search

A knowledge-based interface system for relational databases is presented. The system consists of two basic components; a similarity knowledge base and a generalization reasoning engine. The knowledge base is a particular type of semantic network that represents similarity relationships between the data. The similarity relationships are derived from the relational database by a psychological model of similarity. The reasoning engine propagates information obtained from the user's responses over the similarity network and also determines the generic kind of question it should next pose to the user. Through this dialog process, the interface system aids the user in specifying requests for relevant data, as well as in retrieving data from the database. Following a presentation of the constructs that support database design, we note that agenda dependency of the dialog results will typically occur. A smoothing mechanism that can reduce this dependency is presented. Incorporation of smoothing in the database design improves the efficiency and the effectiveness of the resulting system.     

Design of engineering databases: A case for more varied semantic modelling concepts

Interest in database support for engineering applications is rapidly growing. In this paper we concentrate on conceptual database design and address the question of what a semantic model should look like, that meets the needs of engineering applications and is sufficiently formal to support validation, optimization, analysis, as well as transformation to an implementation schema. We present several case studies of engineering databases in order to determine major modelling requirements, and compare these to modelling concepts from the data base and knowledge representation fields. We demonstrate that the main issue is not adding further concepts, but to integrate the existing ones in a selective and precise fashion. We suggest to do so by tailoring the semantic model, starting from a set of base concepts and extending these. An initial model and an extensibility mechanism allowing an explicit and declarative definition of higher-order abstractions are presented. This is demonstrated by specifying some simple concepts such as generalization and a more complex time concept for image sequence evaluation.     

A formal approach to automating conceptual structural design,Part I: Methology

In the conceptual phase of structural design a designer develops and investigates many potential alternatives for safe and economic transfer of loads that are to be carried by the structure. A methodology for automating conceptual structural design is presented in this paper. Some of the salient aspects of the methodology are: (1) an explicit representation of the structural form, function, and behavior; (2) modeling the structural engineering domain as well as the strategy employed by expert designers; (3) usingcost/value ratio as an intrinsic measure of the merit of a design alternative; and (4) reduced reliance on heuristics with more emphasis on first principles and fundamental knowledge. The categories of knowledge that need to be represented in a computer system to support the reasoning for conceptual structural design are identified. The use of such knowledge is illustrated through examples based on several different types of structures. A constraint classification system (to organize the constraints that arise from structural and exogenous considerations) is also proposed.     

A structure for expert systems maintenance

An approach to the design of maintainable expert systems is presented. Central to this approach is a conceptual model in which the data and knowledge are both modelled as formal “items” in a uniform way. “Objects” are introduced as “item building” operators. The notion of the “decomposition” of items and objects provides the foundation for a single rule of normalization. This single rule applies to all items and objects, including knowledge items, and is a non-trivial generalization of the traditional normal forms for database. Coupling relationships represent the necessary maintenance paths in the conceptual model. A complete characterization of coupling relationships is given, and the value of normalization to the reduction of maintenance costs is discussed.     

A graph-theoretic approach to conceptual design with functional perspectives

This paper explores the concepts of concurrency in design and develops an approach that involves reliability and other functional perspectives at the conceptual design stage. The paper uses graph theory to represent a product and define the relationships between its components. It employs the graph-theory concepts of the “tree” and the “forest” to represent a functional design artefact and idle condition, respectively.

The approach presented in the paper provides a more refined visualisation of the energy flow and is applicable to numerous designs including sliding gears, clutches, overrunning clutches and flywheels, amongst others. It can be used to concurrently modify the design taking into consideration various constraints, e.g. expected mechanical failures and cost considerations. A case study is presented to illustrate the benefits of the approach discussed in the paper.     

Novice errors in conceptual database design

Conceptual and logical database modelling are difficult tasks for designers, and the potential for committing and correcting errors is significant. This paper reports on two laboratory experiments that investigated the underlying causes of errors committed by novice designers engaged in conceptual database modelling tasks. These causes can be traced to combinatorial complexity of the task, biases resulting from misapplication of heuristics, and incomplete knowledge about database design. The most common error was that subjects translated their initial understanding of the application into final database structures and did not consider alternative hypotheses and solutions. The paper includes recommendations to reduce the occurrence of errors.