Product data models

The integration in computer integrated manufacturing systems (CIMs) plays a significant role in improving the quality and productivity. To achieve this objective, a uniform product and process representation and an effective, comprehensive and reliable data exchange mechanism are required. Recent works on product data integration have led to STEP (international Standard for Exchange of Product data models). In this paper, we define a model which integrates the STEP product data models with process data models. The idea of classification of STEP product data models is used to classify the process data models. Examples from mechanical industries are included to demonstrate the features of this model.

In this paper, a Graph-based semantic Data Model (GDM) is proposed with the primary objective of bridging the gap between the human perception of an enterprise and the needs of computing infrastructure to organize information in some particular manner for efficient storage and retrieval. The Graph Data Model (GDM) has been proposed as an alternative data model to combine the advantages of the relational model with the positive features of semantic data models. The proposed GDM offers a structural representation for interacting to the designer, making it always easy to comprehend the complex relations amongst basic data items. GDM allows an entire database to be viewed as a Graph (V, E) in a layered organization. Here, a graph is created in a bottom up fashion where V represents the basic instances of data or a functionally abstracted module, called primary semantic group (PSG) and secondary semantic group (SSG). An edge in the model implies the relationship among the secondary semantic groups. The contents of the lowest layer are the semantically grouped data values in the form of primary semantic groups. The SSGs are nothing but the higher-level abstraction and are created by the method of encapsulation of various PSGs, SSGs and basic data elements. This encapsulation methodology to provide a higher-level abstraction continues generating various secondary semantic groups until the designer thinks that it is sufficient to declare the actual problem domain. GDM, thus, uses standard abstractions available in a semantic data model with a structural representation in terms of a graph. The operations on the data model are formalized in the proposed graph algebra. A Graph Query Language (GQL) is also developed, maintaining similarity with the widely accepted user-friendly SQL. Finally, the paper also presents the methodology to make this GDM compatible with the distributed environment, and a corresponding query processing technique for distributed environment is also suggested for the sake of completeness.

Rules, standards and regulations have to be observed in every step of the ship design process. Ignoring these constraints in any case leads to higher costs going along with potentially lower product quality. Numerous investigations have shown that product data model correction activities require considerable resources (man-hours and although money = cost) to obtain an acceptable quality level, and in the worst case, a redesign of potentially larger parts of the ship structure has to be performed. Computer-aided design systems offer a large set of functions to define a product data model. However, in the current situation, these tools are not capable to fully ensure the correctness of the product data model while observing the relevant quality criteria which are generally shipyard specific as they are mainly imposed by the production facilities. A quality management system is introduced which is based on the ISO 10303-59 focusing on quality criteria to be applied for an efficient ship structure production process. The functions of the system will be demonstrated on weldability criteria. These criteria demand notches at distinctive constellations of components depending on their function and, for example, minimum distances and angles between structural parts due to welding processes and material requirements. As an additional criterion, sufficient excess material has to be assigned to plate edges functioning as block boundaries to allow for the correction of inaccuracies in the production process at even late stages. The integration of the product data quality management algorithms with the computer-aided design system, in this case AVEVA marine, shows an efficient correction of inapt data as the automatically detected errors can easily be fixed by means of a guided process including the visualization of the structural parts with the help of the computer-aided design system being applied for data modelling.

There have been several efforts to use relational model and database to store and manipulate Resource Description Framework (RDF). They have one general disadvantage, i.e. one is forced to map the model of semantics of RDF into relational model, which will end up in constraints and additional properties, such as, validating each assertion against the RDF schema which also stored as a triplets table. In this paper, we introduce Semantic Data Model as a proposed data model language to store and manipulate Resource Description Framework. This study also tries to prescribe the procedure on transforming a semantic data model into a RDF data model. Keyworsd: Semantic Data Model, Resource Description Framework.

A novel approach is described for building intelligent information systems (or knowledge-base management systems). The approach utilizes the knowledge data language, which is a schema specification language developed for the knowledge/data model. The model, referred to as a hypersemantic data model, captures both knowledge semantics, as specified in knowledge-based systems, and data semantics, as represented by semantic data models. Hypersemantic data models facilitate the incorporation of knowledge in the form of heuristics, uncertainty, constraints and other artificial intelligence concepts, together with object-oriented concepts found in semantic data models. The unified knowledge/data modeling features and constructs of the language are used to develop a prototype knowledge base management system, the KDL-advisor. >

This research presents a method for constructing a semantic data model for the field of material science based on ontology. The method involves designing the semantic data model and establishing mapping rules between the data model and the ontology. Data semantic analysis and annotation are carried out based on the semantic data model, supporting the integration and efficient retrieval of heterogeneous data in the material science field. Furthermore, the method utilizes the OWL-S technique to describe, issue, and acquire relevant data services, enabling higher-level service semantic synergy in the material science domain. The proposed method effectively enables semantic integration, intelligent inquiry, and personalized services for data in the material science field.

In the current rapidly changing manufacturing environment, most manufacturing companies have realised that the ability to quickly develop a customised product at competitive prices is very crucial for them to survive in the keen competitive global market. Product modelling has been recognised as one of the key factors in determining the success of various product development strategies and for industrial competitiveness now and in the future. Standard for Exchange of Product model data (STEP) is an international standard designed to provide a complete, unambiguous, computer-readable definition of the physical and functional characteristic of a product through its lifecycle. This paper proposes a STEP-compliant product data model to fully support the complete product information representation and management for injection moulding product development. The data model is developed based on the structure of an injection moulding company. The entire data model consists of six data models which are defined to express information from various departments of the company. The data model is described in EXPRESS language, which can be integrated with other STEP-based product data models and databases. Consequently, the proposed system can be further extended for helping other injection moulding manufacturers to improve their product development process. An information sharing prototype system is implemented based on the proposed product data model to demonstrate the feasibility of the approach.

A data model for moving objects is a blueprint that describes data of interest related to movements of objects and a set of operations represented in an information or database management system. Designing an appropriate data model fosters conceptual understanding of the dynamic phenomena of moving objects, yields efficient data storage and retrieval, and further facilitates spatiotemporal analytical processes. Various data models have been proposed to efficiently and effectively store, manage, query, and analyze data about moving objects. This entry starts with the description of fundamental elements of moving objects and their abstract data types. Then it reviews data modeling approaches for representing moving objects, including conventional spatiotemporal data model, constraint model, moving object data model, semantic trajectory data model, event‐based data model, and models for handling big moving object data.

Conventional data models are not satisfactory for modelling data base application systems. The features that they provide are too low level and representational to allow the semantics of a data base to be directly expressed in the schema. The semantic data model (SDM) has been designed as a natural application modelling mechanism that can capture and express the structure of an application environment. The features of the SDM correspond to the principal intensional structures naturally occurring in contemporary data base applications. Furthermore, facilities for expressing derived (redundant) information are an essential part of the SDM; derived information is as prominent in an SDM schema as is primitive data. The SDM is designed to enhance the effectiveness and usability of computerized data bases. It can serve as a formal specification and documentation mechanism for a data base, can support a variety of powerful user interface facilities, and can be used as a tool in the data base design process.

Semantic data modeling of multimedia data is a fundamental problem in multimedia databases. The variety, context-dependency, and ambiguity of the semantics of multimedia data make it difficult to apply conventional data modeling techniques, which usually deal with explicit, self-contained alphanumeric data. Many semantic data modeling techniques are either designed for multimedia or can be used for modeling multimedia data. Specifically, we describe MediaView as a novel object-oriented view mechanism that can successfully capture the elusive nature of multimedia data.

A modern engineering environment needs to solve the problem of integration between different applications. Recent works on product data integration have led to STEP (international Standard for Exchange of Product data models). Unfortunately STEP doesn’t emphasize on the reprsesentation of activities. In this paper, firstly we describe a methodology for classification of activities and then using the object-oriented approche, we define a model which integrates the STEP product data models with activity data models. Some examples in the domain of kinematics analysis and geometric modeling are included.

Decomposing relationship types by pivoting and schema equivalence

To develop semantically-oriented corporate applications, this chapter recommends a data model using RDF, RDFS, and OWL. Instead of static online, an interconnected semantic web is developed using RDF and OWL. Existing corporate applications’ data has been transformed into RDF/OWL equivalents in a number of different attempts to make it available on the semantic web. Even though relational database modeling was used in the majority of applications, in this chapter, we’ll go over why RDF/OWL semantic data modeling is so important and how to go about putting these best practices into action. Furthermore, we demonstrate the value of our method by contrasting it with conventional relational data modeling. RDFS, RDF, OWL, and SPARQL are just a handful of the terms we’ll employ.

Emerging developments in geographic information systems and distributed computing offer a roadmap towards an unprecedented spatial data infrastructure in the climate sciences. Key to this are the standards developments for digital geographic information being led by the International Organisation for Standardisation (ISO) technical committee on geographic information/geomatics (TC211) and the Open Geospatial Consortium (OGC). These, coupled with the evolution of standardised web services for applications on the internet by the World Wide Web Consortium (W3C), mean that opportunities for both new applications and increased interoperability exist. These are exemplified by the ability to construct ISO‐compliant data models that expose legacy data sources through OGC web services. This paper concentrates on the applicability of these standards to climate data by introducing some examples and outlining the challenges ahead. An abstract data model is developed, based on ISO standards, and applied to a range of climate data –both observational and modelled. An OGC Web Map Server interface is constructed for numerical weather prediction (NWP) data stored in legacy data files. A W3C web service for remotely accessing gridded climate data is illustrated. Challenges identified include the following: first, both the ISO and OGC specifications require extensions to support climate data. Secondly, OGC services need to fully comply with W3C web services, and support complex access control. Finally, to achieve real interoperability, broadly accepted community‐based semantic data models are required across the range of climate data types. These challenges are being actively pursued, and broad data interoperability for the climate sciences appears within reach. Copyright © 2005 Royal Meteorological Society.

This paper attempts to design a user-friendly interface which enhances usability of relational database systems. Our approach to usability is to design a semantic data model suitable for a user interface and provide an easy-to-use query language DOMCALC (domain calculus language) which is based on the semantic data model. A query in DOMCALC can be described in terms of intuitive notions, namely domains, instead of relations and attributes. That is, DOMCALC requires for users no knowledge of a conceptual database such as relation names and attribute names. Therefore, the usability based on the semantic data model removes the requirement of knowledge of a conceptual database from users and protects user views from changes in the conceptual database. We also describe an outline of a database system PRIM (Prototype of Laboratory information Management System) which has been developed with the above considerations. This is a step toward the enhancement of usability in relational database systems.