Abstract
Many industries prefer worldwide business operations due to the economic advantage of globalization on product design and development. These industries increasingly operate globalized multi-tier supply chains and deliver products and services all over the world. This global approach produces huge amounts of heterogeneous data residing at various business operations, and the integration of these data plays an important role. Integrating data from multiple heterogeneous sources need to deal with different data models, database schema, and query languages. This chapter presents a semantic web technology-based data integration framework that uses relational databases and XML data with the help of ontology. To model different source schemas, this chapter proposes a method based on the resource description framework (RDF) graph patterns and query rewriting techniques. The semantic translation between the source schema and RDF ontology is described using query and transformational language SPARQL.
TopIntroduction
A supply chain is a network of business facilities and distribution options that performs key functions: raw material procurement, transformation of these materials into intermediate and finished products, and distribution of these finished products to customers (Pal, 2017). In a typical supply chain, raw materials are purchased from different vendors and products are manufactured at one or more manufacturing plants, shipped to warehouses for intermediate storage, and then shipped to retailers or customers. All supply chains share the following characteristics: (i) in an enterprise all business activities are focused to supply products and/or services to its customers; (ii) any number of supply chain business-partners can be linked in the supply chain; (iii) a customer can be a supplier to another customer within the supply chain, which means that the total network of activities can consists of a number of supplier/customer relationships; (iv) the path from supplier to customer, can include a number of intermediaries (distributors) such as wholesalers, warehouses, and retailers, depending on the products and markets. Associated information flows among different supply chain business-partners. In this way, a supply chain creates a complex set of networked business processes, which need to be optimized for organizational profit. The core business processes of modern supply chains are: procurement, production, and sales. Moreover, these business activities need to consider scheduling, delivery, inventory planning, distribution, and understanding market conditions. Market specific supply and demand information, and warehousing facilities along the supply chain, are highlighted in Figure 1.
Figure 1. A diagrammatic representation of supply chain business processes
Managing a supply chain involves numerous decisions about the flow of information, product, funds, and coordination. Supply chain management (SCM) has been instrumental in connecting and smoothing business activities as well as forming various kinds of business relationships e.g., Customer Relationship Management (CRM), Supplier Relationship Management (SRM), among supply chain stakeholders. In this way, SCM is an integrative mechanism to manage the total flow of a distribution channel from supplier level to production, distribution and then ultimately to the end customer. The aim is to achieve goals related to total system performance rather than optimization of a single phase in a logistics chain. The ultimate aim for SCM is to enhance productivity by reducing total inventory level and cycle time for orders. It is important for supply chain business-partners to create a network that is agile and able to respond rapidly to unpredictable changes in demand. To achieve these objectives close cooperation among business partners is essential.
SCM systems utilize modern Information and Communication Technologies (ICT) to acquire, interpret, retain, and distribute information. The software applications of SCM are ready-made packages, usually targeting a certain set of tasks, e.g. tracking product related information during the transportation process. These ready-made package-software applications are mass-customized products that ignore the specific requirements of a certain business sector, and so they are quite problematic. The problem of the appropriate IT solutions for supporting collaboration between supply chain business-partners is not new and it has been approached with several standards and protocols implemented in numerous enterprise information systems. The application like ERP (Enterprise Resource Planning), CRM (Customer Relationship Management), and WMS (Warehouse Management System) contains valuable data that can be utilized by the decision support systems (DSS), however, information integration problems often exist. Specifically, this problem is often attributed to heterogeneous hardware, different data formats, and pressure to improve a system’s performance, as shown in Figure 2. The problem with information interchange is related to issues of data exchange between business-partners operating independently-designed information systems. From a logistics point of view the key issues in Supply Chain Visibility (SCV) is the ability of parts, components or products in transit to be tracked from the manufacturer to their final destination, and traced from the customer to the manufacturer.
Figure 2. Heterogeneous data sources in a global supply chain
Key Terms in this Chapter
Resource Description Framework (RDF): The RDF is a standard for representing knowledge on the web. It is primarily designed for building the semantic web and has been widely adopted in database and datamining communities. RDF models a fact as a triple which consists of a subject (s), a predicate (p), and an object (o).
XML: Extensible markup language (XML) is a simple, very flexible text format derived from SGML (standard generalized markup language). While XML was originally designed to meet the challenges of large-scale electronic publishing, it plays an increasingly significant role in the exchange of a wide variety of data on the web.
Relational Database: Relational database systems support processing of tuples of relations to generate a single result as a set of tuples. Relational algebra, relational calculus and structured query language (SQL) are used to specify queries on relational databases.
SPARQL: The SPARQL query language is a structured language for querying RDF data in a declarative fashion. Its core function is subgraph pattern matching, which corresponds to finding all graph homomorphism in the data graph for a query graph.
Ontology: Information sharing among supply chain business partners using information systems is an important enabler for supply chain management. There are diverse types of data to be shared across supply chain, namely order, inventory, shipment, and customer service. Consequently, information about these issues needs to be shared in order to achieve efficiency and effectiveness in supply chain management. In this way, information-sharing activities require that human and/or machine agents agree on common and explicit business-related concepts (the shared conceptualization among hardware/software agents customers, and service providers) are known as explicit ontologies; and this help to exchange data and derived knowledge out of the data to achieve collaborative goals of business operations.
SPARQL Query: A SPARQL query usually contains a set of triple patterns, much like RDF triples, except that any of the subject, predicate and object may be a variable, whose bindings are to be found in the RDF data.
Linked Data: An approach taken to linking data such that it becomes more useful/accessible than it would be in isolation.
Supply Chain Management: A supply chain consists of a network of key business processes and facilities, involving end users and suppliers that provide products, services, and information. In this chain management, improving the efficiency of the overall chain is an influential factor; and it needs at least four important strategic issues to be considered: supply chain network design, capacity planning, risk assessment and management, and performances monitoring and measurement. Moreover, the details break down of these issues need to consider in the level of individual business processes and sub-processes; and the combined performance of this chain. The coordination of these huge business processes and their performance improvement are the main objectives of a supply chain management system.
SQL: Structured query language (SQL) – a commonly-used language for querying relational database systems.
Structured Data: Data are stored in accordance with a strict schema for database management purpose.