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Quality management systems are commonly applied to meet the increasingly stringent requirements for product quality in discrete manufacturing industries. However, traditional experience-driven quality management methods are incapable of handling heterogeneous data from multiple sources, leading to information islands. This study aims to present a quality management key performance indicator visualization (QM-KPIVIS) system to enable integrated quality control and ultimately ensure product quality.

Based on multiple heterogeneous data, an integrated approach is proposed to quantify explicitly the relationship between Internet of Things data and product quality. Specifically, this study identifies the tracing path of quality problems based on multiple heterogeneous quality information tree. In addition, a hierarchical analysis approach is adopted to calculate the key performance indicators of quality influencing factors in the quality control process.

Proposed QM-KPIVIS system consists of data visualization, quality problem processing, quality optimization and user rights management modules, which perform in a well-coordinated manner. An empirical study was also conducted to validate the effectiveness of proposed system.

To the best of the authors’ knowledge, this study is the first attempt to use industrial Internet of Things and multisource heterogeneous data for integrated product quality management. Proposed approach is more user-friendly and intuitive compared to traditional empirically driven quality management methods and has been initially applied in the manufacturing industry.

The purpose of this paper is to improve the existing paradigm of edge computing to maintain a balanced energy usage.

The new greedy algorithm is proposed to balance the energy consumption in edge computing.

The new greedy algorithm can balance energy more efficiently than the random approach by an average of 66.59 percent.

The results are shown in this paper which are better as compared to existing algorithms.

Leading-edge information and communication technology provides the base to facilitate obtaining, interoperating and federating shared metadata knowledge in collaborative networks from multiple heterogeneous data sources. The purpose of this study is to develop a methodology and a set of mechanisms to support this task in the collaborative environment.

In this paper, the authors first identify and capture four main typical sources to find or generate metadata knowledge for shared data in emerging networked environments, including existing well-designed metadata, the typical ones are relational schemas of existing databases in the environment; fragmented metadata sources, i.e. metadata that can be realized from existing mission statements and example application scenarios in the environment, usually characterized by their fragmented, lightweight and behavior-intensive features; extracting metadata for simple labeled unstructured data, e.g. textual communications among its stakeholders; and semantic constraints on metadata, e.g. the temporal data behavior could be generated from governance policies in the environment. Second, the authors introduce their systematic methodology to the unification of the resulted metadata consisting of four semiautomated unification steps that gradually develops and enhances a unified ontology for the environment, formalized in web ontology language.

The methodology steps and their corresponding mechanisms are described and exemplified in detail in this paper. Furthermore, this paper presents the outcome of applying the authors’ methodology to an example emerging case through the generation of a unified ontology for that environment.

The addressed example application area is a real case in the field of higher education in China and therefore serves as a proof of concept and verification of the effectiveness of the authors’ proposed approach.

The rapidly emerging of Mobile Internet and the constantly increasing of wireless subscribers' number bring new opportunities and challenges to geographic information sharing and accessing. Current Web GISs, which are accessed by using connection based approaches, are very inefficient in fulfilling the requirements of GIS applications under open, dynamic, heterogeneous and distributed computing environments such as (Mobile) Internet. In this paper, we propose a new system for accessing and sharing distributed geographic information by using mobile agent and GML technologies, in which mobile agents are used to overcome the limitations of traditional distributed computing paradigms in (mobile) Internet context and GML is adopted as the common format for spatial information wrapping and mediation, while SVG is used as a web‐map publishing format that can be processed and displayed in Web browser. A prototype is implemented, which demonstrates the effectiveness and feasibility of the proposed method.

This paper aims to develop a framework to represent semantic web query results as Industry Foundation Class (IFC) building models. The subject of interoperability has received considerable attention in the construction literature in recent years. Given the distributed, semantically heterogeneous data sources, the problem is to retrieve information accurately and with minimal human intervention by considering their semantic descriptions.

This paper provides a framework to translate semantic web query results into the XML representations of IFC schema and data. Using the concepts and relationships in an IFC schema, the authors first develop an ontology to specify an equivalent IFC entity in the query results. Then, a mapping structure is defined and used to translate and fill all query results into an ifcXML document. For query processing, the proposed framework implements a set of predefined query mappings between the source schema and a corresponding IFC output schema. The resulting ifcXML document is validated with an XML schema validating parser and then loaded into a building information modeling (BIM) authoring tool.

The research findings indicate that semantic web technology can be used, accurately and with minimal human intervention, to maintain semantic-level information when transforming information between web-based and BIM formats. The developed framework for representing IFC-compatible outputs allows BIM users to query and access building data at any time over the web from data providers.

Currently, the results of semantic web queries are not supported by BIM authoring tools. Thus, the proposed framework utilizes the capabilities of semantic web and query technologies to transform the query results to an XML representation of IFC data.

Rapid innovation and globalization have generated tremendous opportunities and choices in the marketplace for firms and customers. Competitive pressures have led to sourcing and manufacturing on a global scale resulting in a significant increase in products. The paper tries to identify the need for real time business intelligence (BI) in supply chain analytics.

The paper provides argument and analysis of the advantages and hurdles in BI.

The paper focuses on the necessity to revisit the traditional BI concept that integrates and consolidates information in an organization in order to support firms that are service oriented and seeking customer loyalty and retention. Enhancing effectiveness and efficiency of supply chain analytics using a BI approach is a critical component in a company's ability to achieve its competitive advantage.

This paper furthers understanding of the issues surrounding the use of BI systems in supply chains.

Particular attention to the issue of information management will be required to meet the expected growth in IoT-devices and the data they generate. As government agencies start collecting and using such information, they must also deal with the issue of privacy, to comply with laws and regulations. The approach discussed here shows that record-keeping principles may form part of a solution to the issue of managing IoT-data for government agencies.

This study uses the generally accepted record-keeping principles as a basis for a high-level discussion on how IoT-data can be managed. This is followed by a presentation and discussion on how the Norwegian record-keeping standard, Noark, can be extended to highlight practical issues.

Record keeping has principles that are relevant to the management of IoT-data. Further an implementation of the chosen use-cases is possible based on an existing record keeping standard. Record keeping is one of many information science approaches that can manage IoT-data.

The main limitations are that the discussion cannot cover all types of IoT-devices, nor can all issues be captured with a limited choice of examples. The results should be seen within the context of the types of devices discussed and limited to the chosen use-cases. However, the level of abstraction used means the results may be applicable to similar scenarios.

The approach shows that record-keeping principles may be used as an approach to manage IoT-data. This discussion is useful when compared with other information science approaches, e.g. big-data or semantic Web approaches. The practicalities of a record-keeping approach are also discussed and relevant strengths and weaknesses are showed.

Acme Inc, a large retailer, explores the use of Data warehouse for addressing their decision support infrastructure Challenges. Acme plans for a pilot study to assess the feasibility and evaluate the business benefits of using Data warehouse. The focus of this case is to ascertain the steps involved in design, development and implementation of a Data warehouse.

Contemporary cities are the subject of new forms of visualization that are not only changing how we see the urban world but how it operates as a social environment. This chapter explores Google's Street View database and the Google Maps platform as sites for the production of distinctive new streams of visual data about cities around the world. I argue that this kind of digital infrastructure presents urban researchers with both new opportunities and new challenges, raising complex questions about the role of visual images in the context of the ongoing transition to a digital, computational, and networked image world.

Many organizations in the local community environment use and produce geo‐spatial data, so the need for integration of geo‐data is increasing rapidly. Different user groups have different views of the world and information is available in a heterogeneous format. This paper seeks to discuss the need for interoperability in local communities taking Chittagong city of Bangladesh as an example.

These communities use geo‐spatial data in their own format. This results in semantic conflicts, arising when there is a need for integration of the geo‐spatial data. Consequently, the interaction among the aforesaid organizations in terms of data is difficult to achieve and therefore, it is difficult to share the benefit of the recently evolving Information Technology. Taking the above viewpoint into account, this paper presents a framework to address such semantic data conflicts, considered as an issue of interoperability, using ontology.

This paper presented an ontology‐based architecture which can be used in resolving semantic conflicts, enabling the tackling of the interoperability issue, faced by the various local communities. The proposed architecture will reduce the computational time significantly because it does not require processing each query every timeResearch limitations/implications – The architecture presented needs to test with real data in the near future.

In order to share the geo‐data available in different formats, there is a need for developing a global community, consisting of an integrator, global schema and common ontology.

It has been shown that the architecture allows the sharing of geo‐data by resolving geo‐semantic conflicts of the local communities. This will in turn play an important role in addressing the interoperability problem, faced by these communities.