Semantic Web: A road to the knowledge infrastructure on the internet

In this article, I describe the basic technologies for Semantic Web and relationship between Semantic Web and Knowledge Representation in Artificial Intelligence. Semantic Web is planned as an extension of the current web in order to help cooperation between computers and humans, i.e., computers and humans are expected to understand each other in the knowledge level. I first describe the vision of the Semantic Web, then introduce the current Semantic Web technologies, i.e., RDF, RDFS, and OWL. I describe relationship between the trend of Semantic Web and Knowledge Representation, and clarify challenges and difficulties of Semantic Web from the point of view of Knowledge Representation. Hideaki Takeda: He is a professor at National Institute of Informatics (NII) and a professor in Department of Informatics at the Graduate University of Advanced Studies (Sokendai). He received his Ph.D. from the University of Tokyo in 1991. His research interest in computer science includes ontology engineering, community informatics and knowledge sharing systems.     

A collaborative methodology for tacit knowledge management: Application to scientific research

Tacit knowledge, which refers to the know-how, is critical to understand and reuse since it is located in the human heads. It represents the foremost element for human and team evaluation. Seeking for tacit knowledge is achieved only by communicating with the concerned persons, which makes losing it axiomatic if people leave their work without documenting their know-how. Thus, providing a collaborative environment based on a common conceptualization of the domain to formalize the experts’ knowledge and to share their outcomes is required. However, some barriers pertaining to cultural and social factors such as personality traits impede capturing the conceptual model. To cope with these issues, we have proposed a generic two-step methodology that copes with human barriers when capturing the domain experts’ tacit knowledge, their skills, and seeds terms in order to converge to a common knowledge representation. Considering the scientific research management as a use case, we followed the proposed methodology to formalize our scientific research knowledge in the context of network and communication research field. Based on the generated ontology, we have developed a semantic web platform that allows collaboratively annotating experts’ knowledge in a computer interpretable format that can be shared and reused by human and machines. Our evaluation is based on end users’ quality of experience and feedbacks.     

Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs

Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF), has garnered significant attention as it can bring quality information into the digital thread. Implementing more automated methods for product quality assurance is challenging due to the lack of unified information models from design to inspection. To this end, we propose an approach to fuse as-designed data represented in STEP and as-inspected data represented in QIF in a standards-based digital thread based on ontology with knowledge graphs. Specifically, we present an automated pipeline for generating knowledge graphs representing STEP and QIF data, a mapping implementation to integrate STEP and QIF knowledge graphs, and rules and queries to demonstrate the integration’s potential for better decision making with respect to product quality assurance.     

A cooperative tool for facilitating knowledge management

Nowadays, we can find systems and environments supporting processes of ontology building. However, these processes have not been specified enough yet. In this work, a real environment for integrating ontologies supplied by a predetermined set of (experts) users, who might be distributed through a communication network and working cooperatively in the integration process, is introduced. In this environment, the (expert) user can check for the ontology that is being produced, so he/she is able to refine his/her private ontology. Furthermore, the experts who take part of the ontology construction process are allowed to use their own terminology even for requesting information about the global-derived ontology until a specific instant after the integration.     

High Performance Knowledge Bases: four approaches to knowledge acquisition, representation and reasoning for workaround planning

As part of the DARPA-sponsored High Performance Knowledge Bases program, four organisations were set the challenge of solving a selection of knowledge-based planning problems in a particular domain, and then modifying their systems quickly to solve further problems in the same domain. The aim of the exercise was to test the claim that, with the latest AI technology, large knowledge bases can be built quickly and efficiently. The domain chosen was ‘workarounds’; that is, planning how a convoy of military vehicles can ‘work around’ (i.e. circumvent or overcome) obstacles in their path, such as blown bridges or minefields.

This paper describes the four approaches that were applied to solve this problem. These approaches differed in their approach to knowledge acquisition, in their ontology, and in their reasoning. All four approaches are described and compared against each other. The paper concludes by reporting the results of an evaluation that was carried out by the HPKB program to determine the capability of each of these approaches.     

Exploring the boundaries and processes of digital platforms for knowledge work: A review of information systems research

Digital platforms for knowledge work (DPKW), such as Upwork, Freelancer, and Fiverr, connect clients with millions of workers for a range of knowledge work services, including app development, graphic design, and data analytics. Research on this emergent phenomenon has recently gained traction in terms of publication volume and research diversity. Focusing on the contributions of information systems research, we conducted a literature review to distinguish papers on DPKW from related types of digital platforms, to synthesize what we know about knowledge work on DPKW, and to guide future research. Based on a comprehensive literature search, we derived five boundary conditions, which constitute our definition of DPKW: digitality, value network paradigm, centralized governance, contractual work, and knowledge work. We further developed a conceptual process framework of the constituent processes of DPKW. With this framework, we elaborate on an established process model to distinguish the three macro­level processes of matching, contracting, and executing. We further examined micro­level processes suggested in extant research based on a process linking approach in order to understand how they synchronically instantiate each macro­level process. Emphasizing the significance of the micro­ and macro­level processes and the emergent stage of the literature on DPKW, we offer an agenda for future research and outline implications for practice.     

Newsmap: a knowledge map for online news

Information technology has made possible the capture and accessing of a large number of data and knowledge bases, which in turn has brought about the problem of information overload. Text mining to turn textual information into knowledge has become a very active research area, but much of the research remains restricted to the English language. Due to the differences in linguistic characteristics and methods of natural language processing, many existing text analysis approaches have yet to be shown to be useful for the Chinese language. This research focuses on the automatic generation of a hierarchical knowledge map NewsMap, based on online Chinese news, particularly the finance and health sections. Whether in print or online, news still represents one important knowledge source that people produce and consume on a daily basis. The hierarchical knowledge map can be used as a tool for browsing business intelligence and medical knowledge hidden in news articles. In order to assess the quality of the map, an empirical study was conducted which shows that the categories of the hierarchical knowledge map generated by NewsMap are better than those generated by regular news readers, both in terms of recall and precision, on the sub-level categories but not on the top-level categories. NewsMap employs an improved interface combining a 1D alphabetical hierarchical list and a 2D Self-Organizing Map (SOM) island display. Another empirical study compared the two visualization displays and found that users' performances can be improved by taking advantage of the visual cues of the 2D SOM display.     

Reconceptualizing knowledge networks for enterprise systems implementation: incorporating domain expertise of knowledge sources and knowledge flow intensity

Research on knowledge acquisition through informal social networks during enterprise system implementation has not accounted for the domain expertise of knowledge sources or the quality of knowledge flows. By using data collected from an enterprise resource planning system implementation, this paper reconceptualizes knowledge networks into subnetworks on the basis of the domain expertise of end users and analyzes knowledge acquisition patterns between subnetworks across workgroups having varying performance outcomes. Expertise-based knowledge patterns and their intensities had significant implications for performance outcomes, reiterating their role in the learning process and emphasizing the need to incorporate them into knowledge networking models.     

Action research and knowledge co-generation: a not so dangerous liaison with conventional social research

The article reflects on experience of action research in the context of regional development, where there has been pressure to produce practical results. The epistemological status of Action Research is explored, in contrast to conventional social science research. The article concludes that an ongoing relationship with conventional social research is necessary.An earlier version of this paper has been presented at the workshop: Innovation and Regional Development Kingston University 10th December 2004     

Training individuals for distributed teams: problem solving assessment for distributed mission research

In this paper we describe an effort investigating the feasibility and utility of cognitively diagnostic assessment of problem solving when training for distributed team tasks. We utilized computer-based knowledge elicitation methods to assess both relational problem solving, requiring the semantic integration of concepts, and dynamic problem solving, requiring the ability to integrate and apply these concepts. Additionally, we addressed how metacognitive processes interact with learning outcomes when training for complex synthetic task environments. We find first, that multiple methods of assessing problem solving performance are diagnostic of knowledge acquisition for a complex synthetic team task, and second, that general metacomprehension predisposition is related to metacomprehension accuracy in synthetic task environments.     

A flexible architecture for distributed knowledge based systems with nomadic access through handheld devices

Nowadays any Knowledge Based System (KBS) realization needs of intercommunication among distributed components and to use non-connected and distributed data sources, which poses several challenges to the classical Artificial Intelligence field of KBS.

The multiagent paradigm and the use of ontologies are considered to be suitable tools to face the problems of designing and developing today KBS. On the other hand, using such networked KBS through handheld devices makes more efficient exploitation and interaction with the system.

This paper presents an open and flexible architecture for a distributed KBS and an application of it to construct a system for Psychological Disorders consulting, the so called PDA² (Psychological Disorder Assistant through PDA). We analyze the main features of the architecture as well as the agent tools we may use to construct it. Additionally, we present a support ontology for Psychological Disorders.     

Special knowledge sharing incentive mechanism for two clients with complementary knowledge: A principal-agent perspective

In this paper, we study how the firm share the special knowledge of two knowledge-complementarity clients by implementing a large and complex project which the firm out-sourced. Firstly, incentive mechanism for complementarity special knowledge sharing are designed for clients being risk-neutral and risk-averse respectively under the asymmetric information. Further, knowledge complementary effects and other relevant factors on the optimal incentive coefficient are analyzed. Lastly, the numerical results are reported.     

DILIGENT: integrating digital library and Grid technologies for a new Earth observation research infrastructure

This paper introduces DILIGENT, a digital library infrastructure built by integrating digital library and Grid technologies and resources. This infrastructure allows different communities to dynamically build specialised digital libraries capable to support the entire e-Science knowledge production and consumption life-cycle by using shared computing, storage, content, and application resources. The paper presents some of the main software services that implement the DILIGENT system. Moreover, it exemplifies the provided features by presenting how the DILIGENT infrastructure is being exploited in supporting the activity of user communities working in the Earth Science Environmental sector. This work is partially funded by the European Commission in the context of the DILIGENT project, under the 2nd call of FP6 IST priority.     

Envisioning entrepreneurship and digital innovation through a design science research lens: A matrix approach

Design Science Research (DSR) in the information systems (IS) field is, at its essence, about Digital Innovation (DI). Innovative sociotechnical design artifacts involve digital information technologies (IT) being used in ways that result in profound disruptions to traditional ways of doing business and to widespread societal changes. The pervasiveness of DI means that the individuals involved in bringing it about have diverse backgrounds, including application specialists, software engineers, data scientists, business managers, economists, venture capitalists, various user groups, and entrepreneurial leaders. This range of backgrounds means that DI, much more than traditional innovation, leads to varied perspectives on the methods and tools to be used in the development of effective and evolvable complex systems incorporating digital innovations. In this paper we present a new matrix approach to DI based on DSR, entrepreneurship, and innovation theories. Clear strategic guidance allows these multiple stakeholders to make sense of the diverse landscape and to understand when and how different entrepreneurial strategies for innovation can best be applied. We define the combined DSR and DI matrix approach in terms of four strategies: invention; advancement; exaptation; and exploitation and their associated DI practices. The research contribution is a novel DSR-DI matrix process model. This model extends entrepreneurship theory as it enriches effectuation thinking with more detailed process guidance for ambidextrous entrepreneurship and it enriches DSR models for DI by showing more explicitly the different pathways corresponding to different quadrants in the knowledge-innovation matrix.     

Relationship bonding for a better knowledge transfer climate: An ERP implementation research

While prior studies on ERP implementation have largely focused on the importance of best practices, the purpose of this paper is to examine the impact of the knowledge transfer climate and relationship bonding. The model categorizes the factors that influence the result of knowledge transfer during ERP implementation into three types: those implemented by the firm, those implemented by the consultant, and those related to the impact of the knowledge transfer climate. The bonding factors from the two former aspects facilitate the building of a better knowledge transfer climate. A total of 174 respondents are surveyed with results subjected to multivariate analysis. The significance of bonding factors is verified, and the role that the knowledge transfer climate plays in the knowledge transfer process and the impact on the transfer process are developed. This paper provides a broader, richer model of knowledge transfer networks to promote insight into successful ERP implementation. In practice, the key to effective knowledge transfer is the establishment of a positive knowledge transfer climate. To achieve a successful ERP implementation, practitioners should focus on developing a positive relationship with ERP implementation partners.     

Two approaches to selecting set of voxels for the diagnosis of Alzheimer?s disease using brain SPECT images

This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The first proposed methodology is based on the selection of those voxels which present a greater difference between Controls and Alzheimer type dementia patients. The mean value of the intensities of the selected voxels is used as features for different classifiers. The proposed methodology reaches an accuracy of 89% in the classification task. A second criterion is chosen to select voxels based on considering those which present not only greater overall difference between both modalities (Controls and Alzheimer) but also present lower dispersion. The classification accuracy using this second condition increases to 94%.     

A procedural framework for dynamic changes of human interactions in knowledge intensive services

The knowledge intensive service processes should be managed in a human-oriented way since humans who naturally undertake complex operations of an intellectual nature in the processes are the most valuable resources. The most fundamental nature of human work is collaborative and dynamic. Humans interact and communicate with each other to accomplish their jobs in the process. To help them to work together, a strong representation of the process should be provided to facilitate them to clearly understand who they should interact with and what activities need to be performed. For the clear representation, Human Interaction Management (HIM), which has been suggested to comprehensively support human work, adopts a role-based approach to process modeling. It, however, tends to hide elements of interactions although the collaborative human interaction is one of the most fundamental nature of human work. To remedy this problem, a state-driven modeling approach to human interactions was presented. It clearly visualizes the interactions so that humans can be guided through it. However, they do not just follow the previously defined sequence of activities, but continuously work out how they are going to proceed from now on according to the state of things they encounter throughout the life of the work. To fully support the dynamic nature of human work, human interactions should be flexibly managed. Therefore, this paper presents a framework for the flexible management of human interactions. The framework provides a capability to flexibly manage the interactions in a decentralized way by allowing interaction participants to dynamically change the involved interaction based on the continuous negotiation of how to achieve the ultimate goal of the interaction. It will be a basis for realization of decentralized management of human interactions in knowledge intensive service processes.     

SemWebDL: A privacy-preserving Semantic Web infrastructure for digital libraries

Recent advances in digital libraries have been closely intertwined with advances in Internet technologies. With the advent of the Web, digital libraries have been able to reach constituencies previously unanticipated. Because of the wide deployability of Web-accessible digital libraries, the potential for privacy violations has also grown tremendously. The much touted Semantic Web, with its agent, service, and ontology technologies, is slated to take the Web to another qualitative level in advances. Unfortunately, these advances may also open doors for privacy violations in ways never seen before. We propose a Semantic Web infrastructure, called SemWebDL, that enables the dynamic composition of disparate and autonomous digital libraries while preserving user privacy. In the proposed infrastructure, users will be able to pose more qualitative queries that may require the ad hoc collaboration of multiple digital libraries. In addition to the Semantic Web-based infrastructure, the quality of the response would rest on extraneous information in the form of a profile. We introduce the concept of communities to enable subject-based cooperation and search speedup. Further, digital libraries heterogeneity and autonomy are transcended by a layered Web-service-based infrastructure. Semantic Web-based digital library providers would advertise to Web services, which in turn are organized in communities accessed by users. For the purpose of privacy preservation, we devise a three-tier privacy model consisting of user privacy, Web service privacy, and digital library privacy that offers autonomy of perspectives for privacy definition and violation. We propose an approach that seamlessly interoperates with potentially conflicting privacy definitions and policies at the different levels of the Semantic Web-based infrastructure. A key aspect in the approach is the use of reputations for outsourcing Web services. A Web service reputation is associated with its behavior with regard to privacy preservation. We developed a technique that uses attribute ontologies and information flow difference to collect, evaluate, and disseminate the reputation of Web services.     

FarsBase-KBP: A knowledge base population system for the Persian Knowledge Graph

While most of the knowledge bases already support the English language, there is only one knowledge base for the Persian language, known as FarsBase, which is automatically created via semi-structured web information. Unlike English knowledge bases such as Wikidata, which have tremendous community support, the population of a knowledge base like FarsBase must rely on automatically extracted knowledge. Knowledge base population can let FarsBase keep growing in size, as the system continues working. In this paper, we present a knowledge base population system for the Persian language, which extracts knowledge from unlabelled raw text, crawled from the Web. The proposed system consists of a set of state-of-the-art modules such as an entity linking module as well as information and relation extraction modules designed for FarsBase. Moreover, a canonicalization system is introduced to link extracted relations to FarsBase properties. Then, the system uses knowledge fusion techniques with minimal intervention of human experts to integrate and filter the proper knowledge instances, extracted by each module. To evaluate the performance of the presented knowledge base population system, we present the first gold dataset for benchmarking knowledge base population in the Persian language, which consisting of 22015 FarsBase triples and verified by human experts. The evaluation results demonstrate the efficiency of the proposed system.     

Internet-based manufacturing: A review and a new infrastructure for distributed intelligent manufacturing

Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing enterprises. Traditional centralized manufacturing systems are not able to meet these requirements. In recent years, the internet has become the worldwide information platform for the sharing of information and data. Information processing is an important challenge in an internet-based manufacturing environment, and must facilitate distribution, heterogeneity, autonomy and cooperation. This paper reviews recent trends and major developments in internet-based manufacturing. Broad categories of distributed information management are identified, based upon the development of computer integrated manufacturing, and the possible direction of future research is indicated.