Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences

CAiSE Radar 2016

The CAiSE Radar is an experimental format, established for CAiSE 2016, to make CAiSE workshops livelier, exciting, stimulate discussions, and attract additional active participants by establishing an environment where not only well established and validated research is reported but research in infancy, new ideas, and potentially interesting research projects can be presented and discussed. So similarly to a radar, the idea is to enable researchers to look into the future of the field and identify upcoming trends early. The aim of such effort is on one hand to contribute to the building of research communities and promote the integration of young researchers into the community, and on the other hand to provide opportunities to discuss ideas early and to receive additional opinions on planned research

From Information Overload to Knowledge Graphs: An Automatic Information Process Model

Continuously increasing text data such as news, articles, and scientific papers from the Internet have caused the information overload problem. Collecting valuable information as well as coding the information efficiently from enormous amounts of unstructured textual information becomes a big challenge in the information explosion age. Although many solutions and methods have been developed to reduce information overload, such as the deduction of duplicated information, the adoption of personal information management strategies, and so on, most of the existing methods only partially solve the problem. What’s more, many existing solutions are out of date and not compatible with the rapid development of new modern technology techniques. Thus, an effective and efficient approach with new modern IT (Information Technology) techniques that can collect valuable information and extract high-quality information has become urgent and critical for many researchers in the information overload age. Based on the principles of Design Science Theory, the paper presents a novel approach to tackle information overload issues. The proposed solution is an automated information process model that employs advanced IT techniques such as web scraping, natural language processing, and knowledge graphs. The model can automatically process the full cycle of information flow, from information Search to information Collection, Information Extraction, and Information Visualization, making it a comprehensive and intelligent information process tool. The paper presents the model capability to gather critical information and convert unstructured text data into a structured data model with greater efficiency and effectiveness. In addition, the paper presents multiple use cases to validate the feasibility and practicality of the model. Furthermore, the paper also performed both quantitative and qualitative evaluation processes to assess its effectiveness. The results indicate that the proposed model significantly reduces the information overload and is valuable for both academic and real-world research

CAiSE Radar 2016

The CAiSE Radar is an experimental format, established for CAiSE 2016, to make CAiSE workshops livelier, exciting, stimulate discussions, and attract additional active participants by establishing an environment where not only well established and validated research is reported but research in infancy, new ideas, and potentially interesting research projects can be presented and discussed. So similarly to a radar, the idea is to enable researchers to look into the future of the field and identify upcoming trends early. The aim of such effort is on one hand to contribute to the building of research communities and promote the integration of young researchers into the community, and on the other hand to provide opportunities to discuss ideas early and to receive additional opinions on planned research

A Semantic Wiki-based Platform for IT Service Management

The book researches the use of a semantic wiki in the area of IT Service Management within the IT department of an SME. An emphasis of the book lies in the design and prototypical implementation of tools for the integration of ITSM-relevant information into the semantic wiki, as well as tools for interactions between the wiki and external programs. The result of the book is a platform for agile, semantic wiki-based ITSM for IT administration teams of SMEs

ID5.2 Roadmap for KRSM RTD

Roadmap for KRSM RTD activities.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

Knowledge visualizations: a tool to achieve optimized operational decision making and data integration

The overabundance of data created by modern information systems (IS) has led to a breakdown in cognitive decision-making. Without authoritative source data, commanders’ decision-making processes are hindered as they attempt to paint an accurate shared operational picture (SOP). Further impeding the decision-making process is the lack of proper interface interaction to provide a visualization that aids in the extraction of the most relevant and accurate data. Utilizing the DSS to present visualizations based on OLAP cube integrated data allow decision-makers to rapidly glean information and build their situation awareness (SA). This yields a competitive advantage to the organization while in garrison or in combat. Additionally, OLAP cube data integration enables analysis to be performed on an organization’s data-flows. This analysis is used to identify the critical path of data throughout the organization. Linking a decision-maker to the authoritative data along this critical path eliminates the many decision layers in a hierarchal command structure that can introduce latency or error into the decision-making process. Furthermore, the organization has an integrated SOP from which to rapidly build SA, and make effective and efficient decisions.http://archive.org/details/knowledgevisuali1094545877Outstanding ThesisOutstanding ThesisMajor, United States Marine CorpsCaptain, United States Marine CorpsApproved for public release; distribution is unlimited