Presented at the 2017 International Conference on Knowledge Management. This presentation explores the Trusted Repository Audit and Checklist through the lens of contextual dimensions within knowledge management, using the case study of the University of North Texas Libraries.

This paper shows a model used in domain knowledge organization and utilization.

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This poster highlights the qualitative study which was conducted in a major regional hospital in Germany, using the FRAM to analyze the recurrent and complex process of surgical care preparation in the morning. The aim was to offer the hospital a detailed qualitative analysis to promote resilience and maintain a safe state of operating during this process. The FRAM illustrated relevant system functions and unveiled sources as well as effects or variabilities that are now in the process of being evaluated according to appropriate goals and values. In this way, the FRAM illuminates hidden but relevant knowledge, so to speak tacit knowledge, within a complex sociotechnical system that is difficult or impossible to identify otherwise.

Risk management is generally characterized by identification, assessment, and mitigation. In the literature on knowledge risk management (KRM), there appears to be much emphasis on taxonomies - which primarily focus on identification - and mitigation strategies, without particular attention to the evaluation phase of KRM. To address this gap, the present paper aims to systematically evaluate potential knowledge risks common at the operational level of small and medium-sized enterprises (SMEs). More significantly, in SMEs, due to their flat structure, the majority of risk is borne by operational functions. This study adopts a quantitative approach by utilizing the grey-DEMATEL technique. The results of this study reveal outsourcing risks are the most critical of all operational knowledge risks followed by communication risks and improper knowledge application. Furthermore, it is observed the risks could be categorized into effect-risk (e.g. relational risk, espionage knowledge waste, continuity risk) and cause-risk (e.g. knowledge waste, risks related to knowledge gaps, risk of using obsolete/unreliable knowledge)

In Nova Scotia, the marginalization of African Nova Scotian learners in the public education system has led to an achievement gap, where their performance in terms of literacy and numeracy in annual assessments is often below the provincial average. This research aims to use machine learning to analyze student data collected by the Nova Scotia Department of Education and Early Childhood Development to provide evidence-driven insights into the schooling outcomes of African Nova Scotian students. We expect that these insights would enable the development of an equitable education system where African Nova Scotian students are able to achieve their maximum potential and overcome the barriers that they face at school. Through collaboration with the Regional Centers of Education, the Nova Scotia Department of Education and Early Childhood Development has been collecting data to track students’ education experiences. We aim to analyze this data using machine learning algorithms to identify learning patterns and promising school characteristics that would provide an understanding of how we can reduce the achievement gap that exists among African Nova Scotian students.

Organizations struggle to harness tacit knowledge – the knowledge that resides in the heads of knowledge workers, whereas there are always opportunities to capture knowledge during project management activities. Using a literature review, this paper analyzes how knowledge can be captured during different project management phases. It attempts to bridge frequently ignored areas of project management, knowledge management, and analytics.

Conference abstracts and project reports can be a valuable source for access to information on possible risks or experiences to build on. However, these collections are often not accessible in a convenient manner. This work explores the usage of knowledge graphs to support document discovery with an automated indexing approach. Therefore, an RDF/SKOS graph is built, consisting of nearly 1400 tagging labels manually extracted from literature on knowledge graphs and organized in a thesaurus structure. The feasibility is demonstrated with a small collection of texts from the domain of library IT. The graph is published online for further use (cf. https://w3id.org/kgcm/ ). This method may be usable to explore other knowledge domains. On the other hand, the graph-building process is both intellectually and technically demanding and needs support by an interplay of cooperative and mechanical processes in the future.

Text summary has become a vital and more popular domain to preserve and highlight the core purpose of textual information as the amount of online information and resource texts has grown. Text summarization is the task of extracting key information from a text document. Text summarizing research in Afaan Oromoo is still rare and hasn't been thoroughly assessed. This study's primary goal was to evaluate the performance and method of extractive models on automatic extractive text summarization for Afaan Oromoo. Automatic Text summarization approaches can be classified as extractive or abstractive. Automatic abstractive text summarization was not included in this study. Existing automatic extractive text summarizing algorithms take key sentences from the source manuscript and provide a summary without changing the data. This paper examined and assessed some studies on the Afaan Oromoo Language Text Summarization system with a focus on methods and performance. In addition, the automatic extractive text summarization domain's challenges in Afaan Oromoo’s were also discussed. This paper used a systematic literature review method to examine the most recent literature in automatic extractive text summarization as it relates to the Afaan Oromoo language. We used a search engine, Google Scholar, ResearchGate, CiteseerX, peer-reviewed papers, and Academia to …

Poster for the 2017 International Conference on Knowledge Management. This poster discusses data sharing practices and compliance with open data mandates by using the Nonaka and Takeuchi (1995) knowledge transfer spiral model to understand behaviors and create resources for researchers.

Poster paper for the 2017 International Conference on Knowledge Management. This paper discusses data sharing practices and compliance with open data mandates by using the Nonaka and Takeuchi (1995) knowledge transfer spiral model to understand behaviors and create resources for researchers.

This pilot study extends nursing’s historical efforts to prevent medication errors by using a database research approach to better understand why medication errors persist in acute care settings. The pilot study was conducted 3 units and float pool nurses. Data were analyzed using descriptive statistics and multilevel regression modeling.

This paper presents the first results from an analysis of recent job advertisements from online platforms from English and German-speaking countries. The full texts of about 4100 job adverts carrying the terms “knowledge manager” or “knowledge management” either in in the job title or in the short description have been analyzed. The main research aim was to identify the most common KM job titles, providing a basis for further analysis of tasks and required competencies to compare the data samples. In particular, the research will address the following research questions: RQ1: What are the job titles used in job adverts related to KM? RQ2: Which tasks are mainly associated with different KM job titles (roles)? RQ3: Which competencies & skill sets are typically required in job adverts? This research inform KM practitioners and HR managers as well as the KM community about landscape of KM roles, main tasks and skills required on the labor markets in the German-speaking (AU, CH, DE) countries and three English-speaking (AUS, UK, USA) countries.

Juliane Dieckmann, Head of Knowledge Management in the Otto Group Holding, is responsible in the Digital & Consulting division for the group-wide transfer of knowledge and the development of KM products specifically aimed at collaboration in organisational units. She focuses with continuing enthusiasm on the task of making Knowledge Management in the Otto Group fit for the path to digital transformation and putting people at the centre of this. The Otto Group is a globally active trading and services group with around 52,000 employees and a turnover of 15.6 billion euros. With 30 major corporate groups it is present in more than 30 countries. Global group activities and strategic partnerships provide the Otto Group with excellent conditions for know-how transfer and the use of synergy potential. Every day, in the course of its business activities, it deals with the core issues of a modern society, including the future of work, value-oriented action, and the opportunities and challenges of the present.

We discuss the engineering of so-called ‘humanoid’ socio-technical settings mimicking cognitive and social skills. We discuss the influence of Artificial Intelligence (AI) on digital selves. We introduce relevant approaches to awareness and the emergence of consciousness in artificial agents. We define mandatory properties of digital selves so that digital societies can be modeled and we present our thoughts on the role of KM in a trans-humanist world.

Presented at the 2017 International Conference on Knowledge Management. This poster demonstrates the utility of text analytic for theory building and validation in information science.

Poster paper for the 2017 International Conference on Knowledge Management. This paper demonstrates the utility of text analytic for theory building and validation in information science.

Twitter is one of the major social media platforms highlighting public opinion. With over 330 million users across the globe, Twitter provides insights into global sentiments on many topics. One can estimate global sentiments towards certain events relating to COVID-19 by analyzing the most common phrases and their related sentiment scores from Twitter API data. This project has compiled the most used trigrams in tweets relating to COVID-19 to calculate sentiment scores for the period from March 22 to August 7, 2020. Another goal of the project is to optimize data collection from Twitter API. Twitter limits access to tweet contents to 900 requests per 15 minutes for unpaid API users. For student data scientists, paying for increased API usage is financially infeasible. So, to deal with the rate limit, the project has written functions using the Tweepy python library to collect Twitter API data. The Pandas library has also been used to sample 139000 tweets from over 300 million. The IEEE Dataset provided sentiment scores for the full population. So, to check the integrity of my sample, I performed a Pearson correlation test between the full dataset and sample data, and got 0.84, showing the sample is representative of …

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. Since the conference was among the first post-pandemic face to face conferences, the overall theme of the 17th edition of the ICKM conference rightly focused on “Knowledge, Uncertainty and Risks: From individual to global scale” at different levels of analysis and agency. This document highlighted one of the posters that focuses on health despairities and how ethnicity is remarkably correlated to one’s health.

Presented at the 2017 International Conference on Knowledge Management. This presentation discusses unofficial music records, and how they have been classified and archived.

Knowledge is the central component of knowledge management (KM); it comes into existence, is managed, and has effects through the activities performed upon it and the results of those activities. Much of the foundational KM literature identifies and classifies these activities (Baskerville, Dulipovici, 2006; Becerra-Fernandez, 2005; Evans, Ali, 2013; Evans, Dalkir, Bidian, 2014; Girard, Girard, 2015; Pee, Kankanhalli, 2009; Mohajan, 2016; Sajeva, 2010). We propose an extension of these activity classifications.

This is the final program for the 2017 International Conference on Knowledge Management.

Presentation for the 2017 International Conference on Knowledge Management. This presentation presents some results of a content analysis study that explores the state of implementation of the Resource Description and Access (RDA) standard in authority records.

While explicit knowledge can be to some extent separated from human brain and stored in organizational memory, tacit knowledge cannot be detached from the individuals who possess it, therefore its management cannot rely primarily on technologies. This calls for knowledge-worker centered approach. Individuals with different cognitive styles process information differently and use a variety of reasoning patterns for decision making and building their personal knowledge bases. The paper overviews the potential applications of the construct of cognitive style to managerial practice in knowledge intensive organizations. It also presents a model that can help visualize the relationships between different cognitive styles and knowledge management processes. The model also demonstrates how such cognitive dimensions manifest themselves at different stages of KM cycle.

Cyber addiction refers to the excessive use of internet and cyber application leading to adverse outcomes such as stress, distractions, reduced motivation levels, and challenges in task orientation. Uncontrolled consumption of the internet leads to information overload that impact productivity and workplace performance (Griffiths, 2010). In such cases, the ubiquitous availability of information can lead to IT-related stress where users derive a reduced sense of satisfaction (Diomidous et al. 2016). People who frequently access the internet can experience various issues, which encompass anxiety, depression, and self-image challenges. Physically, affected individuals experience disrupted sleep patterns, irritability and high levels of fatigue. Social networking sites increase the risk of addiction and online dependency, aspects associated with low levels of productivity (Hoq, 2014). As illustrated in fig 1, the paper hypothesizes that there is a direct relationship between information overload and workplace performance and job satisfaction. The assumption is that cyber addiction worsens the problem of information overload, which in return, impacts information behavior and use and workplace/job performance (Riaz & Qureshi, 2019). The study addresses the following research questions: What is the impact of cyber addiction on workplace performance? What are the relationships between cyber addiction, information workload and information behavior and …