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.

This paper will report on a research to develop Speaker Independent, Continuous Speech Recognizer for Kafi Noonoo (Afro-Asiatic language that belongs to North Omotic sub family in Ethiopia) using Hidden Markov Modeling technique. The portable and open source toolkit called Hidden Markov Model (HMM) Toolkit is used to perform the experiment. The development of HMM based Automatic Speech Recognition (ASR) requires both text and speech corpus for training and testing the HMM. In order to have a model that incorporates different features of the language, we included the different dialects of Kafi Noonoo in the corpus and then prepared the training and test corpus from the scratch, and after preprocessing we have sampled and performed feature extraction using Mel Frequency Cepstral Coefficients (MFCC) feature extraction technique.

Arising in China in December 2019, the novel coronavirus (COVID-19) soon spread to other countries worldwide including Bangladesh. Mass media and social media platforms played an important role in providing Coronavirus related information and news as they enable people to share news as well as personal experiences with one another rapidly. Since little is known about COVID-19, various fake news spread across social media that panicked people into making panic decisions. The primary objective of this study is to examine how social media is spreading fake or unauthentic news during the time of COVID-19 pandemic. This study also focuses on how the university students of Bangladesh are playing their roles in the spread of fake news in social media. An online survey was conducted to reach a wide number of university students who own at least one social media account. A well-structured questionnaire was designed containing both open and close ended questions. Google forms was used to build the survey instrument. The questionnaire was distributed to the students using different social media platforms. Collected data were analyzed using SPSS version 20 and MS Excel. The study showed that the students sometimes received COVID-19 related fake news. The main reason behind …

The digital age comes with transformational activities (also referred to as digital transformation) triggered by emerging fields and technologies, such as data science and analytics, cybersecurity, cloud computing, blockchain, cryptocurrency, and nanotechnology; helping organizations stay current and competitive. This paper focuses on agile frameworks that support the delivery of data science/analytics projects to ensure organizations rapidly deliver analytics products and services to their customers.

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.

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 …

Presentation paper for the 2017 International Conference on Knowledge Management. This paper uses the Brenda Dervin sense making model to explain human behavior and way of reasoning with making purchasing decisions of smart thermostats.

Presented at the 2017 International Conference on Knowledge Management during the panel session on Big Data, Ethics and Public Engagement. This presentation discusses crowdsourcing information science frameworks.

Trauma, and its associated effects, can be conceptualized as a period of information uncertainty. The natural psychological response to trauma is a period of post-traumatic stress. Trauma occurs when an existing knowledge base has been challenged. Any event that challenges important components of an individual’s assumptive world is said to be traumatic. This post-traumatic period is akin to many theories and concepts in information science including uncertainty reduction, Everyday Life Information Seeking, Sensemaking Theory, Making Meaning and Anomalous States of Knowledge. One possible outcome after the post- traumatic period is post-traumatic growth. Researchers agree post-traumatic growth primarily occurs across one or more of the following domains: personal strength, new possibilities, relating to others, appreciation of life and spiritual change. That is, people affected by trauma tend to grow when they find new or additional paths of information certainty.

This presentation investigates update procedures based on deterministic dynamics for populations arranged in a lattice.

Identifying support from Knowledge Management (KM) frameworks and Risk Management to build collective intelligence for handling systemic crises, triggered by the Corona virus disease 2019 (Covid-19)

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.

Project-based learning (PjBL) allows learners to focus on a topic of their interest and apply the presented and acquired knowledge in their current (work) practice. When applied in institutional contexts, these particularities have to be recognized for stakeholder-centered learning support. In this paper we report on identifying and designing value exchanges between concerned stakeholder groups by methodological deployment of the Value Network Analysis. The individual and collective perception of PjBL experiences could be externalized and design inputs of involved and addressed stakeholder groups could be developed in a non-disruptive way. The results give way for increasing self-efficacy of knowledge acquisition and skill development in (digital) learning environments.

The research seeks to know if the COVID-19 pandemic has created culture change by measuring the criteria of work outputs and actions of organization members. As a part of this research, a survey was developed to identify how and to what extent workplace culture has been impacted. 111 professional services staff from a North Texas business were surveyed. We identified three factors for criteria of work outputs and behavior that indicates the current level of change of the culture. The three factors are identified as, Expectations (α= 0.786), Accuracy (α= 0.603), and Timeliness (α= 0.552). Factor analysis and descriptive statistics are used to analyze the result from the survey.

This presentation considers how knowledge science theories and methods might apply to the original and current Social Informatics challenges.

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

This paper aims to compile organizational innovation management indicators of papers that included some empirical step in the research and were published in the last 5 years (2015-2019). Based on PRISMA protocol, a systematic review was conducted and 356 indicators were extracted. They were categorized in 11 dimensions, following Dziallas & Blind (2019) previous literature research. The results make it possible to update the studies of innovation indicators at the organizational-level, filling an existing time gap in the research field. As for future research, we recommend the unification of similar indicators, the establishment of objective criteria for indicators categorization, and the development of an innovation indicator framework containing relevant indicators based on scholars’ and practitioners’ opinions, their description and measurement/evaluation methods.

The purpose of this research is to explore concept maps as a viable and effective knowledge management tool for cybersecurity education. Concept maps serve as a visual representation of knowledge. They are commonly utilized to support the teaching and learning process or as a student learning evaluation tool. While the focus of education research is on tools specific to cybersecurity such as learning management systems and cyber ranges, there is little dedicated to understanding how concept maps can be applied as an effective element within the security education. This paper reviews relevant research related to the applications of concept maps in diverse knowledge domains. The aim is to leverage previous research applications to garner support for concept maps as a useful knowledge management tool in cybersecurity. This is accomplished by highlighting successful applications of concept maps in related fields. Concept maps are poised to be extremely helpful with complex subjects such as information and cyber security where understanding the subject depends on the application of disparate but interrelated concepts.

Neo-learning was developed as a teaching and learning methodological platform for the Networked Corporate University (NCU) model, in order to promote experiential and expansive learning for the development of competences and facilitate the transfer of learning to work practice. The purpose of this article is to present the neo-learning as a methodological support of the Networked Corporate University model to facilitate the transfer of learning into practice. To achieve this objective, a qualitative approach was chosen for exploratory and descriptive purposes, through a narrative literature review and multiple case studies of the application of the methodology. This article presents the main approaches and theories that underlie the NCU model and the neo-learning methodology. The neo-learning cycle and the applications that validate the methodology are also presented. It is concluded that the neo-learning methodology was developed in accordance with the NCU model to support the teaching and learning processes. The methodology can be considered validated, since it has been applied in several research and extension projects, in academic and corporate, public and private universities, in undergraduate and graduate programs, for initial training, for the developing of teachers and tutors of the presential, online, and remote modalities.

In project-based organizations, knowledge management is becoming a cornerstone of their operation. Of particular importance in acquiring valuable and useful for employees, as well as for the whole organization, is one of the processes of its conversion – externalization. It is important that during the implementation of subsequent projects, valuable resources such as knowledge, skills and experience acquired by employees are not lost, but that employees externalize them. The purpose of this article is to seek an answer to the research problem posed, concerning the course and methods of knowledge externalization in project activities and ways of knowledge externalization in the process of building project knowledge management systems in public organizations.

Presented at the 2017 International Conference on Knowledge Management during the panel session on Big Data, Ethics and Public Engagement. This presentation discusses the Data Rescue Denton 2017 event.

This paper describes the development of the SciThink App, a mobile knowledge management tool to help scientists and researchers query, download, and read scientific and technological literature.

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

Presented at the 2017 International Conference on Knowledge Management. This presentation describes the traditional scientific information analysis (SIA) workflow and proposes an integration-based conceptual framework for the National Science Library at the Chinese Academy of Sciences.