Managing flood-related data to assist in the disaster management is a critical process of high importance during a flood disaster. These data are heterogeneous and can be provided from different data sources, and integrating them is a challenging task which allows to infer new information that helps in limiting the consequences of a flood. In this paper, we propose a novel approach that manages heterogeneous flood-related data based on semantic web techniques and helps in limiting the damage caused by floods. We first propose an ontology that is used to formally describe the flood-related data, and we build our knowledge graph through integrating heterogeneous data using the proposed ontology. Then, we propose a reasoning approach using SHACL rules to infer new information that helps in managing the flood disaster or in anticipating future events. The experimental evaluations of our proposed approach are conducted on a real case study in the frame of flood disaster management with the aim of generating evacuation priorities. The results show that it succeeds in managing heterogeneous flood-related data and generating evacuation priorities in a very short time.

Knowledge is awareness or familiarity gained by experiences of facts, data, and situations. Knowledge management includes techniques and processes to represent, store, search, integrate, and analyze knowledge that is available in digital form. Ontology is a formal explicit specification of a shared conceptualization of a domain of interest and it is a building block of the semantic web and formal description of knowledge. Ontologies capture the structure and knowledge about some domain of interest by describing the concepts in the domain and also the relationships that hold between those concepts. Even though Ethiopia has potential tourist destinations, the country is not benefited from its resources due to misperception about image of the country; lack of promoting the potential tourism resources of the country to the world; problems with sharing, searching and retrieval of tourist information. Thus, the country is forced to accept smaller number of tourists and not getting the benefits it deserves. The objective of this paper is to build ontology for Ethiopian Tourism so that it makes Ethiopian tourism destinations visible to international visitors. We use OWL language implemented in Protégé with other ontology development activities proposed in METHONTOLOGY to build Ethiopian tourism ontology. We also use OWL …

Presentation for the "Open Science and Open Data for Sustainable Development: A Global View" panel that discusses the global landscape of open science.

The study in this paper aims to describe the mechanism of knowledge recall in the context of organizational memory. We approached a startup involved in the development of a digital marketplace and observed how the founders interacted with the accumulated knowledge. With observation as the research method and longitudinal data collected, we found the founding group in the way they understood organizational memory. There are three mechanisms of remembering organizational memory including identification, adaptation, and correction. The identification mechanism is the highest level of recall ability followed by adaptation and correction. This study implies that founders with different backgrounds have different ways of remembering organizational memory.

Quantum physics surpasses human imagination. It totally contradicts everyday experiences. Even literal and mathematical explanations cannot substitute for a non-intuitive behavior that puzzles many of us. Commercial quantum computers are in reach within this decade. History provides examples that the appearance of new technologies brought metaphors to life that may explain up to that point poorly understood knowledge domains (e.g., "brains are hardware while thoughts are software"). The author describes why the proliferation of quantum computers will be accompanied by the rise of metaphors that explain quantum effects. For one, those might help to better communicate about the best use and consequences of quantum computers. But those metaphors could also shed light on organizational performance at all. To show a practical example, the author proposes how the use of quantum metaphors could help organizations to prepare for the quantum computing era - without being exact in predictions about most likely technical implementation of quantum capabilities.

Presentation paper for the 2017 International Conference on Knowledge Management. This paper focuses on the empowerment of the individual in light of Personal Knowledge Management (PKM) learning cycles by extending the ignorance matrix in the context of Big Data and Extelligence.

Presentation paper for the 2017 International Conference on Knowledge Management. This paper introduces the study and practice of design knowledge management and knowledge transfer across the design of a newly built nuclear power plant in China.

Evaluating the impact of learning from climate data, in addition to bridge data, on the performance of concrete deck condition rating prediction is critical for identifying the right data needed to enhance bridge maintenance decision making. Few studies have considered such an evaluation and utilized a small size of samples that prevent revealing the knowledge hidden within the big size of data. Although, such evaluation over big data seems quite necessary, class imbalance problem makes it challenging. To alleviate such a problem, five states, including Alabama, Iowa, New York, Pennsylvania, and South Carolina, were selected as the case study. Not only are the states located in three different climatically consistent regions defined by the National Ocean and Atmospheric Administration (NOAA), but also their concrete deck conditions ratings are somewhat balanced. To conduct the evaluation, this research developed the bridge data set pertaining to 56,288 bridges across the afore-mentioned states through employing the GIS technology. The bridge data set contains bridge data derived from National Bridge Inventory (NBI), and climate data derived from Parameter-elevation Relationships on Independent Slopes Model (PRISM) climate maps and NOAA. Then, two machine learning algorithms, including random forest and GBM, were trained - with and without climate …

The 17th International Conference on Knowledge Management was held in the historic city of Potsdam, Germany. The conference was among the first post-pandemic face to face conferences, and 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.

Poster paper for the 2017 International Conference on Knowledge Management. This paper studies how general faculty members view open access (OA) publishing.

The psychiatric disorder rates among opioid dependents have alarmingly increased over the last decades, and these disorders are higher for women than men and higher for individuals in low socioeconomic groups. Previous knowledge asserted that opioids had no addictive or harmful effects that could lead to psychiatric disorders, but the recent discovery of opioid-related knowledge reversed the existing belief. The purpose of this research is to discover how the new knowledge has changed regarding psychiatric disorders from opioids between men and woman and across socioeconomic groups. In order to uncover these changes, the research data is obtained from the Treatment Episode Data Set (TEDS) in 2007 and 2017. While the percentage of psychiatric disorders among opioid dependents is higher for women than men, unexpectedly the growth rate of psychiatric disorders for men is much faster than women. As such, the socially constructed conventional knowledge that psychiatric disorders are women’s illness will change in the near future. Congruent with existing knowledge, psychiatric disorders in this dataset are higher for underprivileged brackets such as those with low education, unemployed, separated, divorced, and widowed people, and Medicaid recipients, and the growth rates for these groups are steeper than their counterparts.

The Soft Skills theme has been presented and discussed by several academic and professional players: researchers, consultants, entrepreneurs and technicians in Human Resources. These are personal skills that go beyond technical competence, absolutely determining the performance of any organization. Understanding what they will be and how to develop these skills has been the challenge of the World Economic Forum (WEF), which periodically publishes reports mapping areas, professions and skills that will be trending in the coming years. So, this article seeks to answer which skills are requested in advertisements and job vacancies in the area of ​​ICT in the region of Florianópolis? with a double objective: [i] Identify whether companies in the creative economy segment, specifically technology, in the city of Florianópolis / SC are looking for soft skills in their job advertisements; and in this way [ii] Understand whether they are aligned with the trends presented by the WEF. For this, it carried out a qualitative research, classified as descriptive with an exploratory stage of analysis of the vacancies published in the LinkedIn and ACATE platforms, making it possible to conclude the importance of soft skills for the profile of technology professionals. It was also evident the difficulty in …

Presentation paper for the 2017 International Conference on Knowledge Management. This paper examines the level of awareness and understanding of the various issues, challenges, and training needs associated with research data management for Hacettepe University researchers

This workshop is presented by members of a University of North Texas research team. First, the team will overview their experience as members of the research team and share experience in areas such as trust formation, team roles, productivity, work-life balance, faculty-students interaction, peer and faculty mentorship, dissertation preparation, and job seeking. Second, the workshop will discuss and brainstorm how this format can be implemented for organizations both with faculty-student teams and with peer-directed teams. Finally, successes and challenges are openly discussed with audience.

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 …

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.

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.

With an increasing flood of data and at the same time changing requirements, making the relevant information available in the right context to a customer and within the company for the respective development-, technical- and service-departments is a key success factor for many companies and at the same time an enormous challenge. The problem with folders and filing data in tree structures is that information about an object is scattered across different aspects. Access to this information is only possible if the respective aspects are known. In a semantic network, each object exists only once, all information about this object comes together at this point and it can still be accessed within different contexts. Such a network can be changed at any time and further aspects can be added as needed: semantic machine learning, in order to be able to react flexibly to new requirements. Semantic networks combine functions of ontologies, topic maps, taxonomies and thesauri. They model complex relationships and directly transform large amounts of structured and unstructured content into networked units of knowledge. In this way, computer-readable and computer-usable knowledge bases are created. The creation and maintenance of semantic networks is demand-driven and interactive between humans and computers. …

With an increasing flood of data and at the same time changing requirements, making the relevant information available in the right context to a customer and within the company for the respective development-, technical- and service-departments is a key success factor for many companies and at the same time an enormous challenge. The problem with folders and filing data in tree structures is that information about an object is scattered across different aspects. Access to this information is only possible if the respective aspects are known. In a semantic network, each object exists only once, all information about this object comes together at this point and it can still be accessed within different contexts. Such a network can be changed at any time and further aspects can be added as needed: semantic machine learning, in order to be able to react flexibly to new requirements. Semantic networks combine functions of ontologies, topic maps, taxonomies and thesauri. They model complex relationships and directly transform large amounts of structured and unstructured content into networked units of knowledge. In this way, computer-readable and computer-usable knowledge bases are created. The creation and maintenance of semantic networks is demand-driven and interactive between humans and computers. …

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 panels that provide an overview of the different methodologies and theories of sense-making from several of the seminal originators of sensemaking.

Global warming is the term used to describe critical environmental issues and concerns. Social media such as Twitter provides a platform for people to share information, exchange ideas, and express their opinions about current and timely issues. This study utilized contextual analysis to analyze data collected from Twitter for the hashtag "global warming" during the period 2010 & 2011. Using sentiment analysis and topic modeling, the study aimed first at assessing people's perception towards global warming issues, and second study the impact of misinformation from the standpoint of social noise on people's perception of global warming during critical environmental events. The outcome of this study helps create a better understanding of the environmental issues discussed on social media. The sentiment analysis from the data analyzed so far shows that most of the tweets were based on Twitter users' personal opinions and not science. The topic modeling results suggest that Twitter users typically tweeted when a major environmental event occurred due to global warming. Topic modeling also aids in the identification of terms that is associated with social noise. The presence of social noise suggests that misinformation does exist and spreads faster.

Despite continued improvements to HIV/AIDS treatment and awareness, HIV transmission rates remain high among men who have sex with men (MSM). Online consumer health information targeting high risk MSM through social media and geosocial networking (GSN) apps have shown to be successful HIV intervention strategies. This review article addresses (1) the efficacy and acceptance of delivering consumer health information about pre-exposure prophylaxis (PrEP) and HIV prevention through GSN apps, (2) the impact of online and social media communities in the discussion and delivery of information about PrEP and HIV interventions, and (3) on-going and possible future research and the role of information professionals.

Soft skills have become increasingly important in the workplace, particularly in knowledge management (KM). Developing a knowledge culture in an organization depends on the soft skills of leaders. KM literature, however, does not often discuss the development and teaching of soft skills that can facilitate the success of knowledge management in organizations. This presentation will present the challenge of teaching and learning soft skills as well as a proposed framework to address those challenges.

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.