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The purpose of this paper is to explore the basics of semiotic analysis and concept theory that represent two dominant approaches to knowledge representation, and explore how these approaches are fruitful for knowledge organization.

In particular the semiotic theory formulated by the American philosopher C.S. Peirce and the concept theory formulated by Ingetraut Dahlberg are investigated. The paper compares the differences and similarities between these two theories of knowledge representation.

The semiotic model is a general and unrestricted model of signs and Dahlberg's model is thought from the perspective and demand of better knowledge organization system (KOS) development. It is found that Dahlberg's concept model provides a detailed method for analyzing and representing concepts in a KOS, where semiotics provides the philosophical context for representation.

This paper is the first to combine theories of knowledge representation, semiotic and concept theory, within the context of knowledge organization.

The purpose of this paper is to propose a graph-based representation approach for evolutionary knowledge under the big data circumstance, aiming to gradually build conceptual models from data.

A semantic data model named meaning graph (MGraph) is introduced to represent knowledge concepts to organize the knowledge instances in a graph-based knowledge base. MGraph uses directed acyclic graph–like types as concept schemas to specify the structural features of knowledge with intention variety. It also proposes several specialization mechanisms to enable knowledge evolution. Based on MGraph, a paradigm is introduced to model the evolutionary concept schemas, and a scenario on video semantics modeling is introduced in detail.

MGraph is fit for the evolution features of representing knowledge from big data and lays the foundation for building a knowledge base under the big data circumstance.

The representation approach based on MGraph can effectively and coherently address the major issues of evolutionary knowledge from big data. The new approach is promising in building a big knowledge base.

The purpose of this paper is to present descriptive characteristics of the historical development of concept networks. The linguistic principles, mechanisms and motivations behind the evolution of concept networks are discussed. Implications emanating from the idea of the historical development of concept networks are discussed in relation to knowledge representation and organization schemes.

Natural language data including both speech and text are analyzed by examining discourse contexts in which a linguistic element such as a polysemy or homonym occurs. Linguistic literature on the historical development of concept networks is reviewed and analyzed.

Semantic sense relations in concept networks can be captured in a systematic and regular manner. The mechanism and impetus behind the process of concept network development suggest that semantic senses in concept networks are closely intertwined with pragmatic contexts and discourse structure. The interrelation and permeability of the semantic senses of concept networks are captured on a continuum scale based on three linguistic parameters: concrete shared semantic sense; discourse and text structure; and contextualized pragmatic information.

Research findings signify the critical need for linking discourse structure and contextualized pragmatic information to knowledge representation and organization schemes.

The idea of linguistic characteristics, principles, motivation and mechanisms underlying the evolution of concept networks provides theoretical ground for developing a model for integrating knowledge representation and organization schemes with discourse structure and contextualized pragmatic information.

The purpose of this paper is to study the social representations of polydrug use in the Finnish mainstream media. Social representations are shared ways of talking about socially relevant issues and have ramifications on both individual and socio-political levels.

The social representations theory and the “What’s the problem represented to be?” analysis provided the theoretical framework. In total, 405 newspaper articles were used as data and analysed by content analysis and thematic analysis. The key tenets of the social representations theory, anchoring, objectifying and naturalisation, were used in data analysis.

The study found that polydrug use was written about differently in articles over the study period from 1990 to 2016. Three social representations were introduced: first, polydrug use as a concept was used to refer to the co-use of alcohol and medical drugs. This was seen as a problem for young people, which could easily lead to illicit drug use. Second, illicit drugs were included in the definitions of polydrug use, which made the social representation more serious than before. The typical polydrug user was portrayed as a person who was addicted to substances, could not quite control his/her use and was a threat to others in society. Third, the concepts were naturalised as parts of common language and even used as prototypes and metaphors.

The study provides a look at how the phenomenon of polydrug use is conceptualised in everyday language as previous research has concentrated on its scientific definitions. It also adds to the research of media representations of different substances.

A need to renew music-related information notions arises from both information-seeking models and literature of musical semiotics. The purpose of this paper is to create a music information typology, which aims at facilitating the examination of music information types at varying levels of abstraction in the context of information seeking.

Literature of musical semiotics and information seeking are juxtaposed to develop a novel approach to music-related information. The grounding concepts are Bruner’s enactive, iconic and symbolic modes of representation. The modes of representation offer a universal scheme of knowledge that is applied to the domain of music by defining their content through Tarasti’s Theory of Musical Semiotics.

This conceptual paper results in a music information typology ranging from the enactive music information representations to the abstract ones as follows. Music making as the first mode of enactive representations; music listening as the second mode of enactive representations; iconic representations of music; technological models of music as the first mode of symbolic representations; and ideological models of music as the second mode of symbolic representations.

The present paper develops a music information typology that encompasses broadly different music information facets by categorizing music information sources according to their level of abstraction. When applied into empirical research, the typology opens a new window into the perceived roles of music information types in the context of information seeking.

The paper aims to present the development of conceptualization of coronavirus disease 2019 (COVID-19) based on associations with other articles on English edition of Wikipedia. The main goal of the paper is to study the social organization of knowledge about COVID-19 within the Wikipedia community of practice.

The methodological approach taken in this study was based on the application of Moscovici's theory of social representations to Wikipedia's knowledge organization system (KOS). Internal links in the Wikipedia article about COVID-19 were considered anchors in its social representations. Each link in the introductory part of the article was considered an indicator of the semantic relationship between COVID-19 and other concepts from Wikipedia's knowledge base. The subject of this study was links extracted from all revisions of the COVID-19 article between February and September 2020. Qualitative and quantitative analyses were performed on these conceptual structures using both synchronic and diachronic approaches.

It was found that the evolution of anchors in the Wikipedia article on COVID-19 was in line with the mechanism of symbolic coping related to infectious disease. It went through stages of divergence, convergence and normalization. It shows that this mechanism governs the social organization of knowledge related to COVID-19 on Wikipedia.

No studies have been devoted to the image of COVID-19 as presented by the evolution of links in Wikipedia and its implications for knowledge organization (KO).

This chapter describes a successful research-developed representation construction approach to teaching and learning that links student learning and engagement with the epistemic practices of science. This approach involves challenging students to generate and negotiate the representations (text, graphs, models, diagrams) that constitute the discursive practices of science, rather than focusing on the text-based, definitional versions of concepts. The representation construction approach is based on sequences of representational challenges that involve students constructing representations to actively explore and make claims about phenomena. The key principles of the representation construction approach, considered a form of directed inquiry, are outlined with illustrations from case studies of whole topics in forces and astronomy within several middle-years’ science classrooms. This chapter also outlines the manner in which the representation construction approach has been translated into wider scale implementation through a large-scale Professional Development (PD) workshop program. Issues associated with wider scale implementation of the approach are discussed.

This study aims to identify the social representation of cloud computing from the perspective of Information Technology (IT) professionals in emerging countries, comparing it with the extant literature on this subject.

Data were collected from IT professionals in Brazil, which was used as a proxy for the emerging countries’ context related to cloud computing. Social Representation Theory was then applied to analyze the data.

Mismatches between theory and practice on cloud computing make it clear that most of the current scientific literature on cloud computing is, to a great extent, based on the context of developed countries rather than on the context of emerging ones.

Errors of inference may have been made during the categorization of the words evoked. Furthermore, Brazil was used as a proxy for the emerging countries’ context related to cloud computing.

IT professionals in emerging countries have quite an operational view of cloud computing. Thus, companies in these countries have to align cloud computing better with new business models and corporate strategies in order to take advantage of the transformational impacts of cloud computing.

IT professionals in emerging countries have failed to notice the strategic value of cloud computing, the new business models enabled by same, the privacy issues related to it and the impact cloud computing adoption can have on the IT costs of an organization. Moreover, mobility can be a paramount issue related to cloud computing in emerging countries – a fact thus far overlooked by academia.

The purpose of this paper is to illustrate how social representation theory (SRT) can be used to understand the concept of resistance to change. SRT is a growing theory in social psychology research. SRT is about how individuals co-construct representations of various objects in different social settings. These social representations govern the attitudes and actions of individuals and groups. In spite of the growing interest in SRT in various fields, no studies have used SRT to understand resistance to organizational change.

This study reviews the relevant literature on resistance to change and SRT to develop a conceptual framework for understanding resistance from the standpoint of SRT.

The authors develop a model that illustrates how three interrelated objects, i.e. the organizational process and the pre-and post-change situation, are co-constructed in social contexts. Also, the authors discuss how representations of these objects can co-exist (cognitive polyphasia). Our study illustrates the complexity of resistance to change by deconstructing the concept.

Application of SRT to analyze resistance to organizational change is a novel approach that provides several new insights. For example, where most publications regard advocates of change as sense-givers in the change recipient’s sense-making process, the authors argue for a more constructionist approach. Thus, all actors involved in the change process will affect each other and together co-construct the social representations. These social representations govern attitudes to change.