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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 explore the representation of Kanaka Maoli (Hawaiian) Hula Dance in traditional systems of representation and organization.

This exploratory study analyzes the controlled and natural language vocabularies employed for the representation and organization of Hawaiian culture, in particular Hawaiian hula. The most widely accepted and used systems were examined: classification systems (Library of Congress Classification and Dewey Decimal Classification), subject heading systems (Library of Congress Subject Headings and authority files (Library of Congress and OCLC Authority Files), and citation indexing systems (Web of Science Social Sciences and Art and Humanities databases).

Analysis of various tools of representation and organization revealed biases and diasporization in depictions of Hawaiian culture. The study emphasizes the need to acknowledge the aesthetic perspective of indigenous people in their organization and presentation of their own cultural knowledge and advocates a decolonizing methodology to promote alternative information structures in indigenous communities.

This study contributes to the relatively limited scholarship on representation and organization for indigenous knowledge organization systems, in particular Hawaiian culture. Research suggests that access to Native Hawaiian cultural heritage will raise awareness among information professionals in Hawai’i to the beauty of Native Hawaiian epistemology.

The purpose of this paper is to provide a critical analysis from an ethical perspective of how the concept of indigenous wayfinding and voyaging is mapped in knowledge representation, organization and discovery systems.

In this study, the Dewey Decimal Classification, the Library of Congress Subject Headings, the Library of Congress Classifications systems and the Web of Science citation database were methodically examined to determine how these systems represent and facilitate the discovery of indigenous knowledge of wayfinding and voyaging.

The analysis revealed that there was no dedicated representation of the indigenous practices of wayfinding and voyaging in the major knowledge representation, organization and discovery systems. By scattering indigenous practice across various, often very broad and unrelated classes, coherence in the record is disrupted, resulting in misrepresentation of these indigenous concepts.

This study contributes to a relatively limited research literature on representation and organization of indigenous knowledge of wayfinding and voyaging. This study calls to foster a better understanding and appreciation for the rich knowledge that indigenous cultures provide for an enlightened society.

The current paper aims at contributing to the understanding of interorganizational knowledge integration by highlighting the role of individuals' understandings of the task and how they shape knowledge integrating behaviours.

The paper presents a framework of knowledge integration as heedful interrelating. Knowledge integration is conceptualized as help seeking, help giving and reflective reframing, and the paper discusses how these knowledge integrating behaviors are shaped by actors' representations of the situation and their role in it. The framework is illustrated and refined in relation to a qualitative case study of an IT outsourcing project.

Narrow and separating representations of actors' roles, partly based on institutionalized ideas of the proper behaviors of “buyers” and “suppliers”, impede knowledge integration. Such representations render the knowledge integrating behaviors help seeking, help giving and reflective reframing illegitimate.

Results call for attention to actors' representations of the situation and their role in it in order to understand knowledge integration. The interorganizational setting, with its institutionalized roles, provides unique challenges that need to be investigated further. As findings are based on a single case study, further research needs to extend the findings to other kinds of interorganizational collaboration.

The paper adds to the understanding of interorganizational knowledge integration by drawing attention to the importance of individual actors' representations and behaviors. Hereby, the dominant organizational and network levels of analysis in the literature on interorganizational knowledge integration are complemented by an individual level of analysis.

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.

After reviewing cultural heritage institutions; crowdsourcing initiatives and tension between univocal and multivocal views of those who interact with cultural expressions, this paper argues that to support vibrant and effective crowdsourcing communities while ensuring the quality of the work of crowdsourcing project volunteers it is essential to reevaluate and transform the traditional univocal, top-down approach to representation and organization. The paper aims to discuss these issues.

This conceptual paper applies Foucault’s power–knowledge construct and theories of representation to the processes and practices employed in cultural heritage crowdsourcing projects.

Viewed through the Foucauldian lens, cultural heritage professionals are regarded as active parts of the power–knowledge relationship due to their direct engagement in the representation, organization and dissemination of knowledge, exercised not only through the traditional role of cultural heritage institutions as gatekeepers of knowledge but, more importantly, through the power of representation and organization of the cultural heritage.

This paper provides a theoretical understanding of cultural heritage crowdsourcing initiatives and proposes a framework for multivocal representation of cultural heritage expressions in which the voices of volunteers have the same validity as the voices of cultural heritage professionals.

In recent years, knowledge graph completion has gained increasing research focus and shown significant improvements. However, most existing models only use the structures of knowledge graph triples when obtaining the entity and relationship representations. In contrast, the integration of the entity description and the knowledge graph network structure has been ignored. This paper aims to investigate how to leverage both the entity description and the network structure to enhance the knowledge graph completion with a high generalization ability among different datasets.

The authors propose an entity-description augmented knowledge graph completion model (EDA-KGC), which incorporates the entity description and network structure. It consists of three modules, i.e. representation initialization, deep interaction and reasoning. The representation initialization module utilizes entity descriptions to obtain the pre-trained representation of entities. The deep interaction module acquires the features of the deep interaction between entities and relationships. The reasoning component performs matrix manipulations with the deep interaction feature vector and entity representation matrix, thus obtaining the probability distribution of target entities. The authors conduct intensive experiments on the FB15K, WN18, FB15K-237 and WN18RR data sets to validate the effect of the proposed model.

The experiments demonstrate that the proposed model outperforms the traditional structure-based knowledge graph completion model and the entity-description-enhanced knowledge graph completion model. The experiments also suggest that the model has greater feasibility in different scenarios such as sparse data, dynamic entities and limited training epochs. The study shows that the integration of entity description and network structure can significantly increase the effect of the knowledge graph completion task.

The research has a significant reference for completing the missing information in the knowledge graph and improving the application effect of the knowledge graph in information retrieval, question answering and other fields.

This study aims to examine how a collaboration technology is used by three organizational groups. The main focus is on the interplay between the users’ perceptions (of the technology and of the knowledge shared) and the material properties of the collaboration technology.

Two theoretical frameworks (social representations and sociomaterial practice perspective) examine collaboration technology use to better understand the underlying dynamics. The research is conducted as a case study in a US company where a collaboration technology was being implemented.

The findings reveal a process model showing how social dynamics and users’ perceptions of what the collaboration technology can do and cannot do to share the users’ knowledge influence the users’ behaviour. Based on these perceptions, users will twist or amend their interpretation of the reality (the material properties of the technology) to justify their use of the collaboration technology.

This research is conducted as a single case study. However, the significant amount of time spent at the research site allowed for a very rich description of the events and processes involved.

This study offers guidelines on what influences use and adoption of collaboration technologies. It highlights the importance of providing more than just training, as social dynamics and users’ perceptions continuously influence users’ behaviour.

By combining two complementary theoretical frameworks, this study provides a novel and more in-depth explanation of collaboration technology use (or lack thereof).

This study aims to present a new framework for ethical creation and evaluation of multi-perspective knowledge organization systems.

Applying Held's understanding of the ethics of care, this paper proposes five operative criteria for ethical building and evaluation of multi-perspective knowledge representation and organization systems.

This paper argues that a carefully designed multipoint view of representation and organization conforms to the proposed ethical criteria and shifts concerns associated with the expectation of neutrality of library information professionals to the necessity to humanize and diversify the representation and organization of knowledge to build inclusive and equitable systems.

This paper presents multi-perspectiveness as key to ethical knowledge organization. The paper proposes a generic taxonomy of the main stages in the creation of multi-perspective knowledge representation and organization systems and demonstrates how to apply the proposed framework in each stage to ensure ethical outcomes.

Knowledge- and communication-intensive domains still long for a better support of creativity that considers legal requirements, compliance rules and administrative tasks as well, because current systems focus either on knowledge representation or business process management. The purpose of this paper is to discuss our model of integrated knowledge and business process representation and its presentation to users.

The authors follow a design science approach in the environment of patent prosecution, which is characterized by a highly standardized, legally prescribed process and individual knowledge study. Thus, the research is based on knowledge study, BPM, graph-based knowledge representation and user interface design. The authors iteratively designed and built a model and a prototype. To evaluate the approach, the authors used analytical proof of concept, real-world test scenarios and case studies in real-world settings, where the authors conducted observations and open interviews.

The authors designed a model and implemented a prototype for evolving and storing static and dynamic aspects of knowledge. The proposed solution leverages the flexibility of a graph-based model to enable open and not only continuously developing user-centered processes but also pre-defined ones. The authors further propose a user interface concept which supports users to benefit from the richness of the model but provides sufficient guidance.

The balanced integration of the data and task perspectives distinguishes the model significantly from other approaches such as BPM or knowledge graphs. The authors further provide a sophisticated user interface design, which allows the users to effectively and efficiently use the graph-based knowledge representation in their daily study.