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The authors examine and compare accounting associations' identities in distinct segments of the accounting profession surrounding the 2014 merger of three Canadian accounting associations.

The authors conceive of accounting associations' magazine front covers as a setting for “identity performance” (i.e. a scenery through which identity dimensions are intentionally communicated to target audiences). The authors examine pre-merger and post-merger associations' identity performances that took place between January 2011 and December 2020 and identify 21 broad themes that the authors interpret in terms of identity logics (i.e. professionalism/commercialism) and audience focus (society/association members), underscoring (dis)similarities in identity performances pre- and post-merger.

The authors' analysis reveals distinct identity performances for the different segments of the pre-merger accounting profession and for the post-merger unified accounting association. Identity logics manifest differently: a commercial logic dominated for two of the associations and a professional logic dominated for the third. Identity fluidity was evident in the merged association's shift from commercial toward professional logic when the association ceased publishing one magazine and introduced a new one. Society rather than associations' members dominated as a target audience for all associations, but this focus manifested differently. Post-merger, identity performances continued to focus on society as the audience.

The authors highlight the Goffmanian identity performances (Goffman, 1959) taking place via accounting associations' magazines. The authors adopt a segment perspective (Bucher and Strauss, 1961) that demonstrates that commercialism does not trump professionalism in all segments of the profession. For the first time, the authors juxtapose identity logics (professionalism/commercialism) and targeted audiences to better understand how these facets of accountants' identities compare between segments.

The compliance checking of Building Information Modeling (BIM) models is crucial throughout the lifecycle of construction. The increasing amount and complexity of information carried by BIM models have made compliance checking more challenging, and manual methods are prone to errors. Therefore, this study aims to propose an integrative conceptual framework for automated compliance checking of BIM models, allowing for the identification of errors within BIM models.

This study first analyzed the typical building standards in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage, and a data extraction method based on the Dynamo is designed to obtain checking data files. After that, a matching algorithm is devised to express the logical rules of knowledge graph triples, resulting in automated compliance checking for BIM models.

Case validation results showed that this theoretical framework can achieve the automatic construction of domain knowledge graphs and automatic checking of BIM model compliance. Compared with traditional methods, this method has a higher degree of automation and portability.

This study introduces knowledge graphs and natural language processing technology into the field of BIM model checking and completes the automated process of constructing domain knowledge graphs and checking BIM model data. The validation of its functionality and usability through two case studies on a self-developed BIM checking platform.

The study explores the decision-making logics driving the usage of social media among internationalising small and medium-sized enterprises (SMEs), and how it supports entrepreneurial opportunity recognition. The author draws on qualitative data from four internationalising firms all of which had adopted social media. The findings show that causal decision-making logic is the main element driving the initial usage of social media (i.e. pre-adoption). Concerning ongoing usage, the author found evidence of both causal and effectual logic; the choice being dependent on the firm’s resources. The findings also show that both drivers of social media users have a paramount role in entrepreneurial opportunity recognition.

With the development of data mining technology, diverse and broader domain knowledge can be extracted automatically. However, the research on applying knowledge mapping and data visualization techniques to genealogical data is limited. This paper aims to fill this research gap by providing a systematic framework and process guidance for practitioners seeking to uncover hidden knowledge from genealogy.

Based on a literature review of genealogy's current knowledge reasoning research, the authors constructed an integrated framework for knowledge inference and visualization application using a knowledge graph. Additionally, the authors applied this framework in a case study using “Manchu Clan Genealogy” as the data source.

The case study shows that the proposed framework can effectively decompose and reconstruct genealogy. It demonstrates the reasoning, discovery, and web visualization application process of implicit information in genealogy. It enhances the effective utilization of Manchu genealogy resources by highlighting the intricate relationships among people, places, and time entities.

This study proposed a framework for genealogy knowledge reasoning and visual analysis utilizing a knowledge graph, including five dimensions: the target layer, the resource layer, the data layer, the inference layer, and the application layer. It helps to gather the scattered genealogy information and establish a data network with semantic correlations while establishing reasoning rules to enable inference discovery and visualization of hidden relationships.

This study aims to develop a synthetic knowledge repository consisted of interrelated Web Ontology Language.

The ontology composes the main framework to categorize data of product life cycle with eco-design mode (PLC-EDM) and automatically infer specialists’ knowledge for data confirmation, eventually assisting the utilizations and generation of strategies toward decision-making

(i) utilization of a novel model with ontology mode for information reuse cross the different eco-design applications; (ii) generation of a sound platform toward life cycle evaluation; and (iii) implementation of the PLC-EDM model along the product generation process.

It cannot substitute an evaluation tool of life cycle. Certainly, this model does not predict the “target and range” and/or the depiction of the “utility module” that are basic activities in life cycle assessments as characterized through the international organization for standardization regulations.

As portion of this framework, a prototype Web application is presented which is applied to produce, reuse and verify knowledge of product life cycle.

By counting upon the ontology, the information conducted by the utilization is certainly semantically represented to promote the data sharing among various participants and tools. Besides, the data can be verified against possible faults by inferring over the ontology. Hence, a feasible way to a popular topic in the domain of eco-design applications extension in the industry.

The goals are: to lean on rigid modeling principles; and to promote the interoperability and diffusion of the ontology toward particular utilization demands.

Personal museums provide the conceptual catalyst for liking as a research approach and inclusivity around “idiosyncratic” knowledges within information research. An adapted research paper format echoes the approach of personal museums: as a commentary on the limits of institutional shaping for the field.

Personal museums are conceptualized as spaces of knowing in-formation, ontological openings that are literally and figuratively entered into, that make a difference to human and material ways of knowing. Karen Barad's agential realism and Sianne Ngai's vernacular aesthetic categories provide the theoretical lenses through which the researcher's 2018 visit to one personal museum is revisited.

An ethnographic account of the author's visit to the Communist Consumer Museum (CCM) in Timişoara, Romania shows how its improvisational, friendly and intimate atmosphere exposes it as a space of entanglements in a quantum sense, emphasizing the inseparability of human and material realms and how knowledges are always in-formation. Such entanglements create atmospheres generative of different ways of thinking about information and knowledge.

Human expressions of liking reveal material agencies as ways of knowing and information beyond the realm of human experience and meaning. A vernacular aesthetics of liking is presented as a way to resist the marginalizing tendencies of knowledges classified as unconventional, idiosyncratic or eccentric. This approach is one way of resisting the assumptions of channel thinking that often shape how information is studied.

The purpose of the paper is to propose a semantic model for describing open source software (OSS) in a machine–human understandable format. The model is extracted to support source code reusing and revising as the two primary targets of OSS through a systematic review of related documents.

Conducting a systematic review, all the software reusing criteria are identified and introduced to the web of data by an ontology for OSS (O4OSS). The software semantic model introduced in this paper explores OSS through triple expressions in which the O4OSS properties are predicates.

This model improves the quality of web data by describing software in a structured machine–human readable profile, which is linked to the related data that was previously published on the web. Evaluating the OSS semantic model is accomplished through comparing it with previous approaches, comparing the software structured metadata with profile index of software in some well-known repositories, calculating the software retrieval rank and surveying domain experts.

Considering context-specific information and authority levels, the proposed software model would be applicable to any open and close software. Using this model to publish software provides an infrastructure of connected meaningful data and helps developers overcome some specific challenges. By navigating software data, many questions which can be answered only through reading multiple documents can be automatically responded on the web of data.

The purpose of this study is to introduce the concept of Ecopoiesis. Introduction of the concept of ecopiesis, which explains the linkage strategy between relational and energetic resources (sustainability) that enable the relational viability of living things.

The design is based on the use of the relationship between abduction, epigenesis, cismogenesis and morphogenesis.

This paper concludes with a counter-intuitive proposal to the dominant lines of thought, distinguishing: Complexity as vital interweaving, Aristotelian Oikos as communitarian distinction, Organism-Entorno from relational theory (beyond the interactional), in a cybernetic referential framework that allows tending to sustain and sustain life from Ecopoiesis.

According to a relational theory of cognition, the sources of knowledge go beyond genetic and environmental factors. In the sphere of explanation, this study moves from “how much,” “why” and “how” to “why not.” Thus, the processes involved in understanding the living are forced to move from the logic of parts to the logic of patterns, which implies developing an explanation that considers the unique characteristics of development, encompassing the diverse origins of the organization of the living.

The study seeks to contribute to a deeper understanding of the relationship between remediations and participation in new media. By lending some transparency, the analysis hopes to contribute toward generating a critical optics aware of the potentials and pitfalls of emergent media.

The methodology is visual semiotic analysis. The author make no claim for one, true interpretation or critical judgment about the images.

In demonstrating some shortfalls of Instagram affordances, the analysis shows how social media sites can develop tools that encourage users to engage in civic consciousness and respectful political debate. The study makes clear that new media tools can hamper or aid participatory logics.

To author’s knowledge, no other study that has analyzed remediated images related to the controversial confirmation of Brett Kavanaugh to the U.S. Supreme Court. It is also important to place these images in the contexts of “iconicity” in emergent media (a concept increasingly being eroded in new media environment).

There is an increasing interest in the use of knowledge graphs to represent real-world knowledge and a common need to manage imprecise knowledge in many real-world applications. This paper aims to study approaches to solve flexible queries over knowledge graphs.

By introducing fuzzy logic in the query answering process, the authors are able to obtain a novel algorithm to solve flexible queries over knowledge graphs. This approach is implemented in the FUzzy Knowledge Graphs system, a software tool with an intuitive user-graphical interface.

This approach makes it possible to reuse semantic web standards (RDF, SPARQL and OWL 2) and builds a fuzzy layer on top of them. The application to a use case shows that the system can aggregate information in different ways by selecting different fusion operators and adapting to different user needs.

This approach is more general than similar previous works in the literature and provides a specific way to represent the flexible restrictions (using fuzzy OWL 2 datatypes).