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This paper aims to better understand how an accounting information system (AIS), working as a multidimensional knowledge object, engages users in a new round of knowledge development which allows them to explore new managerial directions. Drawing on the concept of the knowledge object and the knowing in practice perspective, this study considers the relationships between subjects and objects in the explication of accounting practice, underlining how AIS could become a knowledge object that can assume a variety of forms, starting from such contradictions emerging from practice.

Theoretical argumentations are applied to a case study at a global logistics provider in the South of Italy, which manages the supply chain from origin to destination, offering a multitude of services in the transport and distribution sector.

The case study shows that the process of knowledge accumulation promotes the mutation of AIS into a knowledge object that, in its variety of forms, allows managers to explore new managerial directions such as the reorganization of warehouse activities.

The paper seeks to enrich the interpretation of AIS as a multidimensional knowledge object becoming a catalyst of new managerial directions through knowing. That helps to understand the role of accounting tools as a social practice supporting decision-making and how accounting systems’ openness and questioning nature makes them objects of enquiry able to support the identification of new managerial directions and lead the AIS to continually explode and mutate into something else.

The purpose of this article is to understand the meaning of museum objects from an information perspective. Links are made from Buckland's conceptual information framework as a semiotic to museum object as “document” and finally to user experience of these museum “documents”. The aim is to provide a new lens through which museum studies researchers can understand museum objects and for LIS researchers to accept museum objects as another form of document to be studied.

A conceptual and comparative analysis of Buckland's information typology as a semiotic. Outcome of analysis forms a model of understanding the museum object as a “document” that is accessed by users on a continuum of experience.

Michael Buckland's information typology is insightful and useful for a broad understanding of what all heritage institutions have in common: the physical object. Buckland helps us see the museum as an information system, the museum object as a document, and the multidimensional use of the concept information and its semiotic ramifications.

Buckland's typology is important to an understanding of the museum system and museum object in both LIS and museum studies. The concept of “document” opens up a broader perspective, which creates, rather than limits understandings of the human relationship with information. This expanded concept of “document” as sign/semiotic helps us understand user experience in ways not previously explored in the convergence of museums and information studies, from the practical to the theoretical. In this inclusive sense, Buckland's concept of document is a unifying theoretical concept for museums, libraries, and archives.

KM seems to be another buzzword. More and more we hear about the new imperatum of knowledge. Like researchers in a new field, our daily life is a continuous knowledge management process. Moreover, the origins of our focus diversify biased to the KM perspectives that we have conceptualized. Our paper intends to reveal the continuous process of KM to re‐usable learning objects. The case of organizational memory is treated as a cumulative system of value adding components. The deployment of information and communication technologies in our approach justifies the intelligence of our analysis. Web semantics, metadata specification and extensive XML specifications provide only the enclosure of an extensive analysis of concepts. Two concepts are presented: multidimensional dynamic e‐learning and the value adding knowledge management framework.

Semantic modelling is an essential prerequisite for designing the intelligent human–computer interaction in future aircraft cockpit. The purpose of this paper is to outline an ontology-based solution to this issue.

The scenario elements are defined considering the cognitive behaviours, system functions, interaction behaviours and interaction situation. The knowledge model consists of a five-tuple array including concepts, relations, functions, axioms and instances. Using the theory of belief-desire-intention, the meta-model of cognitive behaviours is established. The meta-model of system functions is formed under the architecture of sub-functions. Supported by information flows, the meta-model of interaction behaviours is presented. Based on the socio-technical characteristics, the meta-model of interaction situation is proposed. The knowledge representation and reasoning process is visualized with the semantic web rule language (SWRL) on the Protégé platform. Finally, verification and evaluation are carried out to assess the rationality and quality of the ontology model. Application scenarios of the proposed modelling method are also illustrated.

Verification results show that the knowledge reasoning based on SWRL rules can further enrich the knowledge base in terms of instance attributes and thereby improve the adaptability and learning ability of the ontology model in different simulations. Evaluation results show that the ontology model has a good quality with high cohesion and low coupling.

The approach presented in this paper can be applied to model complex human–machine–environment systems, from a semantics-driven perspective, especially for designing future cockpits.

Different from the traditional approaches, the method proposed in this paper tries to deal with the socio-technical modelling issues concerning multidimensional information semantics. Meanwhile, the constructed model has the ability of autonomous reasoning to adapt to complex situations.

Learning objects strive for reusability in e‐Learning to reduce cost and allow personalization of content. We show why learning objects require adapted Information Retrieval systems. In the spirit of the Semantic Web, we discuss the semantic description, discovery, and composition of learning objects. As part of our project, we tag learning objects with both objective (e.g., title, date, and author) and subjective (e.g., quality and relevance) metadata. We present the RACOFI (Rule‐Applying Collaborative Filtering) Composer prototype with its novel combination of two libraries and their associated engines: a collaborative filtering system and an inference rule system. We developed RACOFI to generate context‐aware recommendation lists. Context is handled by multidimensional predictions produced from a database‐driven scalable collaborative filtering algorithm. Rules are then applied to the predictions to customize the recommendations according to user profiles. The RACOFI Composer architecture has been developed into the contextaware music portal inDiscover.

Currently, the Tang tomb mural cultural relic resources are presented in a multi-source and heterogeneous manner, with a lack of effective organization and sharing between resources. Therefore, this study aims to propose a multidimensional knowledge discovery solution for Tang tomb mural cultural relic resources.

Taking the Tang tomb murals collected by the Shaanxi History Museum as an example, based on clarifying the relevant concepts of Tang tomb mural resources and considering both dynamic and static dimensions, a top-down approach was adopted to first construct an ontology model of Tang tomb mural type cultural relics resources. Then, the actual case data was imported into the Neo4J graph database according to the defined pattern hierarchy to complete the static organization of knowledge, and presented in a multimodal form in knowledge reasoning and retrieval. In addition, geographic information system (GIS) technology is used to dynamically display the spatiotemporal distribution of Tang tomb mural resources, and the distribution trend is analysed from a digital humanistic perspective.

The multi-dimensional knowledge discovery of Tang tomb mural cultural relics resources can help establish the correlation and spatiotemporal relationship between resources, providing support for semantic retrieval and navigation, knowledge discovery and visualization and so on.

This study takes the murals in the collection of the Shaanxi History Museum as an example, revealing potential knowledge associations in a static and intelligent way, achieving knowledge discovery and management of Tang tomb murals, and dynamically presents the spatial distribution of Tang tomb murals through GIS technology, meeting the knowledge presentation needs of different users and opening up new ideas for the study of Tang tomb murals.

The paper describes exploratory research into the nature of the International/Industrial Marketing and Purchasing (IMP) conference papers with particular focus on content. A qualitative analysis of the Proceedings of the 16th Annual IMP Conference is presented. The results provide insights into the diversity of academic thought that fuels the development of the IMP network and allows us to begin charting the development of knowledge structures within past IMP conferences. Of particular interest are, first, the tentative knowledge structure that emerges, second, the depth of analysis that emerges from using multidimensional coding, and third, the utility of the process of successive categorisation.

The texturalcentric model of visual and tactile response to textural fabric surfaces was used to extract characteristics that could be used to build a construct definition of texture perception. Using multidimensional scaling analysis permitted subjects to provide numeric judgements of fabrics rather than using words with the individual's historic definition of those terms or without knowledge of some terms. Two hundred and forty subjects (50 per cent male, 50 per cent female) provided visual, tactile, or visual and tactile ratings of similarities of fabrics. The 47 fabrics were used in two administrations to ascertain cross‐validation. Data were analysed using M‐D SCAL Version 5M. Dimensions or characteristics of fabric were statistically analysed and named using bipolar adjectives: rough to smooth, plane to depth, irregular to regular surface units, shiny to matt, fine to coarse, light weight to heavy weight, simple to complex, small units to large units, open to compact, and soft to bumpy‐rough.

Formulates a new theoretical basis for a formal approach to strategies for multidimensional investment. Summarizes the concepts on which the model is based and shows how they are combined within a dynamic schema. In order to prepare operational policies for multidimensional investment, enlarges the basic notion underlying investment epistemology, i.e. capital. Defines and analyses the concept of multidimensional capital and develops the notion of how to model dynamic networks of interacting active units, w hich self‐organize a multidimensional field into which systemic strategies of investment can be inserted