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The purpose of this paper is to give a structured literature review, design concepts, and research propositions related to a product‐oriented design theory for information services. Information services facilitate the exchange of information goods with or without transforming these goods. Exemplar information services are e‐publishing, electronic communities‐of‐practice, and management reporting. The importance of information services in the current economy merits the development of an explicit product‐ and process‐oriented design theory.

This article focuses on the product‐oriented design theory by applying Walls et al.'s framework. A product‐oriented design theory of information services identifies relevant descriptive and explanatory insights (i.e. content, use, value, and revenue), meta‐requirements, and meta‐designs. The paper describes design problems for information services, and gives key requirements for information services. Next, it describes the information, organizational and information technological components of an information service, and identifies at least four information service architectures. Finally, it gives research hypotheses, research ideas, and discusses practical implications.

The results form a product‐oriented design theory for information services. The paper gives a structured way for practitioners to analyze information service design challenges, and suggestions are given for requirements and design decisions on three aspects (content, use feature, and revenue).

Given the previously fragmented nature of the literature, this paper gives new opportunities for research and practice.

Having considered various types of pedagogy as well as technology affordances and multimedia learning principles, this chapter focuses on issues surrounding the representation and sharing of content using technology. Anderson & Krathwohl’s (2001) Taxonomy of Learning, Teaching and Assessing is examined as a means of conceptualizing different types of thinking processes in a way that can be applied across discipline areas. The representational requirements of different subject areas (English, mathematics, science, history, geography, and computing) are explored by means of examples, with reference to the role of technology and the range of possible tasks that may be utilized. Assessment issues as they relate to the representation of content are also considered. The broader contextual shift toward open education and sharing is discussed, including key drivers such as learning object repositories, open educational resources, Creative Commons licensing, and massive open online courses.

The purpose of this paper is to identify the unique d

mensions associated with knowledge quality (KQ) based on students’ perception in an educational institution.

Purposive sampling was used to select students who were active users of the electronic-Learning (eLearning) system at two faculties in a single university. The qualitative data gathering employed an unstructured open-ended questionnaire distributed to the 52 selected participants.

The qualitative findings unearth the students’ perspective about quality of knowledge gained from content used in online courses. In total, 34 underlying sub-dimensions of KQ emerged, which were categorized into five KQ dimensions: intrinsic KQ, contextual KQ, representational KQ, accessible KQ, and actionable KQ.

The findings provide an insight to educators to consider KQ dimensions in providing quality knowledge to students in an eLearning environment.

Previous studies have used information quality dimensions to measure KQ because of a lack of conceptualization of KQ that leads to difficulties in operationalizing this construct. In this study, a conceptual and operational definition of KQ, in the context of eLearning, is proposed based on grounded data from students participating in an online learning environment.

This paper seeks to present a modeling approach for e‐learning content, describing how to structure e‐learning content and also represent it in OWL DL.

This paper presents three different layers of information that should be considered in e‐learning and conceptual models to guide the representation of e‐learning content. This proposal is based on existing standards and experience gained in previous works. It is also shown how to structure and represent the content embedded in learning objects (LOs).

Besides providing a better structuring of the e‐learning content, content reuse and exploratory navigations over content through the semantic relationships between information (mainly information objects (IOs) and conceptual units) are promoted.

A visual tool to allow a better exploration of the e‐learning content is already being developed. However, it is essential to develop optimized storing and retrieving mechanisms that would make this approach more interesting.

When compared with other approaches such as those based on semantic models and deductive models, the decrease in complexity makes acceptance and adoption of this approach by teachers and instructional designers easier.

This paper fulfils an identified three‐level information need for e‐learning content and presents a new modeling approach. Besides structuring the e‐learning content, the model is also represented in OWL DL. It allows an easier/richer implementation of e‐learning content.

The purpose of this paper is to present a conceptual model for coding and dissemination of data associated with historical photographic archives. The model is based on Linked Open Data technology and seeks to exhaustively represent the most relevant characteristics for the tasks of contextualization of the documentary groupings and units, management, document retrieval, dissemination and sharing of data about the historical photographs.

An OWL ontology, called Ontophoto, was constructed following an adaptation of the methodology proposed by Uschold and Gruninger and Gruninger and Fox. The ontology was implemented using Protégé 5.5 software. Next a Graph DB® graph database application (Ontotext) was created to generate a query system based on the SPARQL language. To validate the consistency and effectiveness of the model and ontology, a competency questions methodology has been applied using a sample from the Skogler photographic archive.

The model facilitates the generation of systems for dissemination and retrieval of iconographic data for historical research, overcoming some of the limitations with respect to the design of methods of content and contextual information representation for heritage photographic archives.

This study is based on a sample. Future work should consider the implementation of the model on the totality of a photographic collection.

This paper presents a comprehensive ontological model that allows the creation of distributed systems of knowledge representation, which can be queried through SPARQL language.

The goal of the research is to explore whether the use of higher‐level semantic features can help us to build better self‐organising map (SOM) representation as measured from a human‐centred perspective. The authors also explore an automatic evaluation method that utilises human expert knowledge encapsulated in the structure of traditional textbooks to determine map representation quality.

Two types of document representations involving semantic features have been explored – i.e. using only one individual semantic feature, and mixing a semantic feature with keywords. Experiments were conducted to investigate the impact of semantic representation quality on the map. The experiments were performed on data collections from a single book corpus and a multiple book corpus.

Combining keywords with certain semantic features achieves significant improvement of representation quality over the keywords‐only approach in a relatively homogeneous single book corpus. Changing the ratios in combining different features also affects the performance. While semantic mixtures can work well in a single book corpus, they lose their advantages over keywords in the multiple book corpus. This raises a concern about whether the semantic representations in the multiple book corpus are homogeneous and coherent enough for applying semantic features. The terminology issue among textbooks affects the ability of the SOM to generate a high quality map for heterogeneous collections.

The authors explored the use of higher‐level document representation features for the development of better quality SOM. In addition the authors have piloted a specific method for evaluating the SOM quality based on the organisation of information content in the map.

This study explores how digital storytelling (DST) approaches can be used for social media campaigns to create more engaging digital content. The ability to better engage with networked publics offers benefits to entities of different scale and scope, since in doing so they establish stronger relationships with their consumers and publics.

A digital discourse analysis combined with a five-layer coded film analysis is applied to a DST video, viewed on Facebook.

Four overarching and overlapping approaches are identified. These are emotional appeal based on clear human ideals, equality and simplicity of characters, simplicity and universal representations.

Similar studies are required across varying targeted digital stories of different length and subject matter to distinguish effectiveness.

Despite advanced technological capacity for audience segmentation, social media campaigns often include unengaging content. DST offers universal characteristics that can be used by entities to engage with their consumers and publics.

DST has been used to create learning and pedagogical environments and more participative democracies. Yet its use to strategically engage with networked publics is empirically lacking. The findings of the study can facilitate more effective digital content strategies for entities of all purposes to pursue.

Few studies have sought to deconstruct effective short form DST for strategic purposes. This study applies a methodological approach best suited for analysing digital content. The findings provide insights into how strategists and social media managers can create more engaging digital content.

In this article, we develop and advance an understanding of institutions as multimodal accomplishments. We draw on social semiotics and the linguistic concept of metafunctions to establish the visual as a specific mode of meaning construction. In addition, we make semiotic modes conducive to institutional inquiry by introducing the notion of distinct “modal registers” – specialized configurations of linguistic signs within a particular mode that are adapted and applied in the reproduction of institutions or institutional domains. At the core of our article, we operationalize metafunctions to develop methodology for the analysis of visual registers. We illustrate our approach with data from Corporate Social Responsibility (CSR) reporting in Austria.

The analysis of multimedia content is being applied in various real-time computer vision applications. In multimedia content, digital images constitute a significant part. The representation of digital images interpreted by humans is subjective in nature and complex. Hence, searching for relevant images from the archives is difficult. Thus, electronic image analysis strategies have become effective tools in the process of image interpretation.

The traditional approach used is text-based, i.e. searching images using textual annotations. It consumes time in the manual process of annotating images and is difficult to reduce the dependency in textual annotations if the archive consists of large number of samples. Therefore, content-based image retrieval (CBIR) is adopted in which the high-level visuals of images are represented in terms of feature vectors, which contain numerical values. It is a commonly used approach to understand the content of query images in retrieving relevant images. Still, the performance is less than optimal due to the presence of semantic gap among the image content representation and human visual understanding perspective because of the image content photometric, geometric variations and occlusions in search environments.

The authors proposed an image retrieval framework to generate semantic response through the feature extraction with convolution network and optimization of extracted features using adaptive moment estimation algorithm towards enhancing the retrieval performance.

The proposed framework is tested on Corel-1k and ImageNet datasets resulted in an accuracy of 98 and 96%, respectively, compared to the state-of-the-art approaches.

The purpose of this paper is to examine the integration of digital library (DL) technologies with ontology‐based knowledge representation in providing semantic rich information access (IA) in e‐learning. DL technologies have powerful and flexible content management and access functionalities, whereas ontology helps teachers and students to link content materials to their learning objectives. This paper demonstrates that the integration provides a powerful and meaningful e‐learning environment.

DiLight is designed as an interactive e‐learning system that integrates DL and ontology technologies. By conducting comparative experiments involving DiLight in students' actual learning process, the authors examined the advantages and limitations of DiLight in e‐learning.

Compared to a widely used e‐learning environment, DiLight can provide significantly better support for students' complex IA tasks because DiLight is more useful for relationship discovery and problem solving. DiLight is also effective even when students were either less familiar with tasks or felt that they were more difficult. There is no single best access method for all learning situations. Therefore, multiple IA methods should be built into e‐learning systems. Although most of time the search was the first choice of the students, ontology‐based methods were useful in supporting them to complete their tasks too.

This is a comparative empirical study using an interactive e‐learning system called DiLight to explore the usage of integrated DL and ontology in e‐learning. The experiment results demonstrate the value of the multiple IA methods provided by DL, and the usefulness of integrating DL with ontology.