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In recent years, OpenGLAM and the broader open license movement have been gaining momentum in the cultural heritage sector. The purpose of this paper is to examine OpenGLAM from the perspective of end users, identifying barriers for commercial and non-commercial reuse of openly licensed art images.

Following a review of the literature, the authors scope out how end users can discover institutions participating in OpenGLAM, and use case studies to examine the process they must follow to find, obtain and reuse openly licensed images from three art museums.

Academic literature has so far focussed on examining the risks and benefits of participation from an institutional perspective, with little done to assess OpenGLAM from the end users’ standpoint. The authors reveal that end users have to overcome a series of barriers to find, obtain and reuse open images. The three main barriers relate to image quality, image tracking and the difficulty of distinguishing open images from those that are bound by copyright.

This study focusses solely on the examination of art museums and galleries. Libraries, archives and also other types of OpenGLAM museums (e.g. archaeological) stretch beyond the scope of this paper.

The authors identify practical barriers of commercial and non-commercial reuse of open images, outlining areas of improvement for participant institutions.

The authors contribute to the understudied field of research examining OpenGLAM from the end users’ perspective, outlining recommendations for end users, as well as for museums and galleries.

The purpose of this paper is to investigate the organization and design of a real-life digital collection for the field of Book Arts. This paper also examines the challenges in building digital libraries for visual domains with specialized user pools.

A qualitative study was conducted. An online survey asked participants from the field of Book Arts to provide free-text descriptions of randomized visual representatives taken from the collection using open-ended question and answer boxes. Themes extracted from the survey were coded and presented using basic statistical measures.

The results of this study identified a set of specialized access points for items that were selected as being significant for Book Arts and perhaps other areas in the Fine Arts. Results informed retrieval of visual information for this domain along with user interface design and evaluation strategies. In addition, the survey used in this study demonstrated the ability to collect longer, more in-depth answers and category terms alike from the participants.

This study was necessary for the practical purpose of organizing a digital collection of the Book Arts, a unique collection. While similar studies have been conducted, even for collections deemed to be from the “Fine Arts”, previous studies do not agree on what is important for organizing digital collections including varying opinions of certain bibliographic access points and visual representation.

Analysis of user viewing and query‐matching behavior furnishes additional evidence that the relevance of retrieved images for system users may arise from descriptions of objects and content‐based elements that are not evident or not even present in the image. This investigation looks at how users assign pre‐determined query terms to retrieved images, as well as looking at a post‐retrieval process of image engagement to user cognitive assessments of meaningful terms. Additionally, affective/emotion‐based query terms appear to be an important descriptive category for image retrieval. A system for capturing (eliciting) human interpretations derived from cognitive engagements with viewed images could further enhance the efficiency of image retrieval systems stemming from traditional indexing methods and technology‐based content extraction algorithms. An approach to such a system is posited.

Large cultural heritage datasets from museum collections tend to be biased and demonstrate omissions that result from a series of decisions at various stages of the collection construction. The purpose of this study is to apply a set of ethical criteria to compare the level of bias of six online databases produced by two major art museums, identifying the most biased and the least biased databases.

At the first stage, the relevant data have been automatically extracted from all six databases and mapped to a unified ontological scheme based on Wikidata. Then, the authors applied ethical criteria to the results of the geographical distribution of records provided by two major art museums as online databases accessed via museums' websites, API datasets and datasets submitted to Wikidata.

The authors show that the museums use different artworks in each of its online databases and each data-base has different types of bias reflected by the study variables, such as artworks' country of origin or the creator's nationality. For most variables, the database behind the online search system on the museum's website is more balanced and ethical than the API dataset and Wikidata databases of the two museums.

By applying ethical criteria to the analysis of cultural bias in various museum databases aimed at different audiences including end users, researchers and commercial institutions, this paper shows the importance of explicating bias and maintaining integrity in cultural heritage representation through different channels that potentially have high impact on how culture is perceived, disseminated, contextualized and transformed.

This paper aims to examine how the internet both precipitated and facilitated significant shifts for academic libraries in the kinds of services they provide, and the ways in which they provide access to content. It aims to view this evolution from the perspective of one academic library in an institution that has been at the center of internet and technology development worldwide for over 30 years, the University of Illinois at Urbana‐Champaign.

The first 30 years of the internet in libraries are explored in decade time segments. Each of the three decades is characterized by significant and unique internet developments. Key internet‐based innovations in libraries are explored, in the areas of service, digital libraries, search and discovery. The reasons for the relative impact of these innovations are explored and discussed.

The internet is both foundation and incubator for myriad new social, technical, organizational and legal constructs, including policy and best practices, governance, intellectual property, whole new categories of services, industries, and areas of research. Since diverse stakeholders can participate with little or no investment, the pace of growth and innovation is unpredictable. This pace is sustained over time, occurring on multiple levels. For this reason, the internet does not “grow” simply in one direction, such as exponential user growth, or the systematic installation of infrastructure. In the University of Illinois at Urbana‐Champaign, the internet has fundamentally altered, and continues to enable significant shifts in the direction of the library's programs, services and resources.

This paper contributes to a group of invited papers that addresses the first 30 years of the internet in libraries.

This paper seeks to report on the study that proposed a model of image retrieval tasks for creative multimedia. The aim of this model was to understand the purpose of the tasks, intended use of the images, mode of query submission, nature of the keywords given by the users, and relevance criteria.

A survey was done to compile a total of 35 image retrieval tasks from 35 academic staff members at Faculty of ICT, International Islamic University Malaysia, and Faculty of Creative Multimedia, Malaysia. A search using Google Image Search category was carried out to find images on the web that met the intended use of the academic staff members.

Findings revealed that images were mostly intended for analysis, decorations, design, illustrations, image processing, and inspiration. Users preferred linguistic query mode, and visual query mode if they had a sample of the image. Most users requested images with captions for making the relevance judgment. Technical attributes, topicality, and completeness were the most important relevance criteria. Users' keywords were of abstract and concrete elements, and were expressed in a visual way and as a subject. Images decided as relevant ranged from an object in the image to the whole image. This model reflected similar findings to other studies with some variations.

Results are useful for understanding the nature of image retrieval tasks for the area of creative multimedia.

This paper developed a model of image retrieval tasks in the area of creative multimedia, and offers a value in understanding the tasks that are intended to meet the demand of the Creative Multimedia Industry established in Malaysia.

This study aims to consider the value of user‐assigned image tags by comparing the facets that are represented in image tags with those that are present in image queries to see if there is a similarity in the way that users describe and search for images.

A sample dataset was created by downloading a selection of images and associated tags from Flickr, the online photo‐sharing web site. The tags were categorised using image facets from Shatford's matrix, which has been widely used in previous research into image indexing and retrieval. The facets present in the image tags were then compared with the results of previous research into image queries.

The results reveal that there are broad similarities between the facets present in image tags and queries, with people and objects being the most common facet, followed by location. However, the results also show that there are differences in the level of specificity between tags and queries, with image tags containing more generic terms and image queries consisting of more specific terms. The study concludes that users do describe and search for images using similar image facets, but that measures to close the gap between specific queries and generic tags would improve the value of user tags in indexing image collections.

Research into tagging has tended to focus on textual resources with less research into non‐textual documents. In particular, little research has been undertaken into how user tags compare to the terms used in search queries, particularly in the context of digital images.

Dunhuang murals are rich in cultural and artistic value. The purpose of this paper is to construct a novel mobile visual search (MVS) framework for Dunhuang murals, enabling users to efficiently search for similar, relevant and diversified images.

The convolutional neural network (CNN) model is fine-tuned in the data set of Dunhuang murals. Image features are extracted through the fine-tuned CNN model, and the similarities between different candidate images and the query image are calculated by the dot product. Then, the candidate images are sorted by similarity, and semantic labels are extracted from the most similar image. Ontology semantic distance (OSD) is proposed to match relevant images using semantic labels. Furthermore, the improved DivScore is introduced to diversify search results.

The results illustrate that the fine-tuned ResNet152 is the best choice to search for similar images at the visual feature level, and OSD is the effective method to search for the relevant images at the semantic level. After re-ranking based on DivScore, the diversification of search results is improved.

This study collects and builds the Dunhuang mural data set and proposes an effective MVS framework for Dunhuang murals to protect and inherit Dunhuang cultural heritage. Similar, relevant and diversified Dunhuang murals are searched to meet different demands.

The paper provides a theory base for deriving connotative descriptors for photographs from existing denotative descriptors, and then demonstrates a model for enhancing browsing within image collections by providing a tool for carving up the searching space.

The paper conceptually explores the nature of iconic messages contained in an image by adopting semiotics as a theoretical tool. A problem of image retrieval is identified as loss of connotative messages during the image representation process. The paper proposes an image‐retrieval model utilizing an association thesaurus that facilitates the assignment of connotative index terms by making use of denotative index terms of an image. A series of experiments are performed for evaluating the effectiveness of the proposed model.

Experimental results demonstrate that the association thesaurus improves image‐retrieval effectiveness by increasing the recall of connotatively related image documents as well as the recall of browsing sets.

Applying connotative index terms to an image would be time consuming. Deriving connotative terms from denotative terms and then using them to enrich the browsing environment suggest a method of increasing retrieval effectiveness while reducing the resources required for representation.

Since images are often used to illustrate concepts that are not immediately evident from just the objects in front of the lens, connotative descriptions are particularly valuable. Since human perception of images is, in a sense, hard wired into our brains, browsing is a frequent and reasonable search method in image collections. Using connotative descriptors to point the way to clusters of images with a higher probability of relevance changes the locus of control over representation establishes an environment for dynamic representation, and gives credibility to browsing as a significant search method.

This study aims to examine the differences between web image and textual queries.

A large number of web queries from image and textual search engines were analysed and compared based on their factual characteristics, query types, and search interests.

Useful results include the findings that web users tend to input short queries when searching for visual or textual information; that image requests have more zero hits and higher specificity, and contain more refined queries; that web image requests are more focused than textual requests on some popular search interests, and that the variety of textual queries is greater than that of image requests.

This study provides results that may enhance one's understanding of web‐searching behaviour and the inherent implications for the improvement of current web image retrieval systems.