Library websites increasingly serve as the point of contact between the library and its users [1]. An academic library website represents the online portal to the many resources, both digital and analogue, that are offered to students, researchers and other users [2,3]. Being able to locate relevant information on research library websites is crucial for students, researchers and other users when approaching the library website. Thus, the library website is the gateway to the online information and resources that are necessary when acting within the academic world [4,5].
Labelling is one of several elements that ensure the usability of academic library websites [3]. It has previously been shown how terminology and labelling on library websites challenge usability [3,[6][7][8]. The Danish National Statistics Office lists 22 Danish research libraries with special obligations. Most are connected to higher education institutions, such as universities and university colleges. The remaining libraries are associated with national museums for history and various aspects of the arts, except for one, which serves as the national library of D enmark and a university library for several universities across the country. The aim of this paper is to study the use of labels on Danish academic library websites. It sheds light on the characteristics of academic library labels and on how libraries differ in their use of labels in terms of communicating with their users.
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The Danish National Statistics Office lists 22 libraries as research libraries with special responsibilities. We based the selection of libraries on the 2019 statistics. One library, the Danish School of Media and Journalism Library, could not be crawled by the web crawler due to technical issues. This left 21 libraries for the empirical part of this paper.
The libraries with abbreviations are listed in Table 1. To ensure the most extensive versions of the websites, we used the Danish version for the current analysis. Most of the websites offer English counterparts, but they usually contain limited information compared to the Danish equivalents.
We collected the data on 3 September 2020. We used an open access web menu crawler (http://webscompare.com/) to crawl the selected websites. The crawler scrapes category labels using Xpath [17] on the basis of one or several web addresses entered into the interface. The output is a csv file with a flat, alphabetical list of the labels found on the websites. After the data collection, the data was cleaned and prepared for data analysis. The scraper is not capable of handling Danish special letters (AE, Ø, Å), which are commonly used across the websites in this study, and it replaces the special letter with a blank space. The blanks were therefore manually replaced with the correct special letters.
The data analysis consisted of two elements. First, we carried out a quantitative content analysis of the web categories [18,19], analysing per library the number of categories, the average length of categories and the average number of terms in the categories. Subsequently, we used the text analysis functionality of the analysis software NVivo (version 12 Pro) (https://www.qsrinternational.com/nvivo-qualitative-dataanalysis-software/home) for analyses at the term level. Specifically, we used the word frequency functionality and analysed the 1000 most frequent terms in the dataset. We used grouping with synonyms to consider similar terms as one. The analysis was carried out using the Danish language, and the most frequent categories were subsequently translated into English for reporting in the current paper. Subsequently, we carried out a cluster analysis on the basis of word similarity to identify similar libraries.
The libraries included for analysis serve different purposes (Table 1). Six libraries qualify as university college libraries, eight are located at universities or university-like institutions, and six libraries serve different organisations or museums. The Royal Library has a role both as the national library of Denmark and the university library for several Danish universities, resulting in two labels in the table: university library and other. In many of the library cases, their organisational relations appear from the placement of the library website in the web structure. All the UNI and OTHER libraries (14 of the 21 libraries) are incorporated into their host institution websites. The remaining seven libraries, meaning all the UC libraries and the Danish Royal Library, have independent websites with no institutional connection to their host organisation (Figure 1).
Crawling the 21 research libraries, we found the distribution of categories that appears in Table 2. The table shows a large variation in the number of labels on the library websites and an average of 98.76 labels per website. A standard deviation of 84.97 illustrates the large variation between the libraries.
We used the independent sample T-test to test if the variation was related to whether the library website is incorporated into the host organisation's website or has its own website. With no significant difference identified for the number of labels, the average length of labels or the average number of terms in labels, this does not appear to be the case.
We used the term frequency functionality in NVivo to identify high-frequency terms in the data set. The results of the analysis appear in Figure 2. "Search" and variations of "Library" are the most frequent terms along with other library-related terms like "Archive", "Books", "Materials" and "Journals". Another category of high-frequency terms relates to the library as a service function. This category is exemplified by terms like "Way" (representing street names and wayfinding in Danish), "Contact", "Booking", and "Opening", inviting users to use the library and library services like assistance from a trained librarian. The organisational attachment of many of the libraries is also reflected in the most frequent terms in labels. Here we see the university abbreviations ("SDU", "DTU" and "CBS") and "Research", "Education" and "Student".
Furthermore, we analysed the number of libraries in which the high-frequency terms occurred (Figure 3). This figure, to some extent, changes the impression of the most frequent terms. As would be expected, the institution-specific terms only appear in the related libraries, whereas general library-specific terms are used more generally across the included libraries, with "Library", "Search" and "Contact" as the most used terms.
We used the clustering functionality in NVivo to analyse the similarity between the selected libraries. The results of the analysis appear in Figure 4, which illustrates the two main clusters that evolved from the analysis. The upper cluster consists of all the university college libraries in the population. It is interesting to identify how the purpose and the target group of the library actually influences the choice of terminology at these libraries. The lower and larger cluster consists of a combination of university libraries and the category "other". Here, the picture is a bit more muddled than the upper cluster of the figure, but still some observations can be made. For instance, the Danish Film Institute (CINEMA) and the Design Museum (DESMUS) libraries are so similar that they end up in the same cluster. If the next level of the cluster is considered, they are also connected to another museum, the Royal Danish Defence Academy Library (FB). Likewise, the Aarhus School of Architecture Library (AARCH) and the Royal Danish Academy of Fine Arts Library (KADK), which amongst others are connected to architecture education in Copenhagen, are also so similar that they share a cluster in the figure.
Our analysis shows that the academic libraries with special obligations in Denmark serve various institutions and purposes. They represent a large variation in their use of labels, both in numbers and variety. Previous research has identified challenges with library jargon on academic library websites [e.g. 16]. Considering the most frequent labels used in the current study, the deliberate use of terminology does not appear to be prevalent. However, users should be involved in further studies to obtain a deeper understanding of this issue. The cluster analysis revealed that academic libraries with similar purposes also tend to be similar in their use of labelling. Independent sample T-tests did not reveal that this can be explained by whether the libraries are incorporated into their host institutions' websites and thereby have institution labels as part of their pool of labels. Instead, it seems that the specific use of labels is similar, for instance, between university college libraries, between some museum libraries and between the two Danish schools of architecture. The findings indicate that the libraries in their labelling draw on a shared terminology within their domains, which is a step towards reducing the vocabulary problem in information interaction. Further studies with users within the specific domains can further elaborate on how they understand and experience the vocabulary problem within their domains.