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Universities play an important role in the promotion and implementation of the 2030 Agenda for Sustainable Development. This study aims to examine the visibility of information about the Sustainable Development Goals (SDGs) on the websites of Spanish and major international universities, by means of a quantitative and qualitative analysis with an online visibility management platform that makes use of big data technology.

The Web visibility of the universities studied in relation to the terms “SDG”, “Sustainable Development Goals” and “2030 Agenda” was determined using the SEMrush tool. Information was obtained on the number of web pages accessed and the queries formulated (query expansion). The content indexed by Google for these universities was compiled, and finally, the search engine optimization (SEO) factors applicable to the websites with the highest Web visibility were identified.

The universities analysed are content creators but do not have very high Web visibility in Web searches for information on the SDGs. Of the 98 universities analysed, only four feature prominently in search results.

Although research exists on the application of SEO to different areas, there have not, to date, been any studies examining the Web visibility of universities in relation to Web searches for information on the 2030 Agenda. The main contributions of this study are the global perspective it provides on the Web visibility of content produced by universities about the SDGs and the recommendations it offers for improving that visibility.

The field of website quality evaluation attracts the interest of a range of disciplines, each bringing its own particular perspective to bear. This study aims to identify the main characteristics – methods, techniques and tools – of the instruments of evaluation described in this literature, with a specific concern for the factors analysed, and based on these, a multipurpose model is proposed for the development of new comprehensive instruments.

Following a systematic bibliographic review, 305 publications on website quality are examined, the field's leading authors, their disciplines of origin and the sectors to which the websites being assessed belong are identified, and the methods they employ characterised.

Evaluations of website quality tend to be conducted with one of three primary focuses: strategic, functional or experiential. The technique of expert analysis predominates over user studies and most of the instruments examined classify the characteristics to be evaluated – for example, usability and content – into factors that operate at different levels, albeit that there is little agreement on the names used in referring to them.

Based on the factors detected in the 50 most cited works, a model is developed that classifies these factors into 13 dimensions and more than 120 general parameters. The resulting model provides a comprehensive evaluation framework and constitutes an initial step towards a shared conceptualization of the discipline of website quality.

Controlled vocabularies play an important role in information retrieval. Numerous studies have shown that conceptual searches based on vocabularies are more effective than keyword searches, at least in certain contexts. Consequently, new ways must be found to improve controlled vocabularies. The purpose of this paper is to present a semi-automatic model for updating controlled vocabularies through the use of a text corpus and the analysis of query logs.

An experimental development is presented in which, first, the suitability of a controlled vocabulary to a text corpus is examined. The keywords entered by users to access the text corpus are then compared with the descriptors used to index it. Finally, both the query logs and text corpus are processed to obtain a set of candidate terms to update the controlled vocabulary.

This paper describes a model applicable both in the context of the text corpus of an online academic journal and to repositories and intranets. The model is able to: first, identify the queries that led users from a search engine to a relevant document; and second, process these queries to identify candidate terms for inclusion in a controlled vocabulary.

Ideally, the model should be used in controlled web environments, such as repositories, intranets or academic journals.

The proposed model directly improves the indexing process by facilitating the maintenance and updating of controlled vocabularies. It so doing, it helps to optimise access to information.

The proposed model takes into account the perspective of users by mining queries in order to propose candidate terms for inclusion in a controlled vocabulary.

The purpose of this paper is to describe and evaluate the tool DigiDoc MetaEdit which allows the semi-automatic indexing of HTML documents. The tool works by identifying and suggesting keywords from a thesaurus according to the embedded information in HTML documents. This enables the parameterization of keyword assignment based on how frequently the terms appear in the document, the relevance of their position, and the combination of both.

In order to evaluate the efficiency of the indexing tool, the descriptors/keywords suggested by the indexing tool are compared to the keywords which have been indexed manually by human experts. To make this comparison a corpus of HTML documents are randomly selected from a journal devoted to Library and Information Science.

The results of the evaluation show that there: first, is close to a 50 per cent match or overlap between the two indexing systems, however, if you take into consideration the related terms and the narrow terms the matches can reach 73 per cent; and second, the first terms identified by the tool are the most relevant.

The tool presented identifies the most important keywords in an HTML document based on the embedded information in HTML documents. Nowadays, representing the contents of documents with keywords is an essential practice in areas such as information retrieval and e-commerce.