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The purpose of this paper is to open the special issue of Online Information Review on open knowledge management in higher education. Its aim is to review the concept and extension of the movement or philosophy of open knowledge in universities and higher education institutions.

The approach follows the reference model used by the University of Salamanca (Spain) to promote open knowledge in the institution through its Open Knowledge Office. This model comprises four areas: free software, open educational content and cultural dissemination, open science, and open innovation.

For each of the four areas mentioned above, milestones and the most significant projects are presented, showing how they are promoting publication and information transmission in an open environment, without restrictions and favouring knowledge dissemination in all fields.

Open knowledge is an approach which, although somewhat controversial, is growing relentlessly as cultural and scientific dissemination leave behind other interests or economic models. International organisations and governments are gradually embracing open knowledge as the way to share scientific advances with society and as an international cooperative way to assist development in third‐world countries.

Automatic categorisation can be understood as a learning process during which a program recognises the characteristics that distinguish each category or class from others, i.e. those characteristics which the documents should have in order to belong to that category. As yet few experiments have been carried out with documents in Spanish. Here we show the possibilities of elaborating pattern vectors that include the characteristics of different classes or categories of documents, using techniques based on those applied to the expansion of queries by relevance; likewise, the results of applying these techniques to a collection of documents in Spanish are given. The same collection of documents was categorised manually and the results of both procedures were compared.

The concept of sustainable development (SD) is a popular response to society’s need to preserve and extend the life span of natural resources. One of the 17 goals of the SD is “education quality” (Fourth Goal of Sustainable Development [SDG-4]). Education quality is an important goal because education is a powerful force that can influence social policies and social change. The SDG-4 must be measured in different contexts, and the tools to quantify its effects require exploration. So, this study aims to propose a statistical model to measure the impact of higher education online courses on SD and a structural equation model (SEM) to find constructs or factors that help us explain a sustainability benefits rate. These proposed models integrate the three areas of sustainability: social, economic and environmental.

A beta regression model suggests features that include the academic and economic opportunities offered by the institution, the involvement in research activities and the quality of the online courses. A structural equation modelling (SEM) analysis allowed selecting the key variables and constructs that are strongly linked to the SD.

One of the key findings showed that the benefit provided by online courses in terms of SD is 62.99% higher than that of offline courses in aspects such as transportation, photocopies, printouts, books, food, clothing, enrolment fees and connectivity.

The SEM model needs large sample sizes to have consistent estimations. Thus, despite the obtained estimations in the proposed SEM model being reliable, the authors consider that a limitation of this study was the required time to collect data corresponding to the estimated sample size.

This study proposes two novel and different ways to estimate the sustainability benefits rate focused on SDG-4, and machine learning tools are implemented to validate and gain robustness in the estimations of the beta model. Additionally, the SEM model allows us to identify new constructs associated with SDG-4.

The aim of this paper is to present an initiative to apply the principles of Linked Data to enhance the search and discovery of OpenCourseWare (OCW) contents created and shared by the universities.

This paper is a case study of how linked data technologies can be applied for the enhancement of open learning contents.

Results presented under the umbrella of OCW-Universia consortium, as the integration and access to content from different repositories OCW and the development of a query method to access these data, reveal that linked data would offer a solution to filter and select semantically those open educational contents, and automatically are linked to the linked open data cloud.

The new OCW-Universia integration with linked data adds new features to the initial framework including improved query mechanisms and interoperability.

This paper aims to determine if the digital humanities technique of topic modeling would reveal interesting patterns in a corpus of library-themed literature focused on the future of libraries and pioneer a collaboration model in librarian-led digital humanities projects. By developing the project, librarians learned how to better support digital humanities by actually doing digital humanities, as well as gaining insight on the variety of approaches taken by researchers and commenters to the idea of the future of libraries.

The researchers collected a corpus of over 150 texts (articles, blog posts, book chapters, websites, etc.) that all addressed the future of the library. They ran several instances of latent Dirichlet allocation style topic modeling on the corpus using the programming language R. Once they produced a run in which the topics were cohesive and discrete, they produced word-clouds of the words associated with each topic, visualized topics through time and examined in detail the top five documents associated with each topic.

The research project provided an effective way for librarians to gain practical experience in digital humanities and develop a greater understanding of collaborative workflows in digital humanities. By examining a corpus of library-themed literature, the researchers gained new insight into how the profession grapples with the idea of the future and an appreciation for topic modeling as a form of literature review.

Topic modeling a future-themed corpus of library literature is a unique research project and provides a way to support collaboration between library faculty and researchers from outside the library.