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The open science movement calls for transparent and retraceable research processes. While infrastructures to support these practices in qualitative research are lacking, the design needs to consider different approaches and workflows. The paper bases on the definition of ontologies as shared conceptualizations of knowledge (Borst, 1999). The authors argue that participatory design is a good way to create these shared conceptualizations by giving domain experts and future users a voice in the design process via interviews, workshops and observations.

This paper presents a novel approach for creating ontologies in the field of open science using participatory design. As a case study the creation of an ontology for qualitative coding schemas is presented. Coding schemas are an important result of qualitative research, and reuse can yield great potential for open science making qualitative research more transparent, enhance sharing of coding schemas and teaching of qualitative methods. The participatory design process consisted of three parts: a requirement analysis using interviews and an observation, a design phase accompanied by interviews and an evaluation phase based on user tests as well as interviews.

The research showed several positive outcomes due to participatory design: higher commitment of users, mutual learning, high quality feedback and better quality of the ontology. However, there are two obstacles in this approach: First, contradictive answers by the interviewees, which needs to be balanced; second, this approach takes more time due to interview planning and analysis.

The implication of the paper is in the long run to decentralize the design of open science infrastructures and to involve parties affected on several levels.

In ontology design, several methods exist by using user-centered design or participatory design doing workshops. In this paper, the authors outline the potentials for participatory design using mainly interviews in creating an ontology for open science. The authors focus on close contact to researchers in order to build the ontology upon the expert's knowledge.

The purpose of this paper is to get a first approximation of the usefulness of online forums with regard to information seeking and knowledge generation.

This study captures the characteristics of knowledge generation by examining the pragmatics and types of information needs of posted questions and by investigating knowledge related characteristics of discussion posts as well as the success of communication. Three online forums were examined. The data set consists of 55 threads, containing 533 posts which were categorized manually by two researchers.

Results show that questioners often ask for personal estimations. Information needs often aim for actionable insights or uncertainty reduction. With regard to answers, factual information is the dominant content type and has the highest knowledge value as it is the strongest predictor with regard to the generation of new knowledge. Opinions are also relevant, but in a rather subsequent and complementary way. Emotional aspects are scarcely observed. Overall, results indicate that knowledge creation predominantly follows a socio-cultural paradigm of knowledge exchange.

Although the investigation captures important aspects of knowledge building processes, the measurement of the forums’ knowledge value is still rather limited. Success is only partly measurable with the current scheme. The central coding category “new topical knowledge” is only of nominal value and therefore not able to compare different kinds of knowledge gains in the course of discussion.

The investigation reaches out beyond studies that do not consider that the role and relevance of posts is dependent on the state of the discussion. Furthermore, the paper integrates two perspectives of knowledge value: the success of the questioner with regard to the expressed information need and the knowledge building value for communicants and readers.

Details have now been released of the six research efforts, developing new technologies for digital libraries, which are being funded for four years by the US government. The Digital Library Project's focus is ‘dramatically to advance the means to collect, store, and organise information in digital forms, and make it available for searching, retrieval and processing via communication networks — all in user‐friendly ways.’

This chapter takes a closer look at the integration process of the Western Balkan states. At first we will look at the procedures to join the EU, followed by some general information about the countries of the Western Balkans. Building on this, the path and the current results of the individual countries towards EU membership are reviewed. At the end, a closer look at the Berlin Process shows a concrete example how the individual Western Balkan states work with the EU. This allows an outlook how the enlargement process might continue in the coming years.

The purpose of this study is to develop a model for automated classification of old digitised texts to the Universal Decimal Classification (UDC), using machine-learning methods.

The general research approach is inherent to design science research, in which the problem of UDC assignment of the old, digitised texts is addressed by developing a machine-learning classification model. A corpus of 70,000 scholarly texts, fully bibliographically processed by librarians, was used to train and test the model, which was used for classification of old texts on a corpus of 200,000 items. Human experts evaluated the performance of the model.

Results suggest that machine-learning models can correctly assign the UDC at some level for almost any scholarly text. Furthermore, the model can be recommended for the UDC assignment of older texts. Ten librarians corroborated this on 150 randomly selected texts.

The main limitations of this study were unavailability of labelled older texts and the limited availability of librarians.

The classification model can provide a recommendation to the librarians during their classification work; furthermore, it can be implemented as an add-on to full-text search in the library databases.

The proposed methodology supports librarians by recommending UDC classifiers, thus saving time in their daily work. By automatically classifying older texts, digital libraries can provide a better user experience by enabling structured searches. These contribute to making knowledge more widely available and useable.

These findings contribute to the field of automated classification of bibliographical information with the usage of full texts, especially in cases in which the texts are old, unstructured and in which archaic language and vocabulary are used.