Open informational ecosystems play a crucial role in fostering open educational resources (OER) and allow new opportunities to share and collaborate in the learning and teaching environment. Such ecosystems containing interoperable infrastructures and open interfaces aim at fulfilling user needs and fostering practices related to the concept of OER and the five user rights (5 R’s). To fully embrace this role, those ecosystems need to be designed carefully.In this paper, we discuss implications for open informational ecosystems to fully comprise the concept of OER and related user needs. We carried out literature reviews to analyse recent aspects of the 5 R’s in relation to user behaviour and infrastructures. We will introduce the results from these reviews and illustrate upcoming questions and challenges for the design of an ecosystem respecting the 5 R’s conceptual ideas. With our recommendations, we aim at contributing to a better understanding of the concept of OER to improve ecosystem development and implement useful and user-friendly functions.

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Aspects of open science and scholarly practices are often discussed with a focus on research and research dissemination processes. There is currently less discussion on open science and its influence on learning and teaching in higher education, and reversely. This paper discusses open science in relation to educational practices and resources and reports on a study to investigate current educational practices from the perspective of open science. We argue that offering students opportunities via open educational practices raises their awareness of future open science goals and teaches them the skills needed to reach those goals. We present online survey results from 210 participants with teaching responsibility at higher education institutions in Germany. While some of them try to establish more open learning and teaching settings, most respondents apply rather traditional ways of learning and teaching. 60% do not use open educational resources – many have not even heard of them – nor do they make their courses open for an online audience. Participants’ priority lies in resource accuracy and quality and we still see a gap between the benefit of open practices and their practicability and applicability. The paper contributes to the general discussion of open practices in higher education by looking at open science practices and their adaptation to the learning and teaching environment. It formulates recommendations for improvements of open practice support and infrastructure.

Recommendation systems are not only important in ecommerce, but in academia as well: They support scientists in finding relevant literature and also potential collaboration partners. It is essential that such a recommendation system proposes the most relevant people. Scientometric similarity measurements like co-citation and bibliographic coupling analysis have proved to give a good representation of research activities and hence it can be said that they put authors with similar research together and detect possible collaborations. Our aim is to implement a recommendation system for a target author who searches for collaboration colleagues. The research question is: 1) Can we propose a relevant author cluster for a target scientist? Furthermore we try to apply user data from the social bookmarking system CiteULike. The second research question is: 2) Is this user-based data also relevant for our target scientist and does it recommend different results? Our first outcomes of this work in progress are evaluated by our target authors.

Editormetrics analyse the role of editors of academic journals and their impact on the scientific publication system. However, such analyses would best rely on open, structured and machine-readable data on editors and editorial boards, whose availability still remains rare. To address this shortcoming, the project Open Editors collects data about academic journal editors on a large scale and structures them into a single dataset. It does so by scraping the websites of 6.090 journals from 17 publishers, thereby structuring publicly available information (names, affiliations, editorial roles etc.) about 478.563 researchers. The project will iterate this webscraping procedure annually to enable insights into the changes of editorial boards over time. All codes and data are made available at GitHub, while the result is browsable at a dedicated website (https://openeditors.ooir.org). This dataset carries wide-ranging implications for meta-scientific investigations into the landscape of scholarly publications, including for bibliometric analyses, and allows for critical inquiries into the representation of diversity and inclusivity. It also contributes to the goal of expanding linked open data within science to evaluate and reflect on the scholarly publication process.