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Academic data sharing is a way for researchers to collaborate and thereby meet the needs of an increasingly complex research landscape. It enables researchers to verify results and to pursuit new research questions with "old" data. It is therefore not surprising that data sharing is advocated by funding agencies, journals, and researchers alike. We surveyed 2661 individual academic researchers across all disciplines on their dealings with data, their publication practices, and motives for sharing or withholding research data. The results for 1564 valid responses show that researchers across disciplines recognise the benefit of secondary research data for their own work and for scientific progress as a whole - still they only practice it in moderation. An explanation for this evidence could be an academic system that is not driven by monetary incentives, nor the desire for scientific progress, but by individual reputation - expressed in (high ranked journal) publications. We label this system a Reputation Economy. This special economy explains our findings that show that researchers have a nuanced idea how to provide adequate formal recognition for making data available to others - namely data citations. We conclude that data sharing will only be widely adopted among research professionals if sharing pays in form of reputation. Thus, policy measures that intend to foster research collaboration need to understand academia as a reputation economy. Successful measures must value intermediate products, such as research data, more highly than it is the case now.

This article describes a multi-method approach for usability testing. The approach combines paper prototyping and think-aloud with two supplemental methods: advanced scribbling and a handicraft task. The method of advanced scribbling instructs the participants to use different colors for marking important, unnecessary and confusing elements in a paper prototype. In the handicraft task the participants have to tinker a paper prototype of their wish version. Both methods deliver additional information on the needs and expectations of the potential users and provide helpful indicators for clarifying complex or contradictory findings. The multi-method approach and its surplus benefit are illustrated by a pilot study on the redesign of the homepage of a library 2.0. The findings provide positive evidence for the applicability of the advanced scribbling and the handicraft task as well as for the surplus merit of the multi-method approach. The article closes with a discussion and outlook. (author's abstract), In diesem Artikel wird ein multi-methodischer Ansatz beschrieben, der Paper Prototyping mit zwei zusätzlichen Methoden kombiniert, dem Advanced Scribbling und einem Handicraft Task. Beim Advanced Scribbling [erweitertes, fortgeschrittenes Kritzeln] werden die Untersuchungsteilnehmer/innen instruiert, wichtige, überflüssige und verwirrende Elemente eines Papier-Prototypen mit jeweils unterschiedlichen Farben zu markieren. Für das Handicraft Task [Bastelaufgabe] sollen sie ihre eigene Wunschversion als Papier-Prototyp anfertigen. Beide Methoden liefern zusätzliche Informationen über die Bedürfnisse und Erwartungen der potenziellen Endnutzer/innen und bieten hilfreiche Indikatoren zur Klärung von komplexen oder widersprüchlichen Ergebnissen. Der multi-methodische Ansatz und sein zusätzlicher Mehrwert werden anhand einer Pilot-Studie zur Neugestaltung der Homepage einer modernen Bibliothek (Library 2.0) illustriert. Die Ergebnisse stützen die praktische Anwendbarkeit des Advanced Scribblings und des Handicraft Tasks und liefern zudem positive Evidenz für den Mehrwert des multi-methodischen Ansatzes. Der Artikel schließt mit einer Diskussion und einem Ausblick. (Autorenreferat)

For what reasons do academics follow one another on Twitter? Robert Jäschke, Stephanie B. Linek and Christian P. Hoffmann analysed the Twitter activity of computer scientists and found that while the quality of information provided by a Twitter account is a key motive for following academic colleagues, there is also evidence of a career planning motive. As well as there being reciprocal following between users of the same academic status (except, remarkably, between PhD researchers), a form of strategic politeness can be observed whereby users follow those of higher academic status without necessarily being followed back. The emerging academic public sphere facilitated by Twitter is largely shaped by dynamics and hierarchies all too familiar to researchers struggling to plot their careers in academia.

Despite strong support from funding agencies and policy makers academic data sharing sees hardly any adoption among researchers. Current policies that try to foster academic data sharing fail, as they try to either motivate researchers to share for the common good or force researchers to publish their data. Instead, Dr Sascha Friesike, Benedikt Fecher, Marcel Hebing, and Stephanie Linek argue that in order to tap into the vast potential that is attributed to academic data sharing we need to forge new policies that follow the guiding principle reputation instead of obligation.