Better Sharing Through Licenses? Measuring the Influence of Creative Commons Licenses on the Usage of Open Access Monographs


Introduction :  Open Access and licenses are closely intertwined. Both Creative Commons (CC) and Open Access seek to restore the balance between the owners of creative works and prospective users. Apart from the legal issues around CC licenses, we could look at role of intermediaries whose work is enabled through CC licenses. Does licensing documents under Creative Commons increase access and reuse in a direct way, or is access and reuse amplified by intermediaries?

OAPEN Library and DOAB The OAPEN Library contains books available under both open licenses, for example Creative Commons, as well as books that are published under terms that only allow for personal use. The Directory of Open Access Books (DOAB) functions as an intermediary, offering aggregation services exclusively focused on books with an open license.

Methods: Downloads are used as a proxy for the use of books in the OAPEN Library. The data set that this paper analyses data that was captured over a period of 33 months. During this time, 1734 different books were made available through the OAPEN Library: 855 books under a Creative Commons license and 879 books under a more restrictive regime. The influence of open licenses, aggregation in DOAB, and subject and language are evaluated.

Results :  Once the effects of subject and language are taken into account, there is no evidence that making books available under open licenses results in more downloads than making books available under licenses that only allow for personal use. Yet, additional aggregation in the DOAB has a large positive effect on the number of times a book is downloaded.

Conclusion : The application of open licenses to books does not, on its own, lead to more downloads. However, open licenses pave the way for intermediaries to offer new discovery and aggregation services. These services play an important role by amplifying the impacts of open access licensing in the case of scholarly books.”

URL : Better Sharing Through Licenses? Measuring the Influence of Creative Commons Licenses on the Usage of Open Access Monographs


A systematic review of barriers to data sharing in public health


Background : In the current information age, the use of data has become essential for decision making in public health at the local, national, and global level. Despite a global commitment to the use and sharing of public health data, this can be challenging in reality. No systematic framework or global operational guidelines have been created for data sharing in public health. Barriers at different levels have limited data sharing but have only been anecdotally discussed or in the context of specific case studies. Incomplete systematic evidence on the scope and variety of these barriers has limited opportunities to maximize the value and use of public health data for science and policy.

Methods : We conducted a systematic literature review of potential barriers to public health data sharing. Documents that described barriers to sharing of routinely collected public health data were eligible for inclusion and reviewed independently by a team of experts. We grouped identified barriers in a taxonomy for a focused international dialogue on solutions.

Results : Twenty potential barriers were identified and classified in six categories: technical, motivational, economic, political, legal and ethical. The first three categories are deeply rooted in well-known challenges of health information systems for which structural solutions have yet to be found; the last three have solutions that lie in an international dialogue aimed at generating consensus on policies and instruments for data sharing.

Conclusions : The simultaneous effect of multiple interacting barriers ranging from technical to intangible issues has greatly complicated advances in public health data sharing. A systematic framework of barriers to data sharing in public health will be essential to accelerate the use of valuable information for the global good.”

URL : A systematic review of barriers to data sharing in public health

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A Reputation Economy: Results from an Empirical Survey on Academic Data Sharing


“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.”


The Educational Value of Truly Interactive Science Publishing


“Interactive Scientific Publishing (ISP) has been developed by the Optical Society of America with support from the National Library of Medicine at NIH. It allows authors to electronically publish papers which are linked to the referenced 2D and 3D original image datasets. These image datasets can then be viewed and analyzed interactively by the reader. ISP provides the software for authors to assemble and link their source data to their publication. But more important is that it provides readers with image viewing and analysis tools. The goal of ISP is to improve learning and understanding of the presented information. This paper describes ISP and its effect on learning and understanding. ISP was shown to have enough educational value that readers were willing to invest in the required set–up and learning phases. The social aspects of data sharing and the enlarged review process may be the hardest obstacles to overcome.”


Hybrid Review: Taking SoTL Beyond Traditional Peer Review for Journal Publication


“Developments in emergent technology offer innovative solutions for facilitating a hybrid review process; we examine a unique combination of private–peer and open–public review uniquely relevant for disseminating the scholarship of teaching and learning (SoTL) through development of the Journal of Instructional Research (JIR). An analysis of the hybrid review process (combining the strengths of traditional peer review with an integrative public review process) revealed substantial reviewer participation that contributed to a well–rounded, engaged review process. Public review feedback constructively addressed the value and relevance of the implications, methodology, content and written quality of the manuscripts; an additional layer of private, peer review further refined the manuscripts to determine suitability for publication. This, in turn, created a space where refinement of content, structure, and design of SoTL research was achieved through an interactive process of scholarly inquiry and dialogue.”


Faire parler les données des bibliothèques : du Big Data à la visualisation de données


“Cette étude se penche sur les enjeux de la réutilisation des données des bibliothèques à l’ère du Big Data. En ce qui concerne la production de connaissances sur le monde des bibliothèques et de l’information, les technologies d’analyse du Big Data, contrairement à ce que prétendent les discours qui peuvent parfois les accompagner, ne réduisent pas les biais et présupposés inhérents aux statistiques traditionnelles. Cependant, la visualisation de données, telle que revue et critiquée par les Humanités Numériques, pourrait permettre de prendre en compte d’une manière beaucoup plus centrale la nature fondamentalement politique des bibliothèques. Regardant le pilotage des établissements documentaires, certains auteurs appellent à fonder les décisions non sur les données et chiffres mais sur l’analyse de données. De fait, l’ouverture de la profession de bibliothécaire sur la science des données pourrait être un bon moyen de faire évoluer les méthodes d’évaluation et de pilotage. La visualisation est un moyen ludique d’apprendre l’analyse de donnée et permet de communiquer efficacement sur l’activité de l’établissement. En dernier lieu, les discours actuels accompagnant l’ère du numérique font l’apologie d’un accès individualisé et fragmenté à l’information qui permettrait de se passer des biais inhérents à toute classification universelle. Néanmoins, ces biais sont transposé dans les algorithmes de recherche de l’information. Dès lors, il devient nécessaire de penser un système de navigation qui exprime ce biais et le soumette davantage à une discussion : transformer un catalogue de bibliothèque en data game pourrait être une solution pour exprimer de manière ludique la métaphore sous-jacente à toute organisation des connaissances.”


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What Drives Academic Data Sharing?


“Despite widespread support from policy makers, funding agencies, and scientific journals, academic researchers rarely make their research data available to others. At the same time, data sharing in research is attributed a vast potential for scientific progress. It allows the reproducibility of study results and the reuse of old data for new research questions. Based on a systematic review of 98 scholarly papers and an empirical survey among 603 secondary data users, we develop a conceptual framework that explains the process of data sharing from the primary researcher’s point of view. We show that this process can be divided into six descriptive categories: Data donor, research organization, research community, norms, data infrastructure, and data recipients. Drawing from our findings, we discuss theoretical implications regarding knowledge creation and dissemination as well as research policy measures to foster academic collaboration. We conclude that research data cannot be regarded as knowledge commons, but research policies that better incentivise data sharing are needed to improve the quality of research results and foster scientific progress.”

URL : What Drives Academic Data Sharing?

DOI :10.1371/journal.pone.0118053