The characterization of scholarly communication is dominated by citation-based measures. In this paper we propose several metrics to describe different facets of open access and open research.
We discuss measures to represent the public availability of articles along with their archival location, licenses, access costs, and supporting information. Calculations illustrating these new metrics are presented using the authors’ publications.
We argue that explicit measurement of openness is necessary for a holistic description of research outputs.
Authors : Adina Howe, Michael D. Howe, Amy L. Kaleita, D. Raj Raman
As part of a recent workshop entitled « Imagining Tomorrow’s University”, we were asked to visualize the future of universities as research becomes increasingly data- and computation-driven, and identify a set of principles characterizing pertinent opportunities and obstacles presented by this shift.
In order to establish a holistic view, we take a multilevel approach and examine the impact of open science on individual scholars as well as on the university as a whole.
At the university level, open science presents a double-edged sword: when well executed, open science can accelerate the rate of scientific inquiry across the institution and beyond; however, haphazard or half-hearted efforts are likely to squander valuable resources, diminish university productivity and prestige, and potentially do more harm than good. We present our perspective on the role of open science at the university.
Authors : Irene V. Pasquetto, Bernadette M. Randles, Christine L. Borgman
While science policy promotes data sharing and open data, these are not ends in themselves. Arguments for data sharing are to reproduce research, to make public assets available to the public, to leverage investments in research, and to advance research and innovation.
To achieve these expected benefits of data sharing, data must actually be reused by others. Data sharing practices, especially motivations and incentives, have received far more study than has data reuse, perhaps because of the array of contested concepts on which reuse rests and the disparate contexts in which it occurs.
Here we explicate concepts of data, sharing, and open data as a means to examine data reuse. We explore distinctions between use and reuse of data.
Lastly we propose six research questions on data reuse worthy of pursuit by the community: How can uses of data be distinguished from reuses? When is reproducibility an essential goal? When is data integration an essential goal? What are the tradeoffs between collecting new data and reusing existing data? How do motivations for data collection influence the ability to reuse data? How do standards and formats for data release influence reuse opportunities?
We conclude by summarizing the implications of these questions for science policy and for investments in data reuse.
Since the early 2000s, there has been an explosion in the usage of the term open, arguably stemming from the advent of networked technologies — including the Internet and mobile technologies.
‘Openness’ seems to be everywhere, and takes many forms: from open knowledge, open education, open data and open science, to open Internet, open medical records systems and open innovation. These applications of openness are having a profound, and sometimes transformative, effect on social, political and economic life.
This explosion of the use of the term has led to multiple interpretations, ambiguities, and even misunderstandings, not to mention countless debates and disagreements over precise definitions.
The paper “Fifty shades of open” by Pomerantz and Peek (2016) highlighted the increasing ambiguity and even confusion surrounding this term. This article builds on Pomerantz and Peek’s attempt to disambiguate the term by offering an alternative understanding to openness — that of social praxis.
More specifically, our framing can be broken down into three social processes: open production, open distribution, and open consumption. Each process shares two traits that make them open: you don’t have to pay (free price), and anyone can participate (non-discrimination) in these processes.
We argue that conceptualizing openness as social praxis offers several benefits. First, it provides a way out of a variety of problems that result from ambiguities and misunderstandings that emerge from the current multitude of uses of openness.
Second, it provides a contextually sensitive understanding of openness that allows space for the many different ways openness is experienced — often very different from the way that more formal definitions conceptualize it.
Third, it points us towards an approach to developing practice-specific theory that we believe helps us build generalizable knowledge on what works (or not), for whom, and in what contexts.
Authors : David Nicholas, Anthony Watkinson, Cherifa Boukacem-Zeghmouri, Blanca Rodríguez-Bravo, Jie Xu, Abdullah Abrizah, Marzena Świgon, Eti Herman
Early career researchers (ECRs) are of great interest because they are the new (and biggest) wave of researchers. They merit long and detailed investigation, and towards this end, this overarching paper provides a summary of the firstyear findings of a 3-year, longitudinal study of 116 science and social science ECRs who have published nearly 1,200 papers and come from 7 countries and 81 universities.
ECRs were interviewed in their own languages face-to-face, by Skype, or telephone. The study focused on the attitudes and behaviours of ECRs with respect to scholarly communications and the extent to which they are adopting new and disruptive technologies, such as social media, online communities, and Open Science.
The main findings include: publishing in highimpact factor journals is the only reputational game in town; online scholarly communities, and ResearchGate in particular, are gaining ground; social media are beginning to have an impact, especially in the dissemination arena; outreach activities have become more important; libraries are becoming increasingly invisible to ECRs; Open Science is not gaining traction; and more transformational ideas are being expressed, especially in the US and UK.
Contemporary debates on « open science » mostly focus on the pub- lic accessibility of the products of scientific and academic work. In contrast, this paper presents arguments for « opening » the ongoing work of science.
That is, this paper is an invitation to rethink the university with an eye toward engaging the public in the dynamic, conceptual and representational work involved in creating scientific knowledge.
To this end, we posit that public computing spaces, a genre of open- ended, public learning environment where visitors interact with open source computing platforms to directly access, modify and create complex and authentic scientific work, can serve as a possible model of « open science » in the university.
Participation in Open Data initiatives require two semi-independent actions: the sharing of data produced by a researcher or group, and a consumer of shared data. Consumers of shared data range from people interested in validating the results of a given study to transformers of the data.
These transformers can add value to the dataset by extracting new relationships and information. The relationship between producers and consumers can be modeled in a game-theoretic context, namely by using a Prisoners’ Dilemma (PD) model to better understand potential barriers and benefits of sharing.
In this paper, we will introduce the problem of data sharing, consider assumptions about economic versus social payoffs, and provide simplistic payoff matrices of data sharing.
Several variations on the payoff matrix are given for different institutional scenarios, ranging from the ubiquitous acceptance of Open Science principles to a context where the standard is entirely non-cooperative. Implications for building a CC-BY economy are then discussed in context.