Open science


Open science is the movement to make scientific research transparent and accessible to all levels of society through collaborative networks. It encompasses practices such as publishing open research, campaigning for open access, encouraging scientists to practice open-notebook science, broader dissemination and public engagement in science and generally making it easier to publish, access and communicate scientific knowledge.
Usage of the term varies substantially across disciplines, with a notable prevalence in the STEM disciplines. The term 'open research' has gained currency as a broader alternative to 'open science,' encompassing the humanities and arts alongside traditional scientific disciplines. The primary focus connecting all disciplines is the widespread uptake of new technologies and tools, and the underlying ecology of the production, dissemination and reception of knowledge from a research-based point-of-view.
As Tennant et al. note, the term open science "implicitly seems only to regard 'scientific' disciplines, whereas open scholarship can be considered to include research from the Arts and Humanities, as well as the different roles and practices that researchers perform as educators and communicators, and an underlying open philosophy of sharing knowledge beyond research communities."
Open science can be seen as continuing, rather than revolutionizing, practices that began in the 17th century with the academic journal, which enabled scientists to share resources in response to growing societal demand for scientific knowledge. The Open Science movement emerged from tension between scientists' desire for shared research resources and institutions' interest in protecting proprietary information for profit. Additionally, the status of open access and resources that are available for its promotion are likely to differ from one field of academic inquiry to another.

Principles

The six principles of open science are:
Scientific research typically involves collecting, analyzing, publishing, reanalyzing, critiquing, and reusing data. Proponents of open science identify a number of barriers that impede or dissuade the broad dissemination of scientific data.
These include financial paywalls of for-profit research publishers, restrictions on usage applied by publishers of data, poor formatting of data or use of proprietary software that makes it difficult to re-purpose, and cultural reluctance to publish data for fears of losing control of how the information is used.
According to the FOSTER taxonomy, Open science can often include aspects of Open access, Open data and the open source movement whereas modern science requires software to process data and information.
Open research computation also addresses the problem of reproducibility of scientific results.

Types

The term 'open science' lacks a single standardized definition or measurement framework. On the one hand, it has been referred to as a "puzzling phenomenon". On the other hand, the term has been used to encapsulate a series of principles that aim to foster scientific growth and its complementary access to the public. Sociologists Benedikt Fecher and Sascha Friesike have categorized Open Science into five schools of thought, each emphasizing different aspects of the movement.
According to Fecher and Friesike 'Open Science' encompasses diverse perspectives on how knowledge is created and shared. Fecher and Friesike identify five distinct schools of Open Science, each reflecting different priorities and approaches to the movement:

Infrastructure School

The infrastructure school views efficient research as dependent on openly available platforms, tools, and applications. It regards open science primarily as a technological challenge, focusing on internet-based infrastructure including software, applications, and computing networks. The infrastructure school is tied closely with the notion of "cyberscience", which describes the trend of applying information and communication technologies to scientific research, which has led to an amicable development of the infrastructure school. Specific elements of this prosperity include increasing collaboration and interaction between scientists, as well as the development of "open-source science" practices. The sociologists discuss two central trends in the infrastructure school:
1. Distributed computing: This trend encapsulates practices that outsource complex, process-heavy scientific computing to a network of volunteer computers around the world. The examples that the sociologists cite in their paper is that of the Open Science Grid, which enables the development of large-scale projects that require high-volume data management and processing, which is accomplished through a distributed computer network. Moreover, the grid provides the necessary tools that the scientists can use to facilitate this process.
2. Social and Collaboration Networks of Scientists: This trend encapsulates the development of software that makes interaction with other researchers and scientific collaborations much easier than traditional, non-digital practices. This trend emphasizes social media platforms and collaborative digital tools to enable research communication and coordination. De Roure and colleagues identify four key SVRE capabilities:
  • Managing and sharing research objects
  • Built-in incentives for making research objects available
  • Openness and extensibility for integrating diverse digital artifacts
  • Actionable functionality enabling active research use, not just storage.

    Measurement school

The measurement school focuses on developing alternative methods to determine scientific impact, recognizing its crucial role in researchers' reputations, funding, and careers. The authors then discuss other research indicating support for the measurement school. The three key currents of previous literature discussed by the authors are:
  • Peer review is widely acknowledged as time-consuming.
  • Citation impact, attributed to the authors, correlates more closely with journal circulation than with article quality.
  • Open Science–aligned publishing formats rarely conform to traditional journal structures that calculate impact factors.
Hence, this school argues that there are faster impact measurement technologies that can account for a range of publication types as well as social media web coverage of a scientific contribution to arrive at a complete evaluation of how impactful the science contribution was. The gist of the argument for this school is that hidden uses like reading, bookmarking, sharing, discussing and rating are traceable activities, and these traces can and should be used to develop a newer measure of scientific impact. The umbrella jargon for this new type of impact measurements is called altmetrics, coined in a 2011 article by Priem et al.,. Markedly, the authors discuss evidence that altmetrics differ from traditional webometrics which are slow and unstructured. Altmetrics are proposed to rely upon a greater set of measures that account for tweets, blogs, discussions, and bookmarks. Scholars propose that altmetrics should capture the entire research lifecycle, including collaboration patterns, to produce comprehensive impact measures. However, the authors are explicit in their assessment that few papers offer methodological details as to how to accomplish this. The authors use this and the general dearth of evidence to conclude that research in the area of altmetrics is still in its infancy.

Public School

According to the authors, the central concern of the school is to make science accessible to a wider audience. The inherent assumption of this school, as described by the authors, is that the newer communication technologies such as Web 2.0 allow scientists to open up the research process and also allow scientist to better prepare their "products of research" for interested non-experts. Hence, the school is characterized by two broad streams: one argues for the access of the research process to the masses, whereas the other argues for increased access to the scientific product to the public.
  • Accessibility to the Research Process: Communication technology allows not only for the constant documentation of research but also promotes the inclusion of many different external individuals in the process itself. The authors cite citizen science – the participation of non-scientists and amateurs in research. The authors discuss instances in which gaming tools allow scientists to harness the brain power of a volunteer workforce to run through several permutations of protein-folded structures. This allows for scientists to eliminate many more plausible protein structures while also "enriching" the citizens about science. The authors also discuss a common criticism of this approach: the amateur nature of the participants threatens to pervade the scientific rigor of experimentation.
  • Comprehensibility of the Research Result: This stream of research concerns itself with making research understandable for a wider audience. The authors describe a host of authors that promote the use of specific tools for scientific communication, such as microblogging services, to direct users to relevant literature. The authors claim that this school proposes that it is the obligation of every researcher to make their research accessible to the public. The authors then proceed to discuss if there is an emerging market for brokers and mediators of knowledge that is otherwise too complicated for the public to grasp.

    Democratic school

The democratic school focuses on public access to research products rather than research processes or comprehensibility. The central concern of the school is with the legal and other obstacles that hinder the access of research publications and scientific data to the public. Proponents assert that any research product should be freely available. and that everyone has the same, equal right of access to knowledge, especially in the instances of state-funded experiments and data. Two central currents characterize this school: Open Access and Open Data.
  • Open Data: Opposition to the notion that publishing journals should claim copyright over experimental data, which prevents the re-use of data and therefore lowers the overall efficiency of science in general. The claim is that journals have no use of the experimental data and that allowing other researchers to use this data will be fruitful. Despite open data advocacy, only 25 percent of researchers actively share their datasets, citing the administrative burden as a primary obstacle.
  • Open Access to Research Publication: According to this school, there is a gap between the creation and sharing of knowledge. Proponents argue that even though scientific knowledge doubles every 5 years, access to this knowledge remains limited. These proponents consider access to knowledge as a necessity for human development, especially in the economic sense.