Archives des mots-clés : open science

Reproducibility, Correctness, and Buildability: the Three Principles for Ethical Public Dissemination of Computer Science and Engineering Research

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“We propose a system of three principles of public dissemination, which we call reproducibility, correctness, and buildability, and make the argument that consideration of these principles is a necessary step when publicly disseminating results in any evidence-based scientific or engineering endeavor. We examine how these principles apply to the release and disclosure of the four elements associated with computer science research: theory, algorithms, code, and data. Reproducibility refers to the capability to reproduce fundamental results from released details. Correctness refers to the ability of an independent reviewer to verify and validate the results of a paper. We introduce the new term buildability to indicate the ability of other researchers to use the published research as a foundation for their own new work. This is more broad than extensibility, as it requires that the published results have reached a level of completeness that the research can be used for its stated purpose, and has progressed beyond the level of a preliminary idea. We argue that these three principles are not being sufficiently met by current publications and proposals in computer science and engineering, and represent a goal for which publishing should continue to aim. We introduce standards for the evaluation of reproducibility, correctness, and buildability in relation to the varied elements of computer science research and discuss how they apply to proposals, workshops, conferences, and journal publications, making arguments for appropriate standards of each principle in these settings. We address modern issues including big data, data confidentiality, privacy, security, and privilege. Our examination raises questions for discussion in the community on the appropriateness of publishing works that fail to meet one, some, or all of the stated principles.”

URL : http://research.kristinrozier.com/papers/RozierRozierEthics2014.pdf

GigaDB promoting data dissemination and reproducibility Often…

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GigaDB: promoting data dissemination and reproducibility :

“Often papers are published where the underlying data supporting the research are not made available because of the limitations of making such large data sets publicly and permanently accessible. Even if the raw data are deposited in public archives, the essential analysis intermediaries, scripts or software are frequently not made available, meaning the science is not reproducible. The GigaScience journal is attempting to address this issue with the associated data storage and dissemination portal, the GigaScience database (GigaDB). Here we present the current version of GigaDB and reveal plans for the next generation of improvements. However, most importantly, we are soliciting responses from you, the users, to ensure that future developments are focused on the data storage and dissemination issues that still need resolving.”

URL : http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3950661/

Access to Research Inputs Open Science Versus the…

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Access to Research Inputs: Open Science Versus the Entrepreneurial University :

“The viability of modern open science norms and practices depend on public disclosure of new knowledge, methods, and materials. However, increasing industry funding of research can restrict the dissemination of results and materials. We show, through a survey sample of 837 German scientists in life sciences, natural sciences, engineering, and social sciences, that scientists who receive industry funding are twice as likely to deny requests for research inputs as those who do not. Receiving external funding in general does not affect denying others access. Scientists who receive external funding of any kind are, however, 50% more likely to be denied access to research materials by others, but this is not affected by being funded specifically by industry.”

URL : http://ssrn.com/abstract=2407437

Opening Science : The Evolving Guide on How the Internet is Changing Research, Collaboration and Scholarly Publishing

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“Modern information and communication technologies, together with a cultural upheaval within the research community, have profoundly changed research in nearly every aspect. Ranging from sharing and discussing ideas in social networks for scientists to new collaborative environments and novel publication formats, knowledge creation and dissemination as we know it is experiencing a vigorous shift towards increased transparency, collaboration and accessibility. Many assume that research workflows will change more in the next 20 years than they have in the last 200. This book provides researchers, decision makers, and other scientific stakeholders with a snapshot of the basics, the tools, and the underlying visions that drive the current scientific (r)evolution, often called ‘Open Science.’”

URL : https://microblogging.infodocs.eu/wp-content/uploads/2015/05/opening_science.pdf

Related URL : http://link.springer.com/book/10.1007%2F978-3-319-00026-8

Transformation of Science Communication in the Age of Social Media

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The aim of the present article is to discuss several consequences of the Open Science from a perspective of science communication and philosophy of communication. Apart from the purely communicative and philosophical issues, the paper deals with the questions that concern the science populariza- tion process through social media (especially Twitter and blogs).

The article consists of three sections: the first one suggests a definition of science communication and social media, the second examines the transformation of science in the Age of the Internet and considers the influence of social media on science communication, the third and final one presents some case studies and philosophical observations.

The most important conclusion to be reached here is that the social media have changed science and science communication. Twitter and blogs as novelty tools of science communication can be useful and meaningful for both science and society. Furthermore, social media can be used to facilitate broader involvement of citizens in the discussion about science.

URL : http://teorievedy.flu.cas.cz/index.php/tv/article/view/172

If We Share Data, Will Anyone Use Them? Data Sharing and Reuse in the Long Tail of Science and Technology

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Research on practices to share and reuse data will inform the design of infrastructure to support data collection, management, and discovery in the long tail of science and technology. These are research domains in which data tend to be local in character, minimally structured, and minimally documented. We report on a ten-year study of the Center for Embedded Network Sensing (CENS), a National Science Foundation Science and Technology Center.

We found that CENS researchers are willing to share their data, but few are asked to do so, and in only a few domain areas do their funders or journals require them to deposit data. Few repositories exist to accept data in CENS research areas.. Data sharing tends to occur only through interpersonal exchanges. CENS researchers obtain data from repositories, and occasionally from registries and individuals, to provide context, calibration, or other forms of background for their studies. Neither CENS researchers nor those who request access to CENS data appear to use external data for primary research questions or for replication of studies.

CENS researchers are willing to share data if they receive credit and retain first rights to publish their results. Practices of releasing, sharing, and reusing of data in CENS reaffirm the gift culture of scholarship, in which goods are bartered between trusted colleagues rather than treated as commodities.

URL : If We Share Data, Will Anyone Use Them?

DOI : 10.1371/journal.pone.0067332

Toward Reproducible Computational Research: An Empirical Analysis of Data and Code Policy Adoption by Journals

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Journal policy on research data and code availability is an important part of the ongoing shift toward publishing reproducible computational science. This article extends the literature by studying journal data sharing policies by year (for both 2011 and 2012) for a referent set of 170 journals.

We make a further contribution by evaluating code sharing policies, supplemental materials policies, and open access status for these 170 journals for each of 2011 and 2012.

We build a predictive model of open data and code policy adoption as a function of impact factor and publisher and find higher impact journals more likely to have open data and code policies and scientific societies more likely to have open data and code policies than commercial publishers.

We also find open data policies tend to lead open code policies, and we find no relationship between open data and code policies and either supplemental material policies or open access journal status.

Of the journals in this study, 38% had a data policy, 22% had a code policy, and 66% had a supplemental materials policy as of June 2012. This reflects a striking one year increase of 16% in the number of data policies, a 30% increase in code policies, and a 7% increase in the number of supplemental materials policies.

We introduce a new dataset to the community that categorizes data and code sharing, supplemental materials, and open access policies in 2011 and 2012 for these 170 journals.

URL : http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0067111