Scientific Value Weights more than Being Open or Toll Access:An analysis of the OA advantage in Nature and Science

Purpose:We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries.Design/methodology/approach:We design the indicators,hot-degree,and R-index to indicate a topic OA or TA advantages.First,according to the OA classification of the Web of Science(WoS),we collect data from the WoS by downloading OA and TA articles,letters,and reviews published in Nature and Science during 2010–2019.These papers are divided into three broad disciplines,namely biomedicine,physics,and others.Then,taking a discipline in a journal and using the classical Latent Dirichlet Allocation(LDA)to cluster 100 topics of OA and TA papers respectively,we apply the Pearson correlation coefficient to match the topics of OA and TA,and calculate the hot-degree and R-index of every OA-TA topic pair.Finally,characteristics of the discipline can be presented.In qualitative comparison,we choose some high-quality papers which belong to Nature remarkable papers or Science breakthroughs,and analyze the relations between OA/TA and citation numbers.Findings:The result shows that OA hot-degree in biomedicine is significantly greater than that of TA,but significantly less than that of TA in physics.Based on the R-index,it is found that OA advantages exist in biomedicine and TA advantages do in physics.Therefore,the dissemination of average scientific discoveries in all fields is not necessarily affected by OA or TA.However,OA promotes the spread of important scientific discoveries in high-quality papers.Research limitations:We lost some citations by ignoring other open sources such as arXiv and bioArxiv.Another limitation came from that Nature employs some strong measures for access-promoting subscription-based articles,on which the boundary between OA and TA became fuzzy.Practical implications:It is useful to select hot topics in a set of publications by the hotdegree index.The finding comprehensively reflects the differences of OA and TA in different disciplines,which is a useful reference when researchers choose the publishing way as OA or TA.Originality/value:We propose a new method,including two indicators,to explore and measure OA or TA advantages.

Programming with Conditionals: Epistemic Programming for Scientific Discovery

In order to provide scientists with a computational methodology and some computational tools to program their epistemic processes in scientific discovery, we are establishing a novel programming paradigm, named ‘Epistemic Programming’, which regards conditionals as the subject of computing, takes primary epistemic operations as basic operations of computing, and regards epistemic processes as the subject of programming. This paper presents our fundamental observations and assumptions on scientific discovery processes and their automation, research problems on modeling, automating, and programming epistemic processes, and an outline of our research project of Epistemic Programming.

Priority Disputes in Science in the Context of Conflicting Norms：The Case of Isaac Newton and Gottfried Leibniz Revisited

Thomas S. Kuhn is one of the leading philosophers and historians of science that investigated in-depth cases of simultaneous discoveries in science. Although his analysis of the discovery of energy conservation and oxygen did not focus sharply on the priority disputes involved, it is within such contexts that controversy about which scientist was the first to make a discovery takes place. Evidently, Kuhn＇s recourse to historical case studies is a clear departure from the standpoint of traditional mainstream philosophies of science （namely, logical positivism and falsificationism）, which cavalierly dismissed such concerns as irrelevant to philosophical reconstructions of science Challenges to orthodox logistic approaches were prompted by the realisation that the two dominant traditions mentioned above, in their excessive preoccupation with ＂the logical skeleton of science＂, have lost contact with real science. As a contribution to what Michael Polanyi referred to as post-critical philosophy, the present study reanalyses the tension-generating potentials of bipolar values shared by members of scientific communities. It traces the origins of the rebellion against logic-dominated philosophies of science, and identifies different post-positivist approaches that have eme^rged over the years which legitimise broadening the frontiers of the philosophy of science. Consequent upon that, some conflicting values or norms shared by members of scientific communities and how they affect the quest for scientific knowledge are underscored. Using as a case study the acrimonious priority dispute between Isaac Newton and Gottfried Leibniz concerning the discovery of calculus, the paper demonstrates that excessive concern for recognition which sometimes leads to protracted priority disputes tends to bring out the worst kind of behaviours towards colleagues even from the greatest scientists. We submit, by way of conclusion, that despite the heroic （almost god-like） reputation of such scientists, they are human and, therefore, subject to the vicissitudes of emotional turbulence just like everyone else.

Neural substrates of data-driven scientific discovery:An fMRI study during performance of number series completion task

Although much has been known about how humans psychologically perform data-driven scientific discovery,less has been known about its brain mechanism.The number series completion is a typical data-driven scientific discovery task,and has been demonstrated to possess the priming effect,which is attributed to the regularity identification and its subsequent extrapolation.In order to reduce the heterogeneities and make the experimental task proper for a brain imaging study,the number magnitude and arithmetic operation involved in number series completion tasks are further restricted.Behavioral performance in Experiment 1 shows the reliable priming effect for targets as expected.Then,a factorial design (the priming effect:prime vs.target;the period length:simple vs.complex) of event-related functional magnetic resonance imaging (fMRI) is used in Experiment 2 to examine the neural basis of data-driven scientific discovery.The fMRI results reveal a double dissociation of the left DLPFC (dorsolateral prefrontal cortex) and the left APFC (anterior prefrontal cortex) between the simple (period length=1) and the complex (period length=2) number series completion task.The priming effect in the left DLPFC is more significant for the simple task than for the complex task,while the priming effect in the left APFC is more significant for the complex task than for the simple task.The reliable double dissociation may suggest the different roles of the left DLPFC and left APFC in data-driven scientific discovery.The left DLPFC (BA 46) may play a crucial role in rule identification,while the left APFC (BA 10) may be related to mental set maintenance needed during rule identification and extrapolation.

The fourth scientific discovery paradigm for precision medicine and healthcare:Challenges ahead

With the progression of modern information techniques,such as next generation sequencing(NGS),Internet of Everything(IoE)based smart sensors,and artificial intelligence algorithms,data-intensive research and applications are emerging as the fourth paradigm for scientific discovery.However,we facemany challenges to practical application of this paradigm.In this article,10 challenges to data-intensive discovery and applications in precision medicine and healthcare are summarized and the future perspectives on next generation medicine are discussed.

Big Earth data:A new frontier in Earth and information sciences

Big data is a revolutionary innovation that has allowed the development of many new methods in scientific research.This new way of thinking has encouraged the pursuit of new discoveries.Big data occupies the strategic high ground in the era of knowledge economies and also constitutes a new national and global strategic resource.“Big Earth data”,derived from,but not limited to,Earth observation has macro-level capabilities that enable rapid and accurate monitoring of the Earth,and is becoming a new frontier contributing to the advancement of Earth science and significant scientific discoveries.Within the context of the development of big data,this paper analyzes the characteristics of scientific big data and recognizes its great potential for development,particularly with regard to the role that big Earth data can play in promoting the development of Earth science.On this basis,the paper outlines the Big Earth Data Science Engineering Project(CASEarth)of the Chinese Academy of Sciences Strategic Priority Research Program.Big data is at the forefront of the integration of geoscience,information science,and space science and technology,and it is expected that big Earth data will provide new prospects for the development of Earth science.