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.

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.

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.

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.