Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userIs preprint the future of science? A thirty year journey of online preprint services
108
0
0.0
(
0
)
Added by
Zhihong (Iris) Shen
Publication date
2021
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
Preprint is a version of a scientific paper that is publicly distributed preceding formal peer review. Since the launch of arXiv in 1991, preprints have been increasingly distributed over the Internet as opposed to paper copies. It allows open online access to disseminate the original research within a few days, often at a very low operating cost. This work overviews how preprint has been evolving and impacting the research community over the past thirty years alongside the growth of the Web. In this work, we first report that the number of preprints has exponentially increased 63 times in 30 years, although it only accounts for 4% of research articles. Second, we quantify the benefits that preprints bring to authors: preprints reach an audience 14 months earlier on average and associate with five times more citations compared with a non-preprint counterpart. Last, to address the quality concern of preprints, we discover that 41% of preprints are ultimately published at a peer-reviewed destination, and the published venues are as influential as papers without a preprint version. Additionally, we discuss the unprecedented role of preprints in communicating the latest research data during recent public health emergencies. In conclusion, we provide quantitative evidence to unveil the positive impact of preprints on individual researchers and the community. Preprints make scholarly communication more efficient by disseminating scientific discoveries more rapidly and widely with the aid of Web technologies. The measurements we present in this study can help researchers and policymakers make informed decisions about how to effectively use and responsibly embrace a preprint culture.
rate research
Read More
Below we analyze the `critic statements made in the Preprint arXiv:1301.1828v1 [nucl-th]. The doubtful scientific argumentation of the authors of the Preprint arXiv:1301.1828v1 [nucl-th] is also discussed.
Computer science is a relatively young discipline combining science, engineering, and mathematics. The main flavors of computer science research involve the theoretical development of conceptual models for the different aspects of computing and the more applicative building of software artifacts and assessment of their properties. In the computer science publication culture, conferences are an important vehicle to quickly move ideas, and journals often publish deep
Mentorship in science is crucial for topic choice, career decisions, and the success of mentees and mentors. Typically, researchers who study mentorship use article co-authorship and doctoral dissertation datasets. However, available datasets of this type focus on narrow selections of fields and miss out on early career and non-publication-related interactions. Here, we describe MENTORSHIP, a crowdsourced dataset of 743176 mentorship relationships among 738989 scientists across 112 fields that avoids these shortcomings. We enrich the scientists profiles with publication data from the Microsoft Academic Graph and semantic representations of research using deep learning content analysis. Because gender and race have become critical dimensions when analyzing mentorship and disparities in science, we also provide estimations of these factors. We perform extensive validations of the profile--publication matching, semantic content, and demographic inferences. We anticipate this dataset will spur the study of mentorship in science and deepen our understanding of its role in scientists career outcomes.
I try to describe the stepwise progress in proving that massive black holes do exist in the Universe. As compared to forty years ago, measurements have pushed the size of the 4 million solar mass concentration in the Galactic Center downward by almost 10^6, and its density up by 10^18. Looking ahead toward the future, the question is probably no longer whether SgrA* must be a MBH, but rather whether GR is correct on the scales of the event horizon, whether space-time is described by the Kerr metric and whether the no hair theorem holds. Further improvements of the VLT interferometer GRAVITY (to GRAVITY+) and the next generation 25-40m telescopes (the ESO-ELT, the TMT and the GMT) promise further progress. A test of the no hair theorem in the Galactic Center might come from combining the stellar dynamics with EHT measurements of the photon ring of SgrA*.
The work of astronomers is getting more complex and advanced as the progress of computer development occurs. With improved computing capabilities and increased data flow, more sophisticated software is required in order to interpret, and fully exploit, astronomic data. However, it is not possible for every astronomer to also be a software specialist. As history has shown, the work of scientists always becomes increasingly specialised, and we here argue in favour of another, at least partial, split between programmers and interpreters. In this presentation we outline our vision for a new approach and symbiosis between software specialists and scientists, and present its advantages along with a simple test case.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
