Search (8 results, page 1 of 1)

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Abstract

Prior research in status ordering has used numeric indicators to examine the impact of a status change on the perception of a scientist's work. This study measures the perception change directly as reflected in citation sentiment, with the attainment of a Nobel Prize in Chemistry or a Nobel Prize in Physiology or Medicine considered the status change. The article identifies 12,393 citances to 25 Nobel articles in PubMed Central and includes a control article set of 75 articles with 30,851 citances. The results show a moderate increase in citation sentiment toward Nobel articles postaward. Dynamically, for Nobel articles there is a steady sentiment increase, and a Nobel Prize seems to co-occur with this trend. This trend, however, is not evident in the control article set.

Type

a

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Abstract

The data paper is an emerging academic genre that focuses on the description of research data objects. However, there is a lack of empirical knowledge about this rising genre in quantitative science studies, particularly from the perspective of its linguistic features. To fill this gap, this research aims to offer a first quantitative examination of which rhetorical moves-rhetorical units performing a coherent narrative function-are used in data paper abstracts, as well as how these moves are used. To this end, we developed a new classification scheme for rhetorical moves in data paper abstracts by expanding a well-received system that focuses on English-language research article abstracts. We used this expanded scheme to classify and analyze rhetorical moves used in two flagship data journals, Scientific Data and Data in Brief. We found that data papers exhibit a combination of introduction, method, results, and discussion- and data-oriented moves and that the usage differences between the journals can be largely explained by journal policies concerning abstract and paper structure. This research offers a novel examination of how the data paper, a data-oriented knowledge representation, is composed, which greatly contributes to a deeper understanding of research data and its publication in the scholarly communication system.

Type

a

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Abstract

Inscriptions are defined as traces of scientific research production that are embodied in material artifacts and media, which encompass a wide variety of nonverbal forms such as graphs, diagrams, and tables. Inscription serves as a fundamental rhetorical device in research outputs and practices. As many inscriptions are deeply rooted in a scientific research paradigm, they can be used to evaluate the level of scientificity of a scientific field. This is specifically helpful to understand the relationships between research traditions in digital humanities (DH), a highly cross-disciplinary between various humanities and scientific traditions. This paper presents a quantitative, community-focused examination of how inscriptions are used in English-language research articles in DH journals. We randomly selected 252 articles published between 2011 and 2020 from a representative DH journal list, and manually classified the inscriptions and author domains in these publications. We found that inscriptions have been increasingly used during the past decade, and their uses are more intensive in publications led by STEM authors comparing to other domains. This study offers a timely survey of the disciplinary landscape of DH from the perspective of inscriptions and sheds light on how different research approaches collaborate and combat in the field of DH.

Series

JASIST special issue on digital humanities (DH): A. Landscapes of DH

Type

a

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Abstract

There are currently two dominant interface types for searching and browsing large image collections: keywordbased search, and searching by overall similarity to sample images. We present an alternative based on enabling users to navigate along conceptual dimensions that describe the images. The interface makes use of hierarchical faceted metadata and dynamically generated query previews. A usability study, in which 32 art history students explored a collection of 35,000 fine arts images, compares this approach to a standard image search interface. Despite the unfamiliarity and power of the interface (attributes that often lead to rejection of new search interfaces), the study results show that 90% of the participants preferred the metadata approach overall, 97% said that it helped them learn more about the collection, 75% found it more flexible, and 72% found it easier to use than a standard baseline system. These results indicate that a category-based approach is a successful way to provide access to image collections.

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Abstract

This study provides evidence of data set mentions and citations in multiple disciplines based on a content analysis of 600 publications in PLoS One. We find that data set mentions and citations varied greatly among disciplines in terms of how data sets were collected, referenced, and curated. While a majority of articles provided free access to data, formal ways of data attribution such as DOIs and data citations were used in a limited number of articles. In addition, data reuse took place in less than 30% of the publications that used data, suggesting that researchers are still inclined to create and use their own data sets, rather than reusing previously curated data. This paper provides a comprehensive understanding of how data sets are used in science and helps institutions and publishers make useful data policies.

Type

a

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Abstract

Although researchers have begun to investigate the difference in scientific impact between closed-access and open-access journals, studies that focus specifically on dynamic and disciplinary differences remain scarce. This study serves to fill this gap by using a large longitudinal dataset to examine these differences. Using CiteScore as a proxy for journal scientific impact, we employ a series of statistical tests to identify the quartile categories and disciplinary areas in which impact trends differ notably between closed- and open-access journals. We find that closed-access journals have a noticeable advantage in social sciences (for example, business and economics), whereas open-access journals perform well in medical and healthcare domains (for example, health profession and nursing). Moreover, we find that after controlling for a journal's rank and disciplinary differences, there are statistically more closed-access journals in the top 10%, Quartile 1, and Quartile 2 categories as measured by CiteScore; in contrast, more open-access journals in Quartile 4 gained scientific impact from 2011 to 2015. Considering dynamic and disciplinary trends in tandem, we find that more closed-access journals in Social Sciences gained in impact, whereas in biochemistry and medicine, more open-access journals experienced such gains.

Type

a

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Abstract

The data paper, an emerging scholarly genre, describes research data sets and is intended to bridge the gap between the publication of research data and scientific articles. Research examining how data papers report data events, such as data transactions and manipulations, is limited. The research reported on in this article addresses this limitation and investigated how data events are inscribed in data papers. A content analysis was conducted examining the full texts of 82 data papers, drawn from the curated list of data papers connected to the Global Biodiversity Information Facility. Data events recorded for each paper were organized into a set of 17 categories. Many of these categories are described together in the same sentence, which indicates the messiness of data events in the laboratory space. The findings challenge the degrees to which data papers are a distinct genre compared to research articles and they describe data-centric research processes in a through way. This article also discusses how our results could inform a better data publication ecosystem in the future.

Type

a

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Abstract

This study examines the relationship between team's gender composition and outputs of funded projects using a large data set of National Institutes of Health (NIH) R01 grants and their associated publications between 1990 and 2017. This study finds that while the women investigators' presence in NIH grants is generally low, higher women investigator presence is on average related to slightly lower number of publications. This study finds empirically that women investigators elect to work in fields in which fewer publications per million-dollar funding is the norm. For fields where women investigators are relatively well represented, they are as productive as men. The overall lower productivity of women investigators may be attributed to the low representation of women in high productivity fields dominated by men investigators. The findings shed light on possible reasons for gender disparity in grant productivity.

Type

a